chore(release): bump SDK, CLI, and plugin versions (#6800)

Co-authored-by: mintlify[bot] <109931778+mintlify[bot]@users.noreply.github.com>

.claude-plugin/marketplace.json

@@ -12,7 +12,7 @@
       "name": "mem0",
       "source": "./integrations/mem0-plugin",
       "description": "Mem0 memory layer for AI applications. Add persistent memory, personalization, and semantic search to Claude workflows.",
-      "version": "0.2.11"
+      "version": "0.2.14"
     }
   ]
 }

.cursor-plugin/marketplace.json

@@ -12,7 +12,7 @@
       "name": "mem0",
       "source": "./integrations/mem0-plugin",
       "description": "Mem0 memory layer for AI applications. Add persistent memory, personalization, and semantic search.",
-      "version": "0.2.11"
+      "version": "0.2.14"
     }
   ]
 }

.github/ISSUE_TEMPLATE/bug_report.yml

@@ -9,12 +9,10 @@ body:
       label: Component
       description: Which part of mem0 is affected?
       options:
-        - Core / Python SDK
+        - Python SDK
         - TypeScript SDK
-        - Vector Store (Qdrant, PGVector, Redis, Chroma, etc.)
-        - Graph Memory (Neo4j, Memgraph, etc.)
-        - Ollama / Local Models
-        - OpenClaw
+        - Vector Store
+        - Plugin
         - REST API
         - Other
     validations:

.github/ISSUE_TEMPLATE/feature_request.yml

@@ -9,14 +9,11 @@ body:
       label: Component
       description: Which part of mem0 does this relate to?
       options:
-        - Core / Python SDK
+        - Python SDK
         - TypeScript SDK
-        - Vector Store (Qdrant, PGVector, Redis, Chroma, etc.)
-        - Graph Memory (Neo4j, Memgraph, etc.)
-        - Ollama / Local Models
-        - OpenClaw
+        - Vector Store
+        - Plugin
         - REST API
-        - Benchmarks / Evals
         - Other
     validations:
       required: true

.github/advanced-issue-labeler.yml

@@ -1,18 +1,15 @@
-# Maps dropdown selections to GitHub labels
-# Used by the advanced-issue-labeler GitHub Action
-
-component:
-  - label: "sdk-python"
-    matcher: "Core / Python SDK"
-  - label: "sdk-typescript"
-    matcher: "TypeScript SDK"
-  - label: "vector-store"
-    matcher: "Vector Store"
-  - label: "graph-memory"
-    matcher: "Graph Memory"
-  - label: "ollama"
-    matcher: "Ollama"
-  - label: "openclaw"
-    matcher: "OpenClaw"
-  - label: "rest-api"
-    matcher: "REST API"
+policy:
+  - section:
+      - id: ['component']
+        block-list: ['Other']
+        label:
+          - name: 'sdk-python'
+            keys: ['Python SDK']
+          - name: 'sdk-typescript'
+            keys: ['TypeScript SDK']
+          - name: 'vector-store'
+            keys: ['Vector Store']
+          - name: 'plugin'
+            keys: ['Plugin']
+          - name: 'rest-api'
+            keys: ['REST API']

.github/component-keywords.json

@@ -0,0 +1,40 @@
+{
+  "language": {
+    "sdk-python": [
+      "python", "pip install", "pypi", "pyproject", "requirements.txt",
+      "from mem0", "import mem0", "traceback", "pydantic", "asyncmemory",
+      "poetry", "virtualenv", "venv", "conda", "pytest", "async def"
+    ],
+    "sdk-typescript": [
+      "typescript", "javascript", "pnpm", "yarn", "node.js", "nodejs",
+      "mem0-ts", "mem0ai/oss", "tsconfig", "await import",
+      "=> {", "undefined is not"
+    ]
+  },
+  "area": {
+    "plugin": [
+      "openclaw", "openclaw-mem0", "openclaw.json", "openclaw plugin",
+      "claude code", "opencode", "pi agent", "mem0-plugin",
+      "cursor plugin", "codex plugin", "editor plugin"
+    ],
+    "cli": ["mem0-cli", "@mem0/cli", "npx mem0", "command line"],
+    "vector-store": [
+      "pgvector", "pinecone", "chroma", "chromadb", "weaviate",
+      "milvus", "faiss", "vector store", "vectorstore",
+      "elasticsearch", "supabase", "azure ai search",
+      "s3 vectors", "mongodb"
+    ],
+    "integrations": [
+      "vercel ai", "vercel-ai-sdk", "@mem0/vercel-ai-provider",
+      "llamaindex", "crewai", "autogen", "langgraph"
+    ],
+    "rest-api": [
+      "rest api", "fastapi", "docker-compose", "/v1/memories",
+      "localhost:8000", "localhost:8888", "curl -x", "http endpoint"
+    ],
+    "documentation": [
+      "docs.mem0.ai", "documentation", "typo", "readme", "docstring", "broken link",
+      "issue on docs", "docs:", "link to the docs page", "issue with current documentation"
+    ]
+  }
+}

.github/labeler.yml

@@ -0,0 +1,59 @@
+sdk-python:
+  - changed-files:
+      - any-glob-to-any-file:
+          - 'mem0/**'
+          - 'tests/**'
+          - 'cli/python/**'
+          - 'pyproject.toml'
+          - 'poetry.lock'
+
+sdk-typescript:
+  - changed-files:
+      - any-glob-to-any-file:
+          - 'mem0-ts/**'
+          - 'cli/node/**'
+
+vector-store:
+  - changed-files:
+      - any-glob-to-any-file:
+          - 'mem0/vector_stores/**'
+          - 'mem0-ts/src/oss/src/vector_stores/**'
+
+rest-api:
+  - changed-files:
+      - any-glob-to-any-file: 'server/**'
+
+integrations:
+  - changed-files:
+      - any-glob-to-any-file: 'integrations/**'
+
+plugin:
+  - changed-files:
+      - all-globs-to-any-file:
+          - 'integrations/**'
+          - '!integrations/vercel-ai-sdk/**'
+      - any-glob-to-any-file:
+          - 'skills/**'
+          - '.agents/**'
+          - '.claude-plugin/**'
+          - '.codex-plugin/**'
+          - '.cursor-plugin/**'
+          - 'marketplace.json'
+
+cli:
+  - changed-files:
+      - any-glob-to-any-file: 'cli/**'
+
+documentation:
+  - changed-files:
+      - any-glob-to-any-file:
+          - 'docs/**'
+          - 'examples/**'
+          - '*.md'
+
+ci:
+  - changed-files:
+      - any-glob-to-any-file:
+          - '.github/**'
+          - 'scripts/**'
+          - '.pre-commit-config.yaml'

.github/scripts/infer-component-labels.js

@@ -0,0 +1,44 @@
+const fs = require('fs');
+
+function componentLabels(keywords) {
+  return Object.values(keywords).flatMap(Object.keys);
+}
+
+function toMatcher(term) {
+  const escaped = term.replace(/[.*+?^${}()|[\]\\]/g, '\\$&');
+  const prefix = /^[a-z0-9]/i.test(term) ? '\\b' : '';
+  return new RegExp(prefix + escaped, 'i');
+}
+
+function scoreGroup(text, group) {
+  let winner = null;
+  let best = 0;
+  for (const [label, terms] of Object.entries(group)) {
+    const score = terms.reduce((n, term) => n + (toMatcher(term).test(text) ? 1 : 0), 0);
+    if (score > best) {
+      winner = label;
+      best = score;
+    }
+  }
+  return winner;
+}
+
+const UMBRELLA = { plugin: 'integrations' };
+
+function inferComponentLabels(text, keywords) {
+  if (!text) return [];
+  const labels = [scoreGroup(text, keywords.language), scoreGroup(text, keywords.area)].filter(
+    Boolean,
+  );
+  for (const label of labels.slice()) {
+    const parent = UMBRELLA[label];
+    if (parent && !labels.includes(parent)) labels.push(parent);
+  }
+  return labels;
+}
+
+function loadKeywords(file) {
+  return JSON.parse(fs.readFileSync(file, 'utf8'));
+}
+
+module.exports = { componentLabels, inferComponentLabels, loadKeywords };

.github/scripts/infer-component-labels.test.js

@@ -0,0 +1,102 @@
+const assert = require('assert');
+const path = require('path');
+const { inferComponentLabels, loadKeywords } = require('./infer-component-labels.js');
+
+const keywords = loadKeywords(path.join(__dirname, '..', 'component-keywords.json'));
+
+const cases = [
+  {
+    number: 6210,
+    title: "but(anthropic): sampling parameters returns 400 error for new model",
+    body: "### Component\n\nCore / Python SDK\n\n### Description\n\n### Summary\n\nWhen using Anthropic latest models such as `claude-opus-4-7`, `claude-opus-4-8`, or `claude-sonnet-5`, Mem0 still sends sampling parameters like `temperature` / `top_p`. These models do not support those parameters, causing Anthropic API requests to fail.\n\nSee https://platform.claude.com/docs/en/about-claude/models/migration-guide\n\n### Steps to Reproduce\n\n```python\n  from mem0 import Memory\n\n  m = Memory.from_config({\n      \"llm\": {\n          \"provider\": \"anthropic\",\n          \"config\": {\n              \"model\": \"claude-opus-4-8\",\n              \"api_key\": \"your-anthropic-api-key\"\n          },\n      },\n      ...\n  })\n```\n\n### Expected Behavior\n\nMem0 should detect Anthropic models that do not support sampling parameters and omit temperature and top_p from the request.\n\nFor models that still support sampling parameters, such as claude-opus-4-6, claude-sonnet-4-6, and claude-haiku-4-5, Mem0 should continue sending supported sampling parameters till they're deprecated.\n\n### Actual Behavior\n\nMem0 includes temperature by default for Anthropic requests. With newer Anthropic models that do not support sampling parameters, the API request fails because unsupported parameters are sent.\n\n### Environment\n\n  - mem0 version: 2.0.11\n  - Python/Node version: Python 3.11\n  - OS: macOS\n",
+    expected: ["sdk-python"],
+  },
+  {
+    number: 5770,
+    title: "feat(ts-sdk): add FastEmbed embedding provider",
+    body: "## Summary\n\nThe Python SDK supports **FastEmbed** as an embedding provider, but the TypeScript OSS SDK (`mem0ai/oss`) does not. Add it to bring the TS SDK to parity.\n\n| | |\n|---|---|\n| Python reference | `mem0/embeddings/fastembed.py` |\n| Registered in (Python) | `mem0/utils/factory.py` (EmbedderFactory) |\n| Target file (TypeScript) | `mem0-ts/src/oss/src/embeddings/fastembed.ts` |\n| Suggested implementation | Use the `fastembed` npm package (ONNX local embeddings). |\n\n## Requirements\n\n- [ ] Implement `FastEmbedEmbedder` in `mem0-ts/src/oss/src/embeddings/fastembed.ts`, extending `Embedder` (`mem0-ts/src/oss/src/embeddings/base.ts`) and mirroring the Python provider's behavior (embed / embedBatch).\n- [ ] Register the `\"fastembed\"` provider in `mem0-ts/src/oss/src/utils/factory.ts` (EmbedderFactory).\n- [ ] Add config typing in `mem0-ts/src/oss/src/types/`.\n- [ ] Add a unit test under `mem0-ts/src/oss/src/tests/`.\n- [ ] Add `fastembed` to `mem0-ts/package.json` (optional/peer dependency, lazy-imported like other providers).\n- [ ] Update docs under `docs/` if this provider is user-facing.\n\n## Reference pattern\n\nMirror an existing TS provider: `embeddings/openai.ts`.\n\n## Notes\n\n`fastembed` (v2.x) is the JS port of Qdrant's FastEmbed — local/offline embeddings. Mirror the default model in `mem0/embeddings/fastembed.py`.\n\n---\n_Part of the TypeScript ↔ Python SDK provider-parity effort. One provider per issue (atomic)._\n",
+    expected: ["sdk-typescript"],
+  },
+  {
+    number: 3940,
+    title: "Milvus database will return distance not similarity score",
+    body: "### 🐛 Describe the bug\n\nMilvus database will return distance not similarity score\n\n## in milvus.py\n\ndef _parse_output(self, data: list):\n        \"\"\"\n        Parse the output data.\n\n        Args:\n            data (Dict): Output data.\n\n        Returns:\n            List[OutputData]: Parsed output data.\n        \"\"\"\n        memory = []\n\n        for value in data:\n            uid, score, metadata = (\n                value.get(\"id\"),\n                value.get(\"distance\"),  # here\n                value.get(\"entity\", {}).get(\"metadata\"),\n            )\n\n            memory_obj = OutputData(id=uid, score=score, payload=metadata)\n            memory.append(memory_obj)\n\n        return memory\n",
+    expected: ["vector-store"],
+  },
+  {
+    number: 5290,
+    title: "Recall search failed: Bad Request Using OpenAI Embedding Model",
+    body: "### Component\n\nOpenClaw\n\n### Description\n\n### Summary\nuse openclaw.json config:\n\n```json\n...\n\"embedder\": {\n              \"provider\": \"openai\",\n              \"config\": {\n                \"model\": \"bge-base-zh-v1.5\",\n                \"embedding_dims\": 1024,\n                \"embeddingDims\": 1024,\n                \"url\": \"https://xxxxxxxxx/v1\",\n                \"apiKey\": \"xxxxxxxxxxxx\"\n              }\n            },\n\"vectorStore\": {\n              \"provider\": \"qdrant\",\n              \"config\": {\n                \"url\": \"http://qdrant:6333\",\n                \"apiKey\": \"${QDRANT_API_KEY}\",\n                \"collectionName\": \"mem0\",\n                \"embeddingModelDims\": 1024\n              }\n            }\n```\n```\n\nopenclaw log info is：\n\n```\n23:14:20 Api key is used with unsecure connection.\n23:14:21 [mem0] Recall search failed: Bad Request\n23:14:21 [plugins] openclaw-mem0: skills-mode recall (strategy=smart) injecting 0 memories (~20 tokens)\n23:14:22 [ws] ⇄ res ✓ sessions.list 256ms conn=d1eb9bc4…17da id=201b8113…c9dc\n23:14:22 [ws] ⇄ res ✓ sessions.list 264ms conn=d1eb9bc4…17da id=4939f962…2f16\n23:14:34 [ws] ⇄ res ✓ sessions.list 250ms conn=d1eb9bc4…17da id=f7ad503f…baa6\n23:15:12 [mem0] **Recall search failed: Bad Request**\n23:15:12 [plugins] openclaw-mem0: skills-mode recall (strategy=smart) injecting 0 memories (~20 tokens)\n23:15:12 [ws] ⇄ res ✓ sessions.list 288ms conn=d1eb9bc4…17da id=9e20bb86…371e\n23:15:13 [ws] ⇄ res ✓ sessions.list 268ms conn=d1eb9bc4…17da id=3b49a2ad…7ada\n23:15:20 [ws] ⇄ res ✓ sessions.list 235ms conn=d1eb9bc4…17da id=a192da30…069f\n```\n\n### Actual Behavior\n\nembedding model response ok,response message has 1024 vectors,but the vectors are submitted to vector-db:qdrant with all zero vectors,and vectors has only 256 size.\n\n```http\nPOST /collections/mem0/points/search HTTP/1.1\nhost: qdrant:6333\nconnection: keep-alive\nuser-agent: qdrant-js/1.13.0\napi-key: xxxxxxxxxxxxxxxxxxxxxxxxxxxx\nContent-Type: application/json\nAccept: application/json\naccept-language: *\nsec-fetch-mode: cors\naccept-encoding: gzip, deflate\ncontent-length: 651\n\n{\"vector\":[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],\"limit\":120,\"offset\":0,\"filter\":{\"must\":[{\"key\":\"user_id\",\"match\":{\"value\":\"agent\"}}]},\"with_payload\":true,\"with_vector\":false}\n\n**HTTP/1.1 400 Bad Request**\ntransfer-encoding: chunked\ncontent-type: application/json\nvary: accept-encoding, Origin, Access-Control-Request-Method, Access-Control-Request-Headers\ncontent-encoding: gzip\n\n```\n\n### Expected Behavior\n\nembedding model response ok by tcpdump, response message has 1024 vectors,and this vectors are submitted to vector-db:qdrant with the same vectors,and vectors has also 1024 size.\n\n\n### Environment\n\n- openclaw-mem0 version: 1.0.11\n- qdrant: 1.13.6\n",
+    expected: ["plugin", "integrations"],
+  },
+  {
+    number: 3696,
+    title: "Cannot set expiration_date for memory in REST API server (Docker Compose)",
+    body: "### 🐛 Describe the bug\n\nI'm using docker compose to deploy a REST API server. When adding memory, I'm unable to set the expiration_date. Is this feature not supported?",
+    expected: ["rest-api"],
+  },
+  {
+    number: 6252,
+    title: "cursor: on_file_read_cursor.sh ignores auto_search / MEM0_AUTO_SEARCH",
+    body: "### Component\n\nCursor / mem0-plugin\n\n### Description\n\n`on_file_read_cursor.sh` never checks `MEM0_AUTO_SEARCH`. In Claude Code, #6065/#6071 added a guard on `on_file_read.sh`, but the Cursor PreToolUse variant still always calls `file_context.py` (and thus Platform search) once `MEM0_API_KEY` is set.\n\n### Expected\n\nWhen `auto_search: false` / `MEM0_AUTO_SEARCH=false`, `on_file_read_cursor.sh` should exit 0 without searching.\n\n### Actual\n\nTimeline search still runs.\n\n### Related\n\n#6065, #6071, #6250\n",
+    expected: ["plugin", "integrations"],
+  },
+  {
+    number: 6032,
+    title: "docs: fix typos and punctuation errors across docs",
+    body: "### Description\n\n### Page\nMultiple pages — see list below.\n\n### What's Wrong or Missing\n1. https://docs.mem0.ai/components/llms/overview — \"a llm\" should be \"an LLM\"\n2. https://docs.mem0.ai/components/vectordbs/dbs/azure — 2 comma splices + \"setup\" used as a verb (should be \"set up\")\n3. https://docs.mem0.ai/components/embedders/models/azure_openai — \"from the Azure.\" is an incomplete sentence\n4. https://docs.mem0.ai/components/llms/models/azure_openai — same incomplete \"from the Azure\" phrasing\n5. https://docs.mem0.ai/cookbooks/companions/voice-companion-openai — \"an important information\" (uncountable noun)\n6. https://docs.mem0.ai/cookbooks/essentials/exporting-memories — comma splice\n7. https://docs.mem0.ai/cookbooks/integrations/tavily-search — \"usecase\" should be \"use case\"\n8. https://docs.mem0.ai/cookbooks/overview — broken parallelism in bullet list\n9. README.md — \"Github App\" should be \"GitHub App\"\n10. https://docs.mem0.ai/platform/overview — table cell not capitalized like other rows\n\n### Suggested Fix\nApply the corrections listed above for each page. I will submit a PR soon addressing all of the issues mentioned.",
+    expected: ["documentation"],
+  },
+];
+
+const cliRegressionCase = {
+  number: 3144,
+  title: "Bug Report: Memory Score Does Not Match Expected Relevance in Local Search",
+  body: "### 🐛 Describe the bug\n\n#### Description\n\nWhen using the locally deployed `mem0` server, the returned memory `score` from the `search` interface does not align with the expected semantic relevance. In particular, irrelevant or less relevant memories sometimes receive higher scores than directly related ones.\n\n#### Reproduction Steps\n\n```python\nmem0 = mem0_client(mode=\"local\")\nprint(\"Mem0 client initialized successfully.\")\n\nprint(\"Adding memories...\")\nresult = mem0.add(messages=[\n    {\"role\": \"user\", \"content\": \"I like drinking coffee in the morning\"},\n    {\"role\": \"user\", \"content\": \"I enjoy reading books at night\"}\n], user_id=\"alice\")\nprint(\"Memory added:\", result)\n\nprint(\"Searching memories...\")\nsearch_result = mem0.search(query=\"coffee\", user_id=\"alice\", top_k=2)\nprint(\"Search results:\", search_result)\n```\n\n#### Actual Output\n\n```json\n{\n  \"results\": [\n    {\n      \"id\": \"5099b5be-c673-4f09-99de-a196f43b6476\",\n      \"memory\": \"Likes drinking coffee in the morning\",\n      \"score\": 0.5115111920687857\n    },\n    {\n      \"id\": \"08df5c51-c52b-4c45-a5b6-b3f864ea149a\",\n      \"memory\": \"Enjoys reading books at night\",\n      \"score\": 0.7755568273863331\n    }\n  ],\n  \"relations\": [\n    {\"source\": \"coffee\", \"relationship\": \"consumed_in\", \"destination\": \"morning\"},\n    {\"source\": \"user_id:_alice\", \"relationship\": \"likes\", \"destination\": \"coffee\"},\n    {\"source\": \"user_id:_alice\", \"relationship\": \"likes_drinking\", \"destination\": \"coffee\"},\n    {\"source\": \"user_id:_alice\", \"relationship\": \"in_time\", \"destination\": \"morning\"},\n    {\"source\": \"user_id:_alice\", \"relationship\": \"drinks_in\", \"destination\": \"morning\"}\n  ]\n}\n```\n\n#### Expected Behavior\n\nThe memory `\"Likes drinking coffee in the morning\"` should have a **higher score** than `\"Enjoys reading books at night\"` when querying for `\"coffee\"`, since it is directly semantically related.",
+};
+
+let failures = 0;
+
+function run(name, fn) {
+  try {
+    fn();
+    console.log(`PASS ${name}`);
+  } catch (err) {
+    failures++;
+    console.error(`FAIL ${name}: ${err.message}`);
+  }
+}
+
+for (const { number, title, body, expected } of cases) {
+  const text = `${title}
+
+${body}`;
+  run(`#${number}`, () => {
+    assert.deepStrictEqual(inferComponentLabels(text, keywords), expected);
+  });
+}
+
+run('#3144 cliKeywordPrefixSubstringRegression', () => {
+  const text = `${cliRegressionCase.title}
+
+${cliRegressionCase.body}`;
+  const inferred = inferComponentLabels(text, keywords);
+  assert.ok(!inferred.includes('cli'), `expected 'cli' absent (body contains 'Mem0 client', a substring of the removed 'mem0 cli' term), got ${JSON.stringify(inferred)}`);
+});
+
+run('noKeywordMatchReturnsEmptyArray', () => {
+  const text = 'The weather today is sunny and I went for a walk in the park with my dog.';
+  assert.deepStrictEqual(inferComponentLabels(text, keywords), []);
+});
+
+run('emptyStringReturnsEmptyArray', () => {
+  assert.deepStrictEqual(inferComponentLabels('', keywords), []);
+});
+
+if (failures > 0) {
+  console.error(`
+${failures} test(s) failed.`);
+  process.exit(1);
+}
+console.log(`
+All ${cases.length + 3} tests passed.`);

.github/workflows/ci-gate.yml

@@ -38,8 +38,11 @@ jobs:
       cli_python: ${{ steps.filter.outputs.cli_python }}
       cli_node: ${{ steps.filter.outputs.cli_node }}
       openclaw: ${{ steps.filter.outputs.openclaw }}
+      mem0_plugin: ${{ steps.filter.outputs.mem0_plugin }}
       opencode_plugin: ${{ steps.filter.outputs.opencode_plugin }}
       pi_agent_plugin: ${{ steps.filter.outputs.pi_agent_plugin }}
+      n8n_nodes_mem0: ${{ steps.filter.outputs.n8n_nodes_mem0 }}
+      zapier_mem0: ${{ steps.filter.outputs.zapier_mem0 }}
       docs_llms_txt: ${{ steps.filter.outputs.docs_llms_txt }}
     steps:
       - uses: dorny/paths-filter@v3
@@ -71,6 +74,11 @@ jobs:
               - 'integrations/openclaw/**'
               - '.github/workflows/openclaw-checks.yml'
               - '.github/workflows/ci-gate.yml'
+            mem0_plugin:
+              - 'integrations/mem0-plugin/**'
+              - '!integrations/mem0-plugin/.opencode-plugin/**'
+              - '.github/workflows/mem0-plugin-checks.yml'
+              - '.github/workflows/ci-gate.yml'
             opencode_plugin:
               - 'integrations/mem0-plugin/.opencode-plugin/**'
               - '.github/workflows/opencode-plugin-checks.yml'
@@ -79,6 +87,13 @@ jobs:
               - 'integrations/pi-agent-plugin/**'
               - '.github/workflows/pi-agent-plugin-checks.yml'
               - '.github/workflows/ci-gate.yml'
+            n8n_nodes_mem0:
+              - 'integrations/n8n-nodes-mem0/**'
+              - '.github/workflows/n8n-nodes-mem0-checks.yml'
+            zapier_mem0:
+              - 'integrations/zapier-mem0/**'
+              - '.github/workflows/zapier-mem0-checks.yml'
+              - '.github/workflows/ci-gate.yml'
             docs_llms_txt:
               - 'docs/**/*.mdx'
               - 'docs/llms.txt'
@@ -122,6 +137,13 @@ jobs:
     uses: ./.github/workflows/openclaw-checks.yml
     secrets: inherit
 
+  mem0-plugin:
+    name: Mem0 Plugin
+    needs: changes
+    if: needs.changes.outputs.mem0_plugin == 'true'
+    uses: ./.github/workflows/mem0-plugin-checks.yml
+    secrets: inherit
+
   opencode-plugin:
     name: OpenCode Plugin
     needs: changes
@@ -136,6 +158,18 @@ jobs:
     uses: ./.github/workflows/pi-agent-plugin-checks.yml
     secrets: inherit
 
+  n8n-nodes-mem0:
+    name: n8n Node
+    needs: changes
+    if: needs.changes.outputs.n8n_nodes_mem0 == 'true'
+    uses: ./.github/workflows/n8n-nodes-mem0-checks.yml
+  zapier-mem0:
+    name: Zapier App
+    needs: changes
+    if: needs.changes.outputs.zapier_mem0 == 'true'
+    uses: ./.github/workflows/zapier-mem0-checks.yml
+    secrets: inherit
+
   docs-llms-txt:
     name: docs llms.txt
     needs: changes
@@ -152,8 +186,11 @@ jobs:
       - cli-python
       - cli-node
       - openclaw
+      - mem0-plugin
       - opencode-plugin
       - pi-agent-plugin
+      - n8n-nodes-mem0
+      - zapier-mem0
       - docs-llms-txt
     if: always()
     runs-on: ubuntu-latest

.github/workflows/ci.yml

@@ -106,7 +106,7 @@ jobs:
         run: |
           pip install --upgrade pip
           pip install -e ".[test,graph,vector_stores,llms,extras]"
-          pip install ruff
+          pip install ruff==0.16.0
       - name: Run Linting
         if: needs.check_changes.outputs.mem0_changed == 'true'
         run: make lint

.github/workflows/issue-labeler.yml

@@ -12,28 +12,56 @@ jobs:
   label:
     runs-on: ubuntu-latest
     steps:
+      - uses: actions/checkout@v4
+
       - uses: stefanbuck/github-issue-parser@v3
         id: issue-parser
+        continue-on-error: true
         with:
           template-path: .github/ISSUE_TEMPLATE/bug_report.yml
 
       - uses: redhat-plumbers-in-action/advanced-issue-labeler@v3
+        continue-on-error: true
         with:
           issue-form: ${{ steps.issue-parser.outputs.jsonString }}
-          section: component
           token: ${{ secrets.GITHUB_TOKEN }}
           config-path: .github/advanced-issue-labeler.yml
 
-      - uses: stefanbuck/github-issue-parser@v3
-        id: feature-parser
-        if: contains(github.event.issue.labels.*.name, 'enhancement')
+      - name: Infer component from text when the form was not used
+        uses: actions/github-script@v7
         with:
-          template-path: .github/ISSUE_TEMPLATE/feature_request.yml
+          script: |
+            const {
+              componentLabels,
+              inferComponentLabels,
+              loadKeywords,
+            } = require(`${process.env.GITHUB_WORKSPACE}/.github/scripts/infer-component-labels.js`);
 
-      - uses: redhat-plumbers-in-action/advanced-issue-labeler@v3
-        if: contains(github.event.issue.labels.*.name, 'enhancement')
-        with:
-          issue-form: ${{ steps.feature-parser.outputs.jsonString }}
-          section: component
-          token: ${{ secrets.GITHUB_TOKEN }}
-          config-path: .github/advanced-issue-labeler.yml
+            const { data: issue } = await github.rest.issues.get({
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              issue_number: context.issue.number,
+            });
+
+            const keywords = loadKeywords(`${process.env.GITHUB_WORKSPACE}/.github/component-keywords.json`);
+            const known = componentLabels(keywords);
+            const existing = issue.labels.map((label) => label.name || label);
+            if (existing.some((name) => known.includes(name))) {
+              core.info(`Component label already present: ${existing.join(', ')}`);
+              return;
+            }
+
+            const labels = inferComponentLabels(`${issue.title}\n\n${issue.body || ''}`, keywords);
+
+            if (labels.length === 0) {
+              core.info('No component could be inferred from the issue text');
+              return;
+            }
+
+            core.info(`Inferred: ${labels.join(', ')}`);
+            await github.rest.issues.addLabels({
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              issue_number: context.issue.number,
+              labels,
+            });

.github/workflows/mem0-plugin-checks.yml

@@ -0,0 +1,58 @@
+name: Mem0 Plugin Checks
+
+# On PRs this is invoked by ci-gate.yml (the single required check);
+# push-to-main and manual runs remain standalone.
+#
+# Covers the Python plugin (scripts/ + tests/). The nested .opencode-plugin/
+# is a separate package with its own workflow (opencode-plugin-checks.yml).
+on:
+  workflow_dispatch:
+  push:
+    branches: [main]
+    paths:
+      - 'integrations/mem0-plugin/**'
+      - '!integrations/mem0-plugin/.opencode-plugin/**'
+      - '.github/workflows/mem0-plugin-checks.yml'
+  workflow_call:
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ["3.10", "3.11", "3.12"]
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Install dependencies
+        working-directory: integrations/mem0-plugin
+        run: |
+          pip install -r requirements.txt
+          pip install pytest
+
+      - name: Verify hook entry points are executable
+        working-directory: integrations/mem0-plugin
+        run: |
+          missing=$(find scripts -name '*.sh' ! -name '_*' ! -perm -u+x -print)
+          if [ -n "$missing" ]; then
+            echo "Hook entry points must be executable:"
+            echo "$missing"
+            exit 1
+          fi
+
+      - name: Check hook manifests are valid JSON
+        working-directory: integrations/mem0-plugin
+        run: |
+          for f in plugin.json mcp_config.json hooks.json hooks/*.json; do
+            jq empty "$f" || (echo "Invalid JSON: $f" && exit 1)
+          done
+
+      - name: Run tests
+        working-directory: integrations/mem0-plugin
+        run: pytest -q

.github/workflows/n8n-nodes-mem0-cd.yml

@@ -0,0 +1,60 @@
+name: Publish n8n-nodes-mem0 📦 to npm
+
+# Dispatched by release.yml (Release Router) when a release tagged
+# n8n-nodes-mem0-v* is published. Can also be dispatched manually to
+# re-publish a tag.
+on:
+  workflow_dispatch:
+    inputs:
+      tag:
+        description: 'Release tag to build and publish (e.g. n8n-nodes-mem0-v0.1.0)'
+        required: true
+        type: string
+      prerelease:
+        description: 'Publish under the version preid dist-tag instead of latest'
+        required: false
+        type: boolean
+        default: false
+
+jobs:
+  build-n-publish:
+    name: Build and publish n8n-nodes-mem0 📦 to npm
+    if: startsWith(inputs.tag, 'n8n-nodes-mem0-v')
+    runs-on: ubuntu-latest
+    permissions:
+      id-token: write
+    defaults:
+      run:
+        working-directory: integrations/n8n-nodes-mem0
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          ref: ${{ inputs.tag }}
+
+      - name: Install pnpm
+        uses: pnpm/action-setup@v4
+        with:
+          version: 9
+
+      - name: Set up Node.js
+        uses: actions/setup-node@v4
+        with:
+          node-version: '20'
+          registry-url: 'https://registry.npmjs.org'
+          cache: 'pnpm'
+          cache-dependency-path: integrations/n8n-nodes-mem0/pnpm-lock.yaml
+
+      - name: Install dependencies
+        run: pnpm install --frozen-lockfile --ignore-scripts
+
+      - name: Build
+        run: pnpm run build
+
+      - name: Publish to npm
+        run: |
+          if [ "${{ inputs.prerelease }}" = "true" ]; then
+            PREID=$(node -p "require('./package.json').version.split('-')[1].split('.')[0]")
+            npx npm@latest publish --provenance --access public --tag "$PREID"
+          else
+            npx npm@latest publish --provenance --access public
+          fi

.github/workflows/n8n-nodes-mem0-checks.yml

@@ -0,0 +1,88 @@
+name: n8n-nodes-mem0 checks
+
+# On PRs this is invoked by ci-gate.yml (the single required check);
+# push-to-main and manual runs remain standalone.
+on:
+  workflow_dispatch:
+  push:
+    branches: [main]
+    paths:
+      - 'integrations/n8n-nodes-mem0/**'
+      - '.github/workflows/n8n-nodes-mem0-checks.yml'
+  workflow_call:
+
+jobs:
+  lint:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Install pnpm
+        uses: pnpm/action-setup@v4
+        with:
+          version: 9
+
+      - name: Setup Node.js
+        uses: actions/setup-node@v4
+        with:
+          node-version: 20
+          cache: 'pnpm'
+          cache-dependency-path: integrations/n8n-nodes-mem0/pnpm-lock.yaml
+
+      - name: Install dependencies
+        run: cd integrations/n8n-nodes-mem0 && pnpm install --frozen-lockfile --ignore-scripts
+
+      - name: Lint
+        run: cd integrations/n8n-nodes-mem0 && pnpm run lint
+
+  test:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Install pnpm
+        uses: pnpm/action-setup@v4
+        with:
+          version: 9
+
+      - name: Setup Node.js
+        uses: actions/setup-node@v4
+        with:
+          node-version: 20
+          cache: 'pnpm'
+          cache-dependency-path: integrations/n8n-nodes-mem0/pnpm-lock.yaml
+
+      - name: Install dependencies
+        run: cd integrations/n8n-nodes-mem0 && pnpm install --frozen-lockfile --ignore-scripts
+
+      - name: Run tests
+        run: cd integrations/n8n-nodes-mem0 && pnpm test
+
+  build:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Install pnpm
+        uses: pnpm/action-setup@v4
+        with:
+          version: 9
+
+      - name: Setup Node.js
+        uses: actions/setup-node@v4
+        with:
+          node-version: 20
+          cache: 'pnpm'
+          cache-dependency-path: integrations/n8n-nodes-mem0/pnpm-lock.yaml
+
+      - name: Install dependencies
+        run: cd integrations/n8n-nodes-mem0 && pnpm install --frozen-lockfile --ignore-scripts
+
+      - name: Build
+        run: cd integrations/n8n-nodes-mem0 && pnpm run build
+
+      - name: Verify dist output exists
+        run: |
+          test -f integrations/n8n-nodes-mem0/dist/nodes/Mem0/Mem0.node.js || (echo "Build output missing: dist/nodes/Mem0/Mem0.node.js" && exit 1)
+          test -f integrations/n8n-nodes-mem0/dist/credentials/Mem0Api.credentials.js || (echo "Build output missing: dist/credentials/Mem0Api.credentials.js" && exit 1)
+          test -f integrations/n8n-nodes-mem0/dist/nodes/Mem0/mem0.svg || (echo "Build output missing: dist/nodes/Mem0/mem0.svg" && exit 1)

.github/workflows/pr-labeler.yml

@@ -0,0 +1,64 @@
+name: PR Labeler
+
+on:
+  pull_request_target:
+    types: [opened, synchronize, reopened, edited]
+
+concurrency:
+  group: pr-labeler-${{ github.event.pull_request.number }}
+  cancel-in-progress: true
+
+permissions:
+  contents: read
+  pull-requests: write
+  issues: read
+
+jobs:
+  label:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/labeler@v5
+        with:
+          repo-token: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Propagate labels from linked issues
+        uses: actions/github-script@v7
+        with:
+          script: |
+            const allowed = new Set([
+              'sdk-python', 'sdk-typescript', 'vector-store', 'plugin',
+              'rest-api', 'documentation', 'ci', 'cli', 'integrations',
+            ]);
+            const umbrella = { plugin: 'integrations' };
+            const { repository } = await github.graphql(
+              `query ($owner: String!, $repo: String!, $number: Int!) {
+                repository(owner: $owner, name: $repo) {
+                  pullRequest(number: $number) {
+                    closingIssuesReferences(first: 20) {
+                      nodes { labels(first: 50) { nodes { name } } }
+                    }
+                  }
+                }
+              }`,
+              { owner: context.repo.owner, repo: context.repo.repo, number: context.issue.number },
+            );
+
+            const labels = new Set();
+            for (const issue of repository.pullRequest.closingIssuesReferences.nodes) {
+              for (const label of issue.labels.nodes) {
+                if (allowed.has(label.name)) labels.add(label.name);
+              }
+            }
+
+            for (const label of [...labels]) {
+              if (umbrella[label]) labels.add(umbrella[label]);
+            }
+
+            if (labels.size > 0) {
+              await github.rest.issues.addLabels({
+                owner: context.repo.owner,
+                repo: context.repo.repo,
+                issue_number: context.issue.number,
+                labels: [...labels],
+              });
+            }

.github/workflows/release.yml

@@ -45,6 +45,7 @@ jobs:
             openclaw-v*)  workflow="openclaw-cd.yml" ;;
             opencode-v*)  workflow="opencode-plugin-cd.yml" ;;
             pi-agent-v*)  workflow="pi-agent-plugin-cd.yml" ;;
+            n8n-nodes-mem0-v*) workflow="n8n-nodes-mem0-cd.yml" ;;
             v*)           workflow="cd.yml" ;;
             *)
               echo "::error::Release tag '$TAG' does not match any known package prefix — nothing will be published. See the tag prefix table in AGENTS.md."

.github/workflows/zapier-mem0-cd.yml

@@ -0,0 +1,42 @@
+name: Deploy zapier-mem0 to Zapier
+
+# Zapier apps deploy to Zapier's own platform (not npm), so this is NOT wired
+# into the npm release router (release.yml). It is manual workflow_dispatch
+# only and requires the ZAPIER_DEPLOY_KEY repo secret.
+#
+#   gh workflow run zapier-mem0-cd.yml --ref main
+on:
+  workflow_dispatch:
+
+jobs:
+  push:
+    name: Push zapier-mem0 to Zapier
+    runs-on: ubuntu-latest
+    defaults:
+      run:
+        working-directory: integrations/zapier-mem0
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Install pnpm
+        uses: pnpm/action-setup@v4
+        with:
+          version: 9
+
+      - name: Set up Node.js
+        uses: actions/setup-node@v4
+        with:
+          node-version: 22
+          cache: 'pnpm'
+          cache-dependency-path: integrations/zapier-mem0/pnpm-lock.yaml
+
+      - name: Install dependencies
+        run: pnpm install --frozen-lockfile
+
+      - name: Build TypeScript
+        run: pnpm build
+
+      - name: Push to Zapier
+        env:
+          ZAPIER_DEPLOY_KEY: ${{ secrets.ZAPIER_DEPLOY_KEY }}
+        run: npx zapier-platform-cli@19 push

.github/workflows/zapier-mem0-checks.yml

@@ -0,0 +1,47 @@
+name: zapier-mem0 checks
+
+# On PRs this is invoked by ci-gate.yml (the single required check);
+# push-to-main and manual runs remain standalone.
+#
+# CI compiles the TypeScript app, runs `zapier validate` (offline schema + style
+# checks) against the build, plus the offline jest unit suite (test/unit.test.ts —
+# mocked z.request, no network). The end-to-end jest suite is skipped here because
+# it hits the live Mem0 API — it runs locally with MEM0_API_KEY set (see README).
+on:
+  workflow_dispatch:
+  push:
+    branches: [main]
+    paths:
+      - 'integrations/zapier-mem0/**'
+      - '.github/workflows/zapier-mem0-checks.yml'
+  workflow_call:
+
+jobs:
+  validate:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Install pnpm
+        uses: pnpm/action-setup@v4
+        with:
+          version: 9
+
+      - name: Setup Node.js
+        uses: actions/setup-node@v4
+        with:
+          node-version: 22
+          cache: 'pnpm'
+          cache-dependency-path: integrations/zapier-mem0/pnpm-lock.yaml
+
+      - name: Install dependencies
+        run: cd integrations/zapier-mem0 && pnpm install --frozen-lockfile
+
+      - name: Build TypeScript
+        run: cd integrations/zapier-mem0 && pnpm build
+
+      - name: Validate Zapier app definition
+        run: cd integrations/zapier-mem0 && npx zapier-platform-cli@19 validate
+
+      - name: Run offline unit tests
+        run: cd integrations/zapier-mem0 && pnpm test:unit

AGENTS.md

@@ -27,8 +27,9 @@ This is a **polyglot monorepo** containing Python and TypeScript packages, CLIs,
 | `integrations/openclaw/` | `@mem0/openclaw-mem0` — OpenClaw plugin for Claude Code / AI editors |
 | `integrations/pi-agent-plugin/` | `@mem0/pi-agent-plugin` — Pi Agent plugin |
 | `integrations/vercel-ai-sdk/` | `@mem0/vercel-ai-provider` — Vercel AI SDK memory provider |
+| `integrations/n8n-nodes-mem0/` | `@mem0/n8n-nodes-mem0` — n8n community node; add / search / get / update / delete memories |
+| `integrations/zapier-mem0/` | `@mem0/zapier` — Zapier Platform CLI app (deploys to Zapier, not npm); add / search / get / delete memories |
 | `server/` | FastAPI REST server for self-hosted Mem0 (Docker: FastAPI + PostgreSQL/pgvector + Neo4j) |
-| `openmemory/` | Self-hosted memory platform — `api/` (FastAPI + Alembic + MCP server) and `ui/` (Next.js 15 + React 19) |
 | `skills/` | Claude Code skill definitions. Reference skills (SDK knowledge, always-on): `mem0/`, `mem0-cli/`, `mem0-vercel-ai-sdk/`. Pipeline skills (run on demand): `mem0-integrate/`, `mem0-test-integration/`, `mem0-oss-to-platform/` |
 | `docs/` | Documentation site (Mintlify) |
 | `tests/` | Python SDK tests (pytest) |
@@ -62,7 +63,7 @@ integrations/openclaw/ ──▶ mem0ai (npm)
 - **Node.js**: v18+ (v20 or v22 recommended)
 - **pnpm**: v10+ (`npm install -g pnpm@10`) — used for all TypeScript packages
 - **Hatch**: Python build/environment tool (`pip install hatch`)
-- **Docker**: Required for `server/` and `openmemory/` development
+- **Docker**: Required for `server/` development
 
 ### Initial Setup
 
@@ -214,28 +215,6 @@ docker-compose up                  # starts all 3 services
 - **Services:** PostgreSQL with pgvector, Neo4j 5.x with APOC plugin
 - **Hot reload:** Dev Dockerfile mounts `server/` and `mem0/` for live changes
 
-### OpenMemory (`openmemory/`)
-
-```bash
-# Full stack via Docker Compose
-cd openmemory
-docker-compose up
-# Qdrant: localhost:6333
-# API (MCP): localhost:8765
-# UI: localhost:3000
-
-# Individual development
-cd openmemory/api && uvicorn main:app --reload       # FastAPI backend
-cd openmemory/ui && npm run dev                       # Next.js frontend
-
-# Tests
-cd openmemory/api && pytest tests/                   # API tests (e.g., test_mcp_server.py)
-```
-
-- **API:** FastAPI + Alembic (DB migrations) + MCP server (Model Context Protocol)
-- **UI:** Next.js 15, React 19, Radix UI, Redux Toolkit, TailwindCSS, Recharts
-- **Vector store:** Qdrant
-
 ### Documentation (`docs/`)
 
 ```bash
@@ -331,7 +310,6 @@ python -m benchmarks.beam.run --project-name my-test --backend cloud --mem0-api-
   - Root SDK: line length **120**
   - Python CLI: line length **100** with extended rule set (UP, B, SIM, RUF)
 - **isort** with `profile = "black"` for import sorting.
-- Ruff excludes `openmemory/` from root config.
 
 ### TypeScript Conventions
 
@@ -382,7 +360,6 @@ Optional layer on top of vector memory for relationship-aware retrieval. Configu
 Model Context Protocol support in multiple places:
 
 - **Remote:** MCP server at `mcp.mem0.ai`
-- **Local:** MCP server in `openmemory/api/` (FastAPI-based)
 - **Plugin:** MCP tools in `integrations/mem0-plugin/` — 9 tools: `add_memory`, `search_memories`, `get_memories`, `get_memory`, `update_memory`, `delete_memory`, `delete_all_memories`, `delete_entities`, `list_entities`
 
 ### Plugin & Skills System
@@ -429,8 +406,11 @@ PR testing is orchestrated by a single entry point: **`ci-gate.yml` (CI Gate)**
 | Python CLI | `cli-python-ci.yml` | Push to main (on `cli/python/`), manual | Ruff lint + pytest + hatch build on Python 3.10, 3.11, 3.12 |
 | Node CLI | `cli-node-ci.yml` | Push to main (on `cli/node/`), manual | Biome lint + tsc + vitest + tsup build on Node 20, 22 |
 | OpenClaw | `openclaw-checks.yml` | Push to main (on `integrations/openclaw/`), manual | tsc + vitest (with Codecov) + tsup build on Node 20, 22 |
+| Mem0 Plugin | `mem0-plugin-checks.yml` | Push to main (on `integrations/mem0-plugin/`, excluding `.opencode-plugin/`), manual | pytest + hook entry-point exec bits + JSON manifest validation on Python 3.10, 3.11, 3.12 |
 | OpenCode Plugin | `opencode-plugin-checks.yml` | Push to main (on `integrations/mem0-plugin/.opencode-plugin/`), manual | Bun: tsc type-check + build + dist artifact check |
 | Pi Agent Plugin | `pi-agent-plugin-checks.yml` | Push to main (on `integrations/pi-agent-plugin/`), manual | tsc + vitest + tsup build (dist artifact check) on Node 20, 22 |
+| n8n Node | `n8n-nodes-mem0-checks.yml` | Push to main (on `integrations/n8n-nodes-mem0/`), manual | ESLint (n8n-nodes-base) + tsc build (dist artifact check) on Node 20 |
+| Zapier App | `zapier-mem0-checks.yml` | Push to main (on `integrations/zapier-mem0/`), manual | build (tsc) + `zapier validate` + offline unit tests on Node 22 |
 | docs llms.txt | `docs-llms-txt-check.yml` | Manual | `docs/llms.txt` coverage check |
 
 When adding a new package CI workflow: give it `workflow_call` (plus `push`/`workflow_dispatch` as needed, but no `pull_request` trigger), then register it in `ci-gate.yml` — a path filter under the `changes` job, a call job, and an entry in the gate job's `needs` list.
@@ -450,11 +430,13 @@ Publishing is routed through a single entry point: **`release.yml` (Release Rout
 | OpenClaw | `openclaw-cd.yml` | `openclaw-v*` | npm (`@mem0/openclaw-mem0`) |
 | OpenCode Plugin | `opencode-plugin-cd.yml` | `opencode-v*` | npm (`@mem0/opencode-plugin`) |
 | Pi Agent Plugin | `pi-agent-plugin-cd.yml` | `pi-agent-v*` | npm (`@mem0/pi-agent-plugin`) |
+| n8n Node | `n8n-nodes-mem0-cd.yml` | `n8n-nodes-mem0-v*` | npm (`@mem0/n8n-nodes-mem0`) |
 
 - Package CD workflows are `workflow_dispatch`-only (inputs: `tag`, `prerelease`); they check out and build the given tag. Registry trusted-publisher settings stay pinned to each package's own workflow filename.
 - All publishing uses **OIDC trusted publishing** — no tokens or secrets required.
 - First publish of a new npm package must be done manually; OIDC works for subsequent versions.
 - To re-publish a release (e.g. after a registry settings fix), do **not** delete/recreate the GitHub release — manually dispatch the package workflow instead: `gh workflow run <package>-cd.yml --ref refs/tags/<tag> -f tag=<tag>`.
+- The **Zapier app** (`integrations/zapier-mem0`) deploys to Zapier's own platform, not npm, so it is **not** in the release router. Deploy it manually: `gh workflow run zapier-mem0-cd.yml --ref main` (requires the `ZAPIER_DEPLOY_KEY` secret).
 - When adding a new package: add its CD workflow (`workflow_dispatch` with `tag`/`prerelease` inputs), then register its tag prefix in the `case` block in `release.yml`. Keep the bare `v*` arm last.
 
 ### Utility Workflows
@@ -462,6 +444,7 @@ Publishing is routed through a single entry point: **`release.yml` (Release Rout
 | Workflow | File | Purpose |
 |----------|------|---------|
 | Issue Labeler | `issue-labeler.yml` | Automatic issue labeling |
+| PR Labeler | `pr-labeler.yml` | Path-based PR labeling plus propagating labels from linked issues |
 | Stale Bot | `stale.yml` | Marks stale issues and PRs |
 | llms.txt Check | `docs-llms-txt-check.yml` | Blocks PRs touching `docs/**/*.mdx` when `docs/llms.txt` is out of sync. Fix locally with `python scripts/check-llms-txt-coverage.py --write`. |
 
@@ -584,7 +567,7 @@ N/A
 
 - Follow existing code patterns — don't introduce new frameworks or abstractions without discussion.
 - Version bumps go in `pyproject.toml` (Python) or `package.json` (TypeScript).
-- For `server/` and `openmemory/` work, use Docker Compose for local development.
+- For `server/` work, use Docker Compose for local development.
 - Do NOT use `pip` or `conda` for dependency management — use `hatch` (see `docs/contributing/development.mdx`).
 
 ### Contributing Guides
@@ -607,5 +590,4 @@ N/A
 - Use npm or yarn in TypeScript packages — this repo uses pnpm exclusively.
 - Use `require()` for imports in TypeScript — use ES module `import` syntax.
 - Mix up linter configs: root Python SDK uses line-length 120, Python CLI uses 100, Node CLI uses Biome (not ESLint/Ruff).
-- Modify `openmemory/` database migrations without understanding the Alembic migration chain.
 - Change public APIs without updating documentation in `docs/`.

CONTRIBUTING.md

@@ -1,72 +1,157 @@
-# Contributing to mem0
+# Contributing to Mem0
 
-Let us make contribution easy, collaborative and fun.
+First off, thank you for taking the time to contribute! 🎉 Mem0 is a
+community-driven project and we welcome contributions of all kinds — bug fixes,
+new features, documentation, examples, and integrations.
 
-## Submit your Contribution through PR
+Mem0 is a polyglot monorepo, and this guide covers contributing to both the
+**Python SDK** and the **TypeScript SDK** (and the rest of the repository).
 
-To make a contribution, follow these steps:
+## Before You Start
 
-1. Fork and clone this repository
-2. Do the changes on your fork with dedicated feature branch `feature/f1`
-3. If you modified the code (new feature or bug-fix), please add tests for it
-4. Include proper documentation / docstring and examples to run the feature
-5. Ensure that all tests pass
-6. Submit a pull request
+### 1. Open an Issue First
 
-For more details about pull requests, please read [GitHub's guides](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/creating-a-pull-request).
+**Always open an issue before opening a pull request.** This lets us discuss the
+change, avoid duplicate effort, and agree on the approach before you invest time
+in code.
 
+- Search [existing issues](https://github.com/mem0ai/mem0/issues) first to see if
+  your bug or idea already exists.
+- If it doesn't, open a
+  [bug report](https://github.com/mem0ai/mem0/issues/new?template=bug_report.yml) or
+  [feature request](https://github.com/mem0ai/mem0/issues/new?template=feature_request.yml).
+- For anything beyond a trivial fix, wait for a maintainer to confirm the approach
+  before starting significant work.
 
-### 📦 Development Environment
+Every pull request must link to an issue using `Closes #<issue-number>`.
 
-We use `hatch` for managing development environments. To set up:
+### 2. Sign the Contributor License Agreement (CLA)
+
+**We cannot accept or merge any pull request until you have signed our Contributor
+License Agreement (CLA).**
+
+When you open your first PR, the CLA bot will automatically comment with a link to
+sign. Signing takes less than a minute and only needs to be done once. Pull
+requests from contributors who have not signed the CLA will be blocked from
+merging.
+
+## Repository Layout
+
+The two most common contribution targets are the SDKs:
+
+| Package               | Path       | Language     | Package manager |
+| --------------------- | ---------- | ------------ | --------------- |
+| Python SDK (`mem0ai`) | `mem0/`    | Python 3.9+  | `hatch`         |
+| TypeScript SDK (`mem0ai`) | `mem0-ts/` | TypeScript | `pnpm`        |
+
+Other packages include the CLIs (`cli/python/`, `cli/node/`), integrations
+(`integrations/`), the self-hosted `server/`, and the docs site
+(`docs/`). See [AGENTS.md](./AGENTS.md) for a full map of the repository.
+
+## Development Workflow
+
+1. **Fork** the repository and **clone** your fork.
+2. Create a **feature branch** from `main` (e.g. `feature/my-new-feature` or
+   `fix/issue-1234`).
+3. Make your changes — add **tests**, **documentation**, and **examples** as
+   appropriate.
+4. Run **linting and tests** for every package you touched (see below).
+5. Commit using [Conventional Commits](https://www.conventionalcommits.org/)
+   (e.g. `feat:`, `fix:`, `docs:`, `refactor:`, `test:`).
+6. Push and open a **pull request** against `main`, linking the issue with
+   `Closes #<number>` and filling out the
+   [PR template](./.github/PULL_REQUEST_TEMPLATE.md).
+
+### Contributing to the Python SDK (`mem0/`)
+
+We use [`hatch`](https://hatch.pypa.io/latest/install/) to manage environments.
+**Do not use `pip` or `conda` for dependency management.**
 
 ```bash
-# Activate environment for specific Python version:
-hatch shell dev_py_3_9   # Python 3.9
-hatch shell dev_py_3_10  # Python 3.10  
-hatch shell dev_py_3_11  # Python 3.11
-hatch shell dev_py_3_12  # Python 3.12
+# Activate a dev environment (3.9 / 3.10 / 3.11 / 3.12)
+hatch shell dev_py_3_11
 
-# The environment will automatically install all dev dependencies
-# Run tests within the activated shell:
-make test
-```
-
-### 📌 Pre-commit
-
-To ensure our standards, make sure to install pre-commit before starting to contribute.
-
-```bash
+# Install pre-commit hooks (runs ruff + isort on commit)
 pre-commit install
+
+# Lint, format, and sort imports
+make lint
+make format
+make sort
+
+# Run the test suite (run `make install_all` first if deps are missing)
+make test
 ```
 
-### 🧪 Testing
+- **Linter / formatter:** Ruff (line length **120**)
+- **Import sorting:** isort (`profile = "black"`)
+- **Tests:** pytest (in `tests/`)
 
-We use `pytest` to test our code across multiple Python versions. You can run tests using:
+See the full [Development guide](https://docs.mem0.ai/contributing/development) for
+environment details.
+
+### Contributing to the TypeScript SDK (`mem0-ts/`)
+
+We use [`pnpm`](https://pnpm.io/) (v10+) for all TypeScript packages. **Do not use
+`npm` or `yarn`.**
 
 ```bash
-# Run tests with default Python version
-make test
+cd mem0-ts
+pnpm install
 
-# Test specific Python versions:
-make test-py-3.9   # Python 3.9 environment
-make test-py-3.10  # Python 3.10 environment
-make test-py-3.11  # Python 3.11 environment
-make test-py-3.12  # Python 3.12 environment
-
-# When using hatch shells, run tests with:
-make test  # After activating a shell with hatch shell test_XX
+pnpm run build        # tsup (CJS + ESM)
+pnpm run test         # jest (all tests)
+pnpm run test:unit    # unit tests with coverage
 ```
 
-Make sure that all tests pass across all supported Python versions before submitting a pull request.
+- **Build:** tsup
+- **Formatter:** Prettier
+- **Tests:** jest
+- Always run type checking after changes: `pnpm run typecheck` (or `tsc --noEmit`).
+- Use ES module `import` syntax — never `require()`.
 
-We look forward to your pull requests and can't wait to see your contributions!
+## Good Contribution Practices
 
-### 🚀 Releasing
+- **Keep PRs small and focused.** One logical change per PR is easier to review and
+  merge.
+- **Follow existing patterns.** Match the style, structure, and conventions of the
+  code around you. Don't introduce new frameworks or abstractions without
+  discussion.
+- **Write tests** that would fail without your change — regression tests for bugs,
+  coverage for new features.
+- **Update documentation** in `docs/` for any user-facing change. New `.mdx` pages
+  must be added to `docs/llms.txt` (run
+  `python scripts/check-llms-txt-coverage.py --write` to scaffold entries).
+- **Add examples** when introducing new user-facing behavior.
+- **Run linters and tests locally** before pushing — CI re-runs them on every PR
+  via the CI Gate.
+- **Never commit secrets** — no `.env` files, API keys, or credentials.
+- **Don't add core dependencies lightly.** New Python dependencies belong in an
+  optional group in `pyproject.toml`, not the core `dependencies` list.
+- **Be responsive** to review feedback and keep your branch up to date with `main`.
 
-All packages are published automatically via GitHub Actions when a GitHub Release is created with the correct tag prefix.
+## Pull Request Checklist
 
-#### Tag Prefixes
+Before requesting review, make sure:
+
+- [ ] An issue exists and is linked with `Closes #<number>`
+- [ ] You have signed the CLA
+- [ ] Your code follows the project's style guidelines (lint passes)
+- [ ] You performed a self-review of your changes
+- [ ] Tests are added/updated and pass locally
+- [ ] Documentation is updated if needed
+
+## Reporting Security Issues
+
+**Do not report security vulnerabilities through public issues or pull requests.**
+Please follow our [Security Policy](./SECURITY.md) to report them privately.
+
+## Releasing
+
+All packages are published automatically via GitHub Actions when a GitHub Release
+is created with the correct tag prefix.
+
+### Tag Prefixes
 
 | Package | Registry | Tag Prefix | Example |
 |---------|----------|------------|---------|
@@ -77,15 +162,17 @@ All packages are published automatically via GitHub Actions when a GitHub Releas
 | `@mem0/vercel-ai-provider` | npm | `vercel-ai-v*` | `vercel-ai-v2.0.6` |
 | `@mem0/openclaw-mem0` | npm | `openclaw-v*` | `openclaw-v1.0.1` |
 
-#### How to Release
+### How to Release
 
 1. Bump the version in `pyproject.toml` (Python) or `package.json` (Node)
 2. Create a [GitHub Release](https://github.com/mem0ai/mem0/releases/new) with the matching tag prefix
 3. The correct workflow will trigger automatically — verify in the [Actions tab](https://github.com/mem0ai/mem0/actions)
 
-#### Publishing Details
+### Publishing Details
 
 - **PyPI packages** use OIDC trusted publishing via `pypa/gh-action-pypi-publish`
 - **npm packages** use OIDC trusted publishing via npm CLI (>= 11.5.1) — no tokens or secrets required
 - All workflows require `permissions: id-token: write` for OIDC authentication
 - First publish of a new npm package must be done manually; OIDC works for subsequent versions
+
+We look forward to your pull requests and can't wait to see your contributions!

Makefile

@@ -11,7 +11,7 @@ install:
 	hatch env create
 
 install_all:
-	pip install ruff==0.6.9 groq together boto3 litellm ollama chromadb weaviate weaviate-client sentence_transformers vertexai \
+	pip install ruff==0.16.0 groq together boto3 litellm ollama chromadb weaviate weaviate-client sentence_transformers vertexai \
 	            google-generativeai elasticsearch opensearch-py vecs "pinecone<7.0.0" pinecone-text faiss-cpu langchain-community \
 							upstash-vector azure-search-documents langchain-memgraph langchain-neo4j langchain-aws rank-bm25 pymochow pymongo psycopg kuzu databricks-sdk valkey
 

README.md

@@ -46,12 +46,12 @@
 
 | Benchmark | Old | New  | Tokens  | Latency p50  |
 | --- | --- | --- | --- | --- |
-| **LoCoMo** | 71.4 | **91.6** | 7.0K  | 0.88s  |
-| **LongMemEval** | 67.8 | **94.8** | 6.8K  | 1.09s  |
+| **LoCoMo** | 71.4 | **92.5** | 7.0K  | 0.88s  |
+| **LongMemEval** | 67.8 | **94.4** | 6.8K  | 1.09s  |
 | **BEAM (1M)** | — | **64.1** | 6.7K  | 1.00s  |
 | **BEAM (10M)** | — | **48.6** | 6.9K  | 1.05s  |
 
-All benchmarks run on the same production-representative model stack. Single-pass retrieval (one call, no agentic loops).
+All benchmarks run on the same production-representative model stack. Single-pass retrieval (one call, no agentic loops) at a top_200 retrieval budget. Scores reflect Mem0's managed platform, which includes proprietary optimizations not available in the open-source SDK; open-source users should expect directionally similar gains but not identical numbers.
 
 **What changed:**
 - **Single-pass ADD-only extraction** -- one LLM call, no UPDATE/DELETE. Memories accumulate; nothing is overwritten.
@@ -63,8 +63,8 @@ All benchmarks run on the same production-representative model stack. Single-pas
 See the [migration guide](https://docs.mem0.ai/migration/oss-v2-to-v3) for upgrade instructions. The [evaluation framework](https://github.com/mem0ai/memory-benchmarks) is open-sourced so anyone can reproduce the numbers.
 
 ## Research Highlights
-- **91.6 on LoCoMo** -- +20 points over the previous algorithm
-- **94.8 on LongMemEval** -- +27 points, with +53.6 on assistant memory recall
+- **92.5 on LoCoMo** -- +21 points over the previous algorithm
+- **94.4 on LongMemEval** -- +27 points, with 98.2 on assistant memory recall
 - **64.1 on BEAM (1M)** -- production-scale memory evaluation at 1M tokens
 - [Read the full paper](https://mem0.ai/research)
 

SECURITY.md

@@ -0,0 +1,48 @@
+# Security Policy
+
+We take the security of Mem0 and our community seriously. Thank you for helping
+keep Mem0 and its users safe by disclosing vulnerabilities responsibly.
+
+## Reporting a Vulnerability
+
+Please **do not** report security vulnerabilities through public GitHub issues,
+pull requests, or discussions.
+
+If you believe you have found a security vulnerability in Mem0, please report it
+privately through one of the following channels:
+
+1. **GitHub Private Vulnerability Reporting** — open a
+   [private security advisory](https://github.com/mem0ai/mem0/security/advisories/new)
+   directly on this repository.
+2. **Email** the maintainers at **support@mem0.ai** with the subject line:
+
+   `SECURITY: Mem0 vulnerability report`
+
+To help us triage and resolve the issue quickly, please include as much of the
+following as you can:
+
+- Affected component or package (e.g. Python SDK, TypeScript SDK, server, CLI)
+- Affected version, tag, or commit
+- Clear, step-by-step reproduction instructions
+- The security impact and a proof of concept, if available
+- Any suggested fix or mitigation
+
+## Response Process
+
+- We will acknowledge receipt of your report within **72 hours**.
+- We will work with you privately to confirm the issue and assess its impact.
+- Once a fix or mitigation is ready, we will coordinate a disclosure timeline
+  with you and credit you for the discovery, unless you prefer to remain anonymous.
+
+## Public Disclosure
+
+Please avoid sharing technical details of the vulnerability publicly until the
+maintainers have reviewed the issue and a fix or mitigation has been released. We
+are committed to resolving valid reports promptly and keeping you informed
+throughout the process.
+
+## Supported Versions
+
+We release security fixes against the latest published version of each package.
+Whenever possible, please reproduce the issue on the most recent release before
+reporting.

cli/README.md

@@ -60,9 +60,8 @@ mem0 delete <memory-id>
 | `mem0 entity` | List or delete entities (users, agents, apps, runs) |
 | `mem0 event` | Inspect background processing events (bulk deletes, large add jobs) |
 | `mem0 status` | Verify API connection and display current project |
-| `mem0 version` | Print the CLI version |
 
-Run `mem0 <command> --help` for detailed usage on any command.
+Run `mem0 <command> --help` for detailed usage on any command, or `mem0 --version` to print the CLI version.
 
 ## Agent mode
 

cli/cli-spec.json

@@ -207,7 +207,11 @@
         { "name": "immutable", "flags": ["--immutable"], "type": "boolean", "default": false, "help": "Prevent future updates." },
         { "name": "no_infer", "flags": ["--no-infer"], "type": "boolean", "default": false, "help": "Skip inference, store raw." },
         { "name": "expires", "flags": ["--expires"], "type": "string", "help": "Expiration date (YYYY-MM-DD)." },
-        { "name": "categories", "flags": ["--categories"], "type": "string", "help": "Categories (JSON array or comma-separated)." },
+        { "name": "categories", "flags": ["--categories"], "type": "string", "help": "Not supported on add, use --custom-categories instead." },
+        { "name": "custom_instructions", "flags": ["--custom-instructions"], "type": "string", "help": "Custom instructions for fact extraction." },
+        { "name": "custom_categories", "flags": ["--custom-categories"], "type": "string", "help": "Custom categories as a JSON array of {name: description} objects." },
+        { "name": "structured_data_schema", "flags": ["--structured-data-schema"], "type": "string", "help": "Schema for structured data extraction, as JSON." },
+        { "name": "timestamp", "flags": ["--timestamp"], "type": "integer", "help": "Unix timestamp for the memory." },
         { "name": "graph", "flags": ["--graph"], "type": "boolean", "default": false, "help": "Enable graph memory extraction.", "panel": "Scope" },
         { "name": "no_graph", "flags": ["--no-graph"], "type": "boolean", "default": false, "help": "Disable graph memory extraction.", "panel": "Scope" },
         { "name": "output", "flags": ["--output", "-o"], "type": "string", "default": "text", "help": "Output format: text, json, quiet.", "panel": "Output" }
@@ -244,6 +248,9 @@
         { "name": "keyword", "flags": ["--keyword"], "type": "boolean", "default": false, "help": "Use keyword search.", "panel": "Search" },
         { "name": "filter_json", "flags": ["--filter"], "type": "string", "help": "Advanced filter expression (JSON).", "panel": "Search" },
         { "name": "fields", "flags": ["--fields"], "type": "string", "help": "Specific fields to return (comma-separated).", "panel": "Search" },
+        { "name": "show_expired", "flags": ["--show-expired"], "type": "boolean", "default": false, "help": "Include expired memories.", "panel": "Search" },
+        { "name": "reference_date", "flags": ["--reference-date"], "type": "string", "help": "Reference date for relative queries (YYYY-MM-DD or unix timestamp).", "panel": "Search" },
+        { "name": "latest_only", "flags": ["--latest-only"], "type": "boolean", "default": false, "help": "Only return the latest version of each memory.", "panel": "Search" },
         { "name": "graph", "flags": ["--graph"], "type": "boolean", "default": false, "help": "Enable graph in search.", "panel": "Search" },
         { "name": "no_graph", "flags": ["--no-graph"], "type": "boolean", "default": false, "help": "Disable graph in search.", "panel": "Search" },
         { "name": "output", "flags": ["--output", "-o"], "type": "string", "default": "text", "help": "Output: text, json, table.", "panel": "Output" }
@@ -296,6 +303,8 @@
         { "name": "category", "flags": ["--category"], "type": "string", "help": "Filter by category.", "panel": "Filters" },
         { "name": "after", "flags": ["--after"], "type": "string", "help": "Created after (YYYY-MM-DD).", "panel": "Filters" },
         { "name": "before", "flags": ["--before"], "type": "string", "help": "Created before (YYYY-MM-DD).", "panel": "Filters" },
+        { "name": "show_expired", "flags": ["--show-expired"], "type": "boolean", "default": false, "help": "Include expired memories.", "panel": "Filters" },
+        { "name": "latest_only", "flags": ["--latest-only"], "type": "boolean", "default": false, "help": "Only return the latest version of each memory.", "panel": "Filters" },
         { "name": "graph", "flags": ["--graph"], "type": "boolean", "default": false, "help": "Enable graph in listing.", "panel": "Filters" },
         { "name": "no_graph", "flags": ["--no-graph"], "type": "boolean", "default": false, "help": "Disable graph in listing.", "panel": "Filters" },
         { "name": "output", "flags": ["--output", "-o"], "type": "string", "default": "table", "help": "Output: text, json, table.", "panel": "Output" }
@@ -329,6 +338,8 @@
       ],
       "options": [
         { "name": "metadata", "flags": ["--metadata", "-m"], "type": "string", "help": "Update metadata (JSON)." },
+        { "name": "expires", "flags": ["--expires"], "type": "string", "help": "Expiration date (YYYY-MM-DD)." },
+        { "name": "timestamp", "flags": ["--timestamp"], "type": "integer", "help": "Unix timestamp for the memory." },
         { "name": "output", "flags": ["--output", "-o"], "type": "string", "default": "text", "help": "Output: text, json, quiet.", "panel": "Output" }
       ],
       "apiEndpoint": "update"
@@ -356,6 +367,7 @@
         { "name": "all", "flags": ["--all"], "type": "boolean", "default": false, "help": "Delete all memories matching scope filters." },
         { "name": "entity", "flags": ["--entity"], "type": "boolean", "default": false, "help": "Delete the entity itself and all its memories (cascade)." },
         { "name": "project", "flags": ["--project"], "type": "boolean", "default": false, "help": "With --all: delete ALL memories project-wide." },
+        { "name": "delete_linked", "flags": ["--delete-linked"], "type": "boolean", "default": false, "help": "Also delete memories linked to this memory." },
         { "name": "dry_run", "flags": ["--dry-run"], "type": "boolean", "default": false, "help": "Show what would be deleted without deleting." },
         { "name": "force", "flags": ["--force"], "type": "boolean", "default": false, "help": "Skip confirmation." },
         { "name": "user_id", "flags": ["--user-id", "-u"], "type": "string", "help": "Scope to user.", "panel": "Scope" },

cli/node/CHANGELOG.md

@@ -1,60 +0,0 @@
-# Changelog
-
-All notable changes to `@mem0/cli` are documented here.
-
-The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
-and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
-
-## [0.2.9] — 2026-06-19
-
-### Security
-
-- Telemetry no longer passes the Mem0 API key to its child process via
-  command-line arguments. The context is now sent over stdin, so the key is no
-  longer visible in the process list (`ps`, `/proc/<pid>/cmdline`, Activity
-  Monitor). Fixes #4862.
-
-## [0.2.8] — 2026-06-01
-
-### Security
-
-- Pinned transitive dependencies via pnpm overrides to remediate high-severity CVEs:
-  - `jws` → 4.0.1 (CVE-2025-65945)
-  - `langsmith` → ^0.6.0 (CVE-2026-45134)
-  - `tar-fs` → ^2.1.4 (CVE-2025-48387, CVE-2025-59343)
-  - `picomatch` → ^2.3.2 (CVE-2026-33671)
-  - `minimatch` → ^3.1.3 / ^5.1.8 / ^9.0.7 (CVE-2026-27903, CVE-2026-27904, CVE-2026-26996)
-  - `path-to-regexp` → ^8.4.0 (CVE-2026-4926)
-  - `rollup` → ^4.59.0 (CVE-2026-27606)
-  - `glob` → ^10.5.0 (CVE-2025-64756)
-  - `@modelcontextprotocol/sdk` → ^1.25.4 (CVE-2025-66414, CVE-2026-0621)
-
-## [0.2.7] — 2026-05-20
-
-### Added
-
-- `mem0 whoami` — print the active agent's `default_user_id` (the AGENTRUSH
-  leaderboard identifier). Reads from local config, no network call.
-- `mem0 agent-rush <add | search>` — subcommand group that wraps the new
-  `/v1/agent-rush/` platform endpoints for the 7-day AGENTRUSH game. Project
-  routing is implicit (resolved server-side); no flags exposed. Pretty-prints
-  platform error codes into actionable hints (e.g. `agentrush_search_first`
-  → "Run 3 'mem0 agent-rush search' commands before adding.").
-- PII safety prompt on first `mem0 agent-rush add`. Interactive runs require
-  explicit `y` to acknowledge that AGENTRUSH memories are public; the
-  acknowledgement is persisted in `~/.mem0/config.json` under
-  `agent_rush.acknowledged_at` so the prompt only appears once per machine.
-  Non-interactive (agent) invocations surface the warning to stderr without
-  blocking.
-- New config schema field: `agent_rush.acknowledged_at` (ISO timestamp,
-  empty until first interactive acknowledgement).
-
-### Changed
-
-- HTTP requests from the new agent-rush commands send `X-Mem0-Mode: agent-rush`
-  in addition to the existing source headers, so platform telemetry can split
-  game traffic from regular CLI usage.
-
-## [0.2.6] and earlier
-
-Unlogged historical releases. See git history under `cli/node/`.

cli/node/README.md

@@ -232,14 +232,6 @@ Verify your API connection and display the current project.
 mem0 status
 ```
 
-### `mem0 version`
-
-Print the CLI version.
-
-```bash
-mem0 version
-```
-
 ## Agent mode
 
 Pass `--agent` (or its alias `--json`) as a **global flag** on any command to get output designed for AI agent tool loops:
@@ -298,6 +290,8 @@ These flags are available on all commands:
 | `--base-url` | Override the configured API base URL for this request |
 | `-o, --output` | Set the output format |
 
+`mem0 --version` prints the CLI version. It is only valid before a subcommand, not after one.
+
 ## Environment variables
 
 | Variable | Description |

cli/node/development.md

@@ -51,7 +51,7 @@ pnpm link --global
 
 # Now use it like a normal CLI
 mem0 --help
-mem0 version
+mem0 --version
 ```
 
 > **Warning:** If you also have the Python CLI installed, both register the `mem0` command. The last one linked/installed wins. Unlink with `pnpm unlink --global`.

cli/node/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@mem0/cli",
-  "version": "0.2.9",
+  "version": "0.2.12",
   "description": "The official CLI for mem0 — the memory layer for AI agents",
   "type": "module",
   "bin": {
@@ -51,8 +51,8 @@
       "langsmith@<0.6.0": "^0.6.0",
       "tar-fs@>=2.0.0 <2.1.4": "^2.1.4",
       "picomatch@<2.3.2": "^2.3.2",
-      "postcss@<8.5.10": ">=8.5.10",
-      "esbuild": ">=0.28.1"
+      "esbuild": ">=0.28.1",
+      "postcss@<8.5.18": ">=8.5.18 <9.0.0"
     }
   }
 }

cli/node/pnpm-lock.yaml

@@ -9,8 +9,8 @@ overrides:
   langsmith@<0.6.0: ^0.6.0
   tar-fs@>=2.0.0 <2.1.4: ^2.1.4
   picomatch@<2.3.2: ^2.3.2
-  postcss@<8.5.10: '>=8.5.10'
   esbuild: '>=0.28.1'
+  postcss@<8.5.18: '>=8.5.18 <9.0.0'
 
 importers:
 
@@ -40,7 +40,7 @@ importers:
         version: 20.19.37
       tsup:
         specifier: ^8.0.0
-        version: 8.5.1(postcss@8.5.15)(tsx@4.21.0)(typescript@5.9.3)
+        version: 8.5.1(postcss@8.5.23)(tsx@4.21.0)(typescript@5.9.3)
       tsx:
         specifier: ^4.7.0
         version: 4.21.0
@@ -78,24 +78,28 @@ packages:
     engines: {node: '>=14.21.3'}
     cpu: [arm64]
     os: [linux]
+    libc: [musl]
 
   '@biomejs/cli-linux-arm64@1.9.4':
     resolution: {integrity: sha512-fJIW0+LYujdjUgJJuwesP4EjIBl/N/TcOX3IvIHJQNsAqvV2CHIogsmA94BPG6jZATS4Hi+xv4SkBBQSt1N4/g==}
     engines: {node: '>=14.21.3'}
     cpu: [arm64]
     os: [linux]
+    libc: [glibc]
 
   '@biomejs/cli-linux-x64-musl@1.9.4':
     resolution: {integrity: sha512-gEhi/jSBhZ2m6wjV530Yy8+fNqG8PAinM3oV7CyO+6c3CEh16Eizm21uHVsyVBEB6RIM8JHIl6AGYCv6Q6Q9Tg==}
     engines: {node: '>=14.21.3'}
     cpu: [x64]
     os: [linux]
+    libc: [musl]
 
   '@biomejs/cli-linux-x64@1.9.4':
     resolution: {integrity: sha512-lRCJv/Vi3Vlwmbd6K+oQ0KhLHMAysN8lXoCI7XeHlxaajk06u7G+UsFSO01NAs5iYuWKmVZjmiOzJ0OJmGsMwg==}
     engines: {node: '>=14.21.3'}
     cpu: [x64]
     os: [linux]
+    libc: [glibc]
 
   '@biomejs/cli-win32-arm64@1.9.4':
     resolution: {integrity: sha512-tlbhLk+WXZmgwoIKwHIHEBZUwxml7bRJgk0X2sPyNR3S93cdRq6XulAZRQJ17FYGGzWne0fgrXBKpl7l4M87Hg==}
@@ -316,66 +320,79 @@ packages:
     resolution: {integrity: sha512-RzeBwv0B3qtVBWtcuABtSuCzToo2IEAIQrcyB/b2zMvBWVbjo8bZDjACUpnaafaxhTw2W+imQbP2BD1usasK4g==}
     cpu: [arm]
     os: [linux]
+    libc: [glibc]
 
   '@rollup/rollup-linux-arm-musleabihf@4.60.0':
     resolution: {integrity: sha512-Sf7zusNI2CIU1HLzuu9Tc5YGAHEZs5Lu7N1ssJG4Tkw6e0MEsN7NdjUDDfGNHy2IU+ENyWT+L2obgWiguWibWQ==}
     cpu: [arm]
     os: [linux]
+    libc: [musl]
 
   '@rollup/rollup-linux-arm64-gnu@4.60.0':
     resolution: {integrity: sha512-DX2x7CMcrJzsE91q7/O02IJQ5/aLkVtYFryqCjduJhUfGKG6yJV8hxaw8pZa93lLEpPTP/ohdN4wFz7yp/ry9A==}
     cpu: [arm64]
     os: [linux]
+    libc: [glibc]
 
   '@rollup/rollup-linux-arm64-musl@4.60.0':
     resolution: {integrity: sha512-09EL+yFVbJZlhcQfShpswwRZ0Rg+z/CsSELFCnPt3iK+iqwGsI4zht3secj5vLEs957QvFFXnzAT0FFPIxSrkQ==}
     cpu: [arm64]
     os: [linux]
+    libc: [musl]
 
   '@rollup/rollup-linux-loong64-gnu@4.60.0':
     resolution: {integrity: sha512-i9IcCMPr3EXm8EQg5jnja0Zyc1iFxJjZWlb4wr7U2Wx/GrddOuEafxRdMPRYVaXjgbhvqalp6np07hN1w9kAKw==}
     cpu: [loong64]
     os: [linux]
+    libc: [glibc]
 
   '@rollup/rollup-linux-loong64-musl@4.60.0':
     resolution: {integrity: sha512-DGzdJK9kyJ+B78MCkWeGnpXJ91tK/iKA6HwHxF4TAlPIY7GXEvMe8hBFRgdrR9Ly4qebR/7gfUs9y2IoaVEyog==}
     cpu: [loong64]
     os: [linux]
+    libc: [musl]
 
   '@rollup/rollup-linux-ppc64-gnu@4.60.0':
     resolution: {integrity: sha512-RwpnLsqC8qbS8z1H1AxBA1H6qknR4YpPR9w2XX0vo2Sz10miu57PkNcnHVaZkbqyw/kUWfKMI73jhmfi9BRMUQ==}
     cpu: [ppc64]
     os: [linux]
+    libc: [glibc]
 
   '@rollup/rollup-linux-ppc64-musl@4.60.0':
     resolution: {integrity: sha512-Z8pPf54Ly3aqtdWC3G4rFigZgNvd+qJlOE52fmko3KST9SoGfAdSRCwyoyG05q1HrrAblLbk1/PSIV+80/pxLg==}
     cpu: [ppc64]
     os: [linux]
+    libc: [musl]
 
   '@rollup/rollup-linux-riscv64-gnu@4.60.0':
     resolution: {integrity: sha512-3a3qQustp3COCGvnP4SvrMHnPQ9d1vzCakQVRTliaz8cIp/wULGjiGpbcqrkv0WrHTEp8bQD/B3HBjzujVWLOA==}
     cpu: [riscv64]
     os: [linux]
+    libc: [glibc]
 
   '@rollup/rollup-linux-riscv64-musl@4.60.0':
     resolution: {integrity: sha512-pjZDsVH/1VsghMJ2/kAaxt6dL0psT6ZexQVrijczOf+PeP2BUqTHYejk3l6TlPRydggINOeNRhvpLa0AYpCWSQ==}
     cpu: [riscv64]
     os: [linux]
+    libc: [musl]
 
   '@rollup/rollup-linux-s390x-gnu@4.60.0':
     resolution: {integrity: sha512-3ObQs0BhvPgiUVZrN7gqCSvmFuMWvWvsjG5ayJ3Lraqv+2KhOsp+pUbigqbeWqueGIsnn+09HBw27rJ+gYK4VQ==}
     cpu: [s390x]
     os: [linux]
+    libc: [glibc]
 
   '@rollup/rollup-linux-x64-gnu@4.60.0':
     resolution: {integrity: sha512-EtylprDtQPdS5rXvAayrNDYoJhIz1/vzN2fEubo3yLE7tfAw+948dO0g4M0vkTVFhKojnF+n6C8bDNe+gDRdTg==}
     cpu: [x64]
     os: [linux]
+    libc: [glibc]
 
   '@rollup/rollup-linux-x64-musl@4.60.0':
     resolution: {integrity: sha512-k09oiRCi/bHU9UVFqD17r3eJR9bn03TyKraCrlz5ULFJGdJGi7VOmm9jl44vOJvRJ6P7WuBi/s2A97LxxHGIdw==}
     cpu: [x64]
     os: [linux]
+    libc: [musl]
 
   '@rollup/rollup-openbsd-x64@4.60.0':
     resolution: {integrity: sha512-1o/0/pIhozoSaDJoDcec+IVLbnRtQmHwPV730+AOD29lHEEo4F5BEUB24H0OBdhbBBDwIOSuf7vgg0Ywxdfiiw==}
@@ -653,8 +670,8 @@ packages:
   mz@2.7.0:
     resolution: {integrity: sha512-z81GNO7nnYMEhrGh9LeymoE4+Yr0Wn5McHIZMK5cfQCl+NDX08sCZgUc9/6MHni9IWuFLm1Z3HTCXu2z9fN62Q==}
 
-  nanoid@3.3.12:
-    resolution: {integrity: sha512-ZB9RH/39qpq5Vu6Y+NmUaFhQR6pp+M2Xt76XBnEwDaGcVAqhlvxrl3B2bKS5D3NH3QR76v3aSrKaF/Kiy7lEtQ==}
+  nanoid@3.3.16:
+    resolution: {integrity: sha512-bzlKTyNJ7+LdGIIwy8ijFpIqEQIvafahV7eYykJ8Cvh42EdJeODoJ6gUJXpQJvej1BddH8OqTXZNE/KfbWAu8Q==}
     engines: {node: ^10 || ^12 || ^13.7 || ^14 || >=15.0.1}
     hasBin: true
 
@@ -695,7 +712,7 @@ packages:
     engines: {node: '>= 18'}
     peerDependencies:
       jiti: '>=1.21.0'
-      postcss: '>=8.5.10'
+      postcss: '>=8.5.18 <9.0.0'
       tsx: ^4.8.1
       yaml: ^2.4.2
     peerDependenciesMeta:
@@ -708,8 +725,8 @@ packages:
       yaml:
         optional: true
 
-  postcss@8.5.15:
-    resolution: {integrity: sha512-FfR8sjd4em2T6fb3I2MwAJU7HWVMr9zba+enmQeeWFfCbm+UOC/0X4DS8XtpUTMwWMGbjKYP7xjfNekzyGmB3A==}
+  postcss@8.5.23:
+    resolution: {integrity: sha512-g50586zr4bZmwFiTlflMu8E0bDTb5I5gertgwAKmsdUlTQIhZtunzUlD1WSzwcVWPoAVpsrA6vlfCD7oXvRwgg==}
     engines: {node: ^10 || ^12 || >=14}
 
   readdirp@4.1.2:
@@ -821,7 +838,7 @@ packages:
     peerDependencies:
       '@microsoft/api-extractor': ^7.36.0
       '@swc/core': ^1
-      postcss: '>=8.5.10'
+      postcss: '>=8.5.18 <9.0.0'
       typescript: '>=4.5.0'
     peerDependenciesMeta:
       '@microsoft/api-extractor':
@@ -1388,7 +1405,7 @@ snapshots:
       object-assign: 4.1.1
       thenify-all: 1.6.0
 
-  nanoid@3.3.12: {}
+  nanoid@3.3.16: {}
 
   object-assign@4.1.1: {}
 
@@ -1424,16 +1441,16 @@ snapshots:
       mlly: 1.8.2
       pathe: 2.0.3
 
-  postcss-load-config@6.0.1(postcss@8.5.15)(tsx@4.21.0):
+  postcss-load-config@6.0.1(postcss@8.5.23)(tsx@4.21.0):
     dependencies:
       lilconfig: 3.1.3
     optionalDependencies:
-      postcss: 8.5.15
+      postcss: 8.5.23
       tsx: 4.21.0
 
-  postcss@8.5.15:
+  postcss@8.5.23:
     dependencies:
-      nanoid: 3.3.12
+      nanoid: 3.3.16
       picocolors: 1.1.1
       source-map-js: 1.2.1
 
@@ -1554,7 +1571,7 @@ snapshots:
 
   ts-interface-checker@0.1.13: {}
 
-  tsup@8.5.1(postcss@8.5.15)(tsx@4.21.0)(typescript@5.9.3):
+  tsup@8.5.1(postcss@8.5.23)(tsx@4.21.0)(typescript@5.9.3):
     dependencies:
       bundle-require: 5.1.0(esbuild@0.28.1)
       cac: 6.7.14
@@ -1565,7 +1582,7 @@ snapshots:
       fix-dts-default-cjs-exports: 1.0.1
       joycon: 3.1.1
       picocolors: 1.1.1
-      postcss-load-config: 6.0.1(postcss@8.5.15)(tsx@4.21.0)
+      postcss-load-config: 6.0.1(postcss@8.5.23)(tsx@4.21.0)
       resolve-from: 5.0.0
       rollup: 4.60.0
       source-map: 0.7.6
@@ -1574,7 +1591,7 @@ snapshots:
       tinyglobby: 0.2.15
       tree-kill: 1.2.2
     optionalDependencies:
-      postcss: 8.5.15
+      postcss: 8.5.23
       typescript: 5.9.3
     transitivePeerDependencies:
       - jiti
@@ -1602,7 +1619,7 @@ snapshots:
       esbuild: 0.28.1
       fdir: 6.5.0(picomatch@4.0.4)
       picomatch: 4.0.4
-      postcss: 8.5.15
+      postcss: 8.5.23
       rollup: 4.60.0
       tinyglobby: 0.2.15
     optionalDependencies:

cli/node/pnpm-workspace.yaml

@@ -10,5 +10,5 @@ overrides:
   langsmith@<0.6.0: ^0.6.0
   tar-fs@>=2.0.0 <2.1.4: ^2.1.4
   picomatch@<2.3.2: ^2.3.2
-  "postcss@<8.5.10": ">=8.5.10"
   "esbuild": ">=0.28.1"
+  "postcss@<8.5.18": ">=8.5.18 <9.0.0"

cli/node/src/backend/base.ts

@@ -14,7 +14,10 @@ export interface AddOptions {
 	immutable?: boolean;
 	infer?: boolean;
 	expires?: string;
-	categories?: string[];
+	customInstructions?: string;
+	customCategories?: Record<string, string>[];
+	structuredDataSchema?: Record<string, unknown>;
+	timestamp?: number;
 }
 
 export interface SearchOptions {
@@ -28,6 +31,9 @@ export interface SearchOptions {
 	keyword?: boolean;
 	filters?: Record<string, unknown>;
 	fields?: string[];
+	showExpired?: boolean;
+	referenceDate?: string | number;
+	latestOnly?: boolean;
 }
 
 export interface ListOptions {
@@ -40,6 +46,8 @@ export interface ListOptions {
 	category?: string;
 	after?: string;
 	before?: string;
+	showExpired?: boolean;
+	latestOnly?: boolean;
 }
 
 export interface DeleteOptions {
@@ -48,6 +56,12 @@ export interface DeleteOptions {
 	agentId?: string;
 	appId?: string;
 	runId?: string;
+	deleteLinked?: boolean;
+}
+
+export interface UpdateOptions {
+	expirationDate?: string;
+	timestamp?: number;
 }
 
 export interface EntityIds {
@@ -77,6 +91,7 @@ export interface Backend {
 		memoryId: string,
 		content?: string,
 		metadata?: Record<string, unknown>,
+		opts?: UpdateOptions,
 	): Promise<Record<string, unknown>>;
 
 	delete(

cli/node/src/backend/platform.ts

@@ -15,8 +15,13 @@ import {
 	type ListOptions,
 	NotFoundError,
 	type SearchOptions,
+	type UpdateOptions,
 } from "./base.js";
 
+function encodePathSegment(value: unknown): string {
+	return encodeURIComponent(String(value));
+}
+
 export class PlatformBackend implements Backend {
 	private baseUrl: string;
 	private headers: Record<string, string>;
@@ -146,7 +151,13 @@ export class PlatformBackend implements Backend {
 		if (opts.immutable) payload.immutable = true;
 		if (opts.infer === false) payload.infer = false;
 		if (opts.expires) payload.expiration_date = opts.expires;
-		if (opts.categories) payload.categories = opts.categories;
+		if (opts.customInstructions)
+			payload.custom_instructions = opts.customInstructions;
+		if (opts.customCategories)
+			payload.custom_categories = opts.customCategories;
+		if (opts.structuredDataSchema)
+			payload.structured_data_schema = opts.structuredDataSchema;
+		if (opts.timestamp !== undefined) payload.timestamp = opts.timestamp;
 		payload.source = "CLI";
 
 		return (await this._request("POST", "/v3/memories/add/", {
@@ -207,6 +218,10 @@ export class PlatformBackend implements Backend {
 		if (opts.rerank) payload.rerank = true;
 		if (opts.keyword) payload.keyword_search = true;
 		if (opts.fields) payload.fields = opts.fields;
+		if (opts.showExpired) payload.show_expired = true;
+		if (opts.referenceDate !== undefined)
+			payload.reference_date = opts.referenceDate;
+		if (opts.latestOnly) payload.latest_only = true;
 		payload.source = "CLI";
 
 		const result = (await this._request("POST", "/v3/memories/search/", {
@@ -218,9 +233,13 @@ export class PlatformBackend implements Backend {
 	}
 
 	async get(memoryId: string): Promise<Record<string, unknown>> {
-		return (await this._request("GET", `/v1/memories/${memoryId}/`, {
-			params: { source: "CLI" },
-		})) as Record<string, unknown>;
+		return (await this._request(
+			"GET",
+			`/v1/memories/${encodePathSegment(memoryId)}/`,
+			{
+				params: { source: "CLI" },
+			},
+		)) as Record<string, unknown>;
 	}
 
 	async listMemories(
@@ -257,6 +276,8 @@ export class PlatformBackend implements Backend {
 			extraFilters: Object.keys(extra).length > 0 ? extra : undefined,
 		});
 		if (apiFilters) payload.filters = apiFilters;
+		if (opts.showExpired) payload.show_expired = true;
+		if (opts.latestOnly) payload.latest_only = true;
 		payload.source = "CLI";
 
 		const result = (await this._request("POST", "/v3/memories/", {
@@ -272,14 +293,21 @@ export class PlatformBackend implements Backend {
 		memoryId: string,
 		content?: string,
 		metadata?: Record<string, unknown>,
+		opts: UpdateOptions = {},
 	): Promise<Record<string, unknown>> {
 		const payload: Record<string, unknown> = {};
 		if (content) payload.text = content;
 		if (metadata) payload.metadata = metadata;
+		if (opts.expirationDate) payload.expiration_date = opts.expirationDate;
+		if (opts.timestamp !== undefined) payload.timestamp = opts.timestamp;
 		payload.source = "CLI";
-		return (await this._request("PUT", `/v1/memories/${memoryId}/`, {
-			json: payload,
-		})) as Record<string, unknown>;
+		return (await this._request(
+			"PUT",
+			`/v1/memories/${encodePathSegment(memoryId)}/`,
+			{
+				json: payload,
+			},
+		)) as Record<string, unknown>;
 	}
 
 	async delete(
@@ -297,9 +325,13 @@ export class PlatformBackend implements Backend {
 			})) as Record<string, unknown>;
 		}
 		if (memoryId) {
-			return (await this._request("DELETE", `/v1/memories/${memoryId}/`, {
-				params: { source: "CLI" },
-			})) as Record<string, unknown>;
+			const params: Record<string, string> = { source: "CLI" };
+			if (opts.deleteLinked) params.delete_linked = "true";
+			return (await this._request(
+				"DELETE",
+				`/v1/memories/${encodePathSegment(memoryId)}/`,
+				{ params },
+			)) as Record<string, unknown>;
 		}
 		throw new Error("Either memoryId or --all is required");
 	}
@@ -316,16 +348,18 @@ export class PlatformBackend implements Backend {
 		if (entities.length === 0) {
 			throw new Error("At least one entity ID is required for deleteEntities.");
 		}
-		// Delete each provided entity via the v2 path-based endpoint
-		let result: Record<string, unknown> = {};
+		// Delete each provided entity via the v2 path-based endpoint. Key each
+		// response by entity type so a multi-entity delete (e.g. --user-id and
+		// --agent-id together) doesn't discard everything but the last result.
+		const results: Record<string, unknown> = {};
 		for (const [entityType, entityId] of entities) {
-			result = (await this._request(
+			results[entityType] = (await this._request(
 				"DELETE",
-				`/v2/entities/${entityType}/${entityId}/`,
+				`/v2/entities/${encodePathSegment(entityType)}/${encodePathSegment(entityId)}/`,
 				{ params: { source: "CLI" } },
 			)) as Record<string, unknown>;
 		}
-		return result;
+		return results;
 	}
 
 	async ping(): Promise<Record<string, unknown>> {
@@ -384,9 +418,9 @@ export class PlatformBackend implements Backend {
 	}
 
 	async getEvent(eventId: string): Promise<Record<string, unknown>> {
-		return (await this._request("GET", `/v1/event/${eventId}/`)) as Record<
-			string,
-			unknown
-		>;
+		return (await this._request(
+			"GET",
+			`/v1/event/${encodePathSegment(eventId)}/`,
+		)) as Record<string, unknown>;
 	}
 }

cli/node/src/commands/memory.ts

@@ -21,16 +21,19 @@ import {
 	formatSingleMemory,
 	printResultSummary,
 } from "../output.js";
-import { isAgentMode, setCurrentCommand } from "../state.js";
+import { isAgentMode, setCurrentCommand, stdinIsPiped } from "../state.js";
 
-/** True only when stdin is an actual pipe or file redirect — never in agent mode. */
-function _stdinIsPiped(): boolean {
-	if (isAgentMode()) return false;
-	try {
-		const stat = fs.fstatSync(0);
-		return stat.isFIFO() || stat.isFile();
-	} catch {
-		return false;
+/** Exit 1 if value is not a future YYYY-MM-DD date. */
+function _validateExpires(value: string): void {
+	if (!/^\d{4}-\d{2}-\d{2}$/.test(value)) {
+		printError(
+			"Invalid date format for --expires. Use YYYY-MM-DD (e.g. 2025-12-31).",
+		);
+		process.exit(1);
+	}
+	if (new Date(value) <= new Date()) {
+		printError("--expires date must be in the future.");
+		process.exit(1);
 	}
 }
 
@@ -49,10 +52,22 @@ export async function cmdAdd(
 		infer?: boolean;
 		expires?: string;
 		categories?: string;
+		customInstructions?: string;
+		customCategories?: string;
+		structuredDataSchema?: string;
+		timestamp?: number;
 		output: string;
 	},
 ): Promise<void> {
 	setCurrentCommand("add");
+
+	if (opts.categories) {
+		printError(
+			"--categories is not supported on add. Use --custom-categories instead.",
+		);
+		process.exit(1);
+	}
+
 	let msgs: Record<string, unknown>[] | undefined;
 	let content = text;
 
@@ -78,7 +93,7 @@ export async function cmdAdd(
 		}
 	}
 	// Read from stdin only if stdin is an actual pipe or file redirect
-	else if (!content && _stdinIsPiped()) {
+	else if (!content && stdinIsPiped()) {
 		content = fs.readFileSync(0, "utf-8").trim();
 	}
 
@@ -93,20 +108,6 @@ export async function cmdAdd(
 		process.exit(1);
 	}
 
-	// Validate --expires
-	if (opts.expires) {
-		if (!/^\d{4}-\d{2}-\d{2}$/.test(opts.expires)) {
-			printError(
-				"Invalid date format for --expires. Use YYYY-MM-DD (e.g. 2025-12-31).",
-			);
-			process.exit(1);
-		}
-		if (new Date(opts.expires) <= new Date()) {
-			printError("--expires date must be in the future.");
-			process.exit(1);
-		}
-	}
-
 	let meta: Record<string, unknown> | undefined;
 	if (opts.metadata) {
 		try {
@@ -117,15 +118,28 @@ export async function cmdAdd(
 		}
 	}
 
-	let cats: string[] | undefined;
-	if (opts.categories) {
+	let customCats: Record<string, string>[] | undefined;
+	if (opts.customCategories) {
 		try {
-			cats = JSON.parse(opts.categories);
+			customCats = JSON.parse(opts.customCategories);
 		} catch {
-			cats = opts.categories.split(",").map((c) => c.trim());
+			printError("Invalid JSON in --custom-categories.");
+			process.exit(1);
 		}
 	}
 
+	let schema: Record<string, unknown> | undefined;
+	if (opts.structuredDataSchema) {
+		try {
+			schema = JSON.parse(opts.structuredDataSchema);
+		} catch {
+			printError("Invalid JSON in --structured-data-schema.");
+			process.exit(1);
+		}
+	}
+
+	if (opts.expires) _validateExpires(opts.expires);
+
 	let result: Record<string, unknown>;
 	try {
 		result = await timedStatus("Adding memory...", async () => {
@@ -138,7 +152,10 @@ export async function cmdAdd(
 				immutable: opts.immutable,
 				infer: opts.infer !== false,
 				expires: opts.expires,
-				categories: cats,
+				customInstructions: opts.customInstructions,
+				customCategories: customCats,
+				structuredDataSchema: schema,
+				timestamp: opts.timestamp,
 			});
 		});
 	} catch (e) {
@@ -223,6 +240,9 @@ export async function cmdSearch(
 		keyword: boolean;
 		filterJson?: string;
 		fields?: string;
+		showExpired?: boolean;
+		referenceDate?: string;
+		latestOnly?: boolean;
 		output: string;
 	},
 ): Promise<void> {
@@ -271,6 +291,9 @@ export async function cmdSearch(
 				keyword: opts.keyword,
 				filters,
 				fields: fieldList,
+				showExpired: opts.showExpired,
+				referenceDate: opts.referenceDate,
+				latestOnly: opts.latestOnly,
 			});
 		});
 	} catch (e) {
@@ -364,6 +387,8 @@ export async function cmdList(
 		category?: string;
 		after?: string;
 		before?: string;
+		showExpired?: boolean;
+		latestOnly?: boolean;
 		output: string;
 	},
 ): Promise<void> {
@@ -391,6 +416,8 @@ export async function cmdList(
 				category: opts.category,
 				after: opts.after,
 				before: opts.before,
+				showExpired: opts.showExpired,
+				latestOnly: opts.latestOnly,
 			});
 		});
 	} catch (e) {
@@ -450,7 +477,12 @@ export async function cmdUpdate(
 	backend: Backend,
 	memoryId: string,
 	text: string | undefined,
-	opts: { metadata?: string; output: string },
+	opts: {
+		metadata?: string;
+		expires?: string;
+		timestamp?: number;
+		output: string;
+	},
 ): Promise<void> {
 	setCurrentCommand("update");
 	let meta: Record<string, unknown> | undefined;
@@ -463,11 +495,16 @@ export async function cmdUpdate(
 		}
 	}
 
+	if (opts.expires) _validateExpires(opts.expires);
+
 	const start = performance.now();
 	let result: Record<string, unknown>;
 	try {
 		result = await timedStatus("Updating memory...", async () => {
-			return backend.update(memoryId, text, meta);
+			return backend.update(memoryId, text, meta, {
+				expirationDate: opts.expires,
+				timestamp: opts.timestamp,
+			});
 		});
 	} catch (e) {
 		printError(e instanceof Error ? e.message : String(e));
@@ -493,7 +530,12 @@ export async function cmdUpdate(
 export async function cmdDelete(
 	backend: Backend,
 	memoryId: string,
-	opts: { output: string; dryRun?: boolean; force?: boolean },
+	opts: {
+		output: string;
+		dryRun?: boolean;
+		force?: boolean;
+		deleteLinked?: boolean;
+	},
 ): Promise<void> {
 	setCurrentCommand("delete");
 	if (opts.dryRun) {
@@ -514,7 +556,7 @@ export async function cmdDelete(
 	let result: Record<string, unknown>;
 	try {
 		result = await timedStatus("Deleting...", async () => {
-			return backend.delete(memoryId);
+			return backend.delete(memoryId, { deleteLinked: opts.deleteLinked });
 		});
 	} catch (e) {
 		printError(e instanceof Error ? e.message : String(e));

cli/node/src/commands/utils.ts

@@ -1,5 +1,5 @@
 /**
- * Utility commands: status, version, import.
+ * Utility commands: status, import.
  */
 
 import fs from "node:fs";
@@ -8,7 +8,6 @@ import type { Backend } from "../backend/base.js";
 import { colors, printError, printSuccess, timedStatus } from "../branding.js";
 import { formatAgentEnvelope, formatJsonEnvelope } from "../output.js";
 import { setCurrentCommand } from "../state.js";
-import { CLI_VERSION } from "../version.js";
 
 const { brand, dim, success, error: errorColor } = colors;
 
@@ -82,10 +81,6 @@ export async function cmdStatus(
 	console.log();
 }
 
-export function cmdVersion(): void {
-	console.log(`  ${brand("◆ Mem0")} CLI v${CLI_VERSION}`);
-}
-
 export async function cmdImport(
 	backend: Backend,
 	filePath: string,

cli/node/src/index.ts

@@ -17,6 +17,7 @@ import {
 	isAgentMode,
 	setAgentMode,
 	setCurrentCommand,
+	stdinIsPiped,
 	takeNotice,
 } from "./state.js";
 import { captureEvent } from "./telemetry.js";
@@ -319,7 +320,25 @@ program
 	.option("--immutable", "Prevent future updates.", false)
 	.option("--no-infer", "Skip inference, store raw.")
 	.option("--expires <date>", "Expiration date (YYYY-MM-DD).")
-	.option("--categories <value>", "Categories (JSON array or comma-separated).")
+	.option(
+		"--categories <value>",
+		"Not supported on add, use --custom-categories instead.",
+	)
+	.option(
+		"--custom-instructions <text>",
+		"Custom instructions for fact extraction.",
+	)
+	.option(
+		"--custom-categories <json>",
+		"Custom categories as a JSON array of {name: description} objects.",
+	)
+	.option(
+		"--structured-data-schema <json>",
+		"Schema for structured data extraction, as JSON.",
+	)
+	.option("--timestamp <unix>", "Unix timestamp for the memory.", (v) =>
+		Number.parseInt(v),
+	)
 	.option("-o, --output <format>", "Output format: text, json, quiet.", "text")
 	.option("--api-key <key>", "Override API key.")
 	.option("--base-url <url>", "Override API base URL.")
@@ -366,6 +385,16 @@ program
 	.option("--keyword", "Use keyword search.", false)
 	.option("--filter <json>", "Advanced filter expression (JSON).")
 	.option("--fields <list>", "Specific fields to return (comma-separated).")
+	.option("--show-expired", "Include expired memories.", false)
+	.option(
+		"--reference-date <date>",
+		"Reference date for relative queries (YYYY-MM-DD or unix timestamp).",
+	)
+	.option(
+		"--latest-only",
+		"Only return the latest version of each memory.",
+		false,
+	)
 	.option("-o, --output <format>", "Output: text, json, table.", "text")
 	.option("--api-key <key>", "Override API key.")
 	.option("--base-url <url>", "Override API base URL.")
@@ -375,7 +404,7 @@ program
 	)
 	.action(async (query, opts) => {
 		let resolvedQuery = query;
-		if (!resolvedQuery && !process.stdin.isTTY) {
+		if (!resolvedQuery && stdinIsPiped()) {
 			resolvedQuery = fs.readFileSync(0, "utf-8").trim();
 		}
 		if (!resolvedQuery) {
@@ -398,6 +427,9 @@ program
 			keyword: opts.keyword,
 			filterJson: opts.filter,
 			fields: opts.fields,
+			showExpired: opts.showExpired,
+			referenceDate: opts.referenceDate,
+			latestOnly: opts.latestOnly,
 			output,
 		});
 	});
@@ -441,6 +473,12 @@ program
 	.option("--category <name>", "Filter by category.")
 	.option("--after <date>", "Created after (YYYY-MM-DD).")
 	.option("--before <date>", "Created before (YYYY-MM-DD).")
+	.option("--show-expired", "Include expired memories.", false)
+	.option(
+		"--latest-only",
+		"Only return the latest version of each memory.",
+		false,
+	)
 	.option("-o, --output <format>", "Output: text, json, table.", "table")
 	.option("--api-key <key>", "Override API key.")
 	.option("--base-url <url>", "Override API base URL.")
@@ -464,6 +502,8 @@ program
 			category: opts.category,
 			after: opts.after,
 			before: opts.before,
+			showExpired: opts.showExpired,
+			latestOnly: opts.latestOnly,
 			output,
 		});
 	});
@@ -474,6 +514,10 @@ program
 	.command("update <memoryId> [text]")
 	.description("Update a memory's text or metadata.")
 	.option("-m, --metadata <json>", "Update metadata (JSON).")
+	.option("--expires <date>", "Expiration date (YYYY-MM-DD).")
+	.option("--timestamp <unix>", "Unix timestamp for the memory.", (v) =>
+		Number.parseInt(v),
+	)
 	.option("-o, --output <format>", "Output: text, json, quiet.", "text")
 	.option("--api-key <key>", "Override API key.")
 	.option("--base-url <url>", "Override API base URL.")
@@ -483,7 +527,7 @@ program
 	)
 	.action(async (memoryId, text, opts) => {
 		let resolvedText = text;
-		if (!resolvedText && !opts.metadata && !process.stdin.isTTY) {
+		if (!resolvedText && stdinIsPiped()) {
 			resolvedText = fs.readFileSync(0, "utf-8").trim();
 		}
 		const { cmdUpdate } = await import("./commands/memory.js");
@@ -492,6 +536,8 @@ program
 		const output = isAgent ? "agent" : opts.output;
 		await cmdUpdate(backend, memoryId, resolvedText, {
 			metadata: opts.metadata,
+			expires: opts.expires,
+			timestamp: opts.timestamp,
 			output,
 		});
 	});
@@ -510,6 +556,11 @@ program
 	.option("--project", "With --all: delete ALL memories project-wide.", false)
 	.option("--dry-run", "Show what would be deleted without deleting.", false)
 	.option("--force", "Skip confirmation.", false)
+	.option(
+		"--delete-linked",
+		"Also delete memories linked to this memory.",
+		false,
+	)
 	.option("-u, --user-id <id>", "Scope to user.")
 	.option("--agent-id <id>", "Scope to agent.")
 	.option("--app-id <id>", "Scope to app.")
@@ -563,6 +614,7 @@ program
 				output,
 				dryRun: opts.dryRun,
 				force: opts.force,
+				deleteLinked: opts.deleteLinked,
 			});
 			return;
 		}
@@ -806,8 +858,8 @@ program
 	.addHelpText("after", "\nExamples:\n  $ mem0 help\n  $ mem0 help --json")
 	.action((opts) => {
 		// opts.json is set when `mem0 help --json` is used (subcommand flag).
-		// program.opts().json is set when the root --json global flag was used first.
-		if (opts.json || program.opts().json) {
+		// program.opts().json/.agent is set when a root global flag was used first.
+		if (opts.json || program.opts().json || program.opts().agent) {
 			// Load spec from parent directory
 			const __dirname = path.dirname(fileURLToPath(import.meta.url));
 			const specPath = path.join(__dirname, "..", "..", "cli-spec.json");

cli/node/src/output.ts

@@ -282,11 +282,24 @@ export function sanitizeAgentData(command: string, data: unknown): unknown {
 		}
 		case "search":
 			return (data as Record<string, unknown>[]).map((r) =>
-				pick(r, ["id", "memory", "score", "created_at", "categories"]),
+				pick(r, [
+					"id",
+					"memory",
+					"score",
+					"created_at",
+					"categories",
+					"expiration_date",
+				]),
 			);
 		case "list":
 			return (data as Record<string, unknown>[]).map((r) =>
-				pick(r, ["id", "memory", "created_at", "categories"]),
+				pick(r, [
+					"id",
+					"memory",
+					"created_at",
+					"categories",
+					"expiration_date",
+				]),
 			);
 		case "get": {
 			const r = data as Record<string, unknown>;
@@ -297,11 +310,12 @@ export function sanitizeAgentData(command: string, data: unknown): unknown {
 				"updated_at",
 				"categories",
 				"metadata",
+				"expiration_date",
 			]);
 		}
 		case "update": {
 			const r = data as Record<string, unknown>;
-			return pick(r, ["id", "memory"]);
+			return pick(r, ["id", "memory", "expiration_date"]);
 		}
 		case "delete":
 		case "delete-all":

cli/node/src/state.ts

@@ -3,6 +3,8 @@
  * read by commands and branding functions.
  */
 
+import fs from "node:fs";
+
 let _agentMode = false;
 let _currentCommand = "";
 let _pendingNotice = "";
@@ -38,3 +40,14 @@ export function takeNotice(): string {
 	_pendingNotice = "";
 	return msg;
 }
+
+/** True only when stdin is an actual pipe or file redirect (never in agent mode). */
+export function stdinIsPiped(): boolean {
+	if (isAgentMode()) return false;
+	try {
+		const stat = fs.fstatSync(0);
+		return stat.isFIFO() || stat.isFile();
+	} catch {
+		return false;
+	}
+}

cli/node/tests/cli-integration.test.ts

@@ -44,15 +44,25 @@ describe("CLI Integration — help and version", () => {
     expect(result.stdout).toContain("search");
   });
 
-  it("help --json produces valid JSON", () => {
-    const result = run(["help", "--json"]);
-    expect(result.exitCode).toBe(0);
-    const parsed = JSON.parse(result.stdout);
-    // spec may have cli.name or top-level name
-    const name = parsed.name ?? parsed.cli?.name;
-    expect(name).toBe("mem0");
+  it("prints the version with --version, and has no version subcommand", () => {
+    const flag = run(["--version"]);
+    expect(flag.exitCode).toBe(0);
+    expect(flag.stdout).toContain("Mem0");
+    expect(run(["version"]).exitCode).not.toBe(0);
   });
 
+  it.each([["help", "--json"], ["--json", "help"], ["--agent", "help"]])(
+    "%s %s produces valid JSON",
+    (...args) => {
+      const result = run(args);
+      expect(result.exitCode).toBe(0);
+      const parsed = JSON.parse(result.stdout);
+      // spec may have cli.name or top-level name
+      const name = parsed.name ?? parsed.cli?.name;
+      expect(name).toBe("mem0");
+    },
+  );
+
   it("shows add help", () => {
     const result = run(["add", "--help"]);
     expect(result.exitCode).toBe(0);

cli/node/tests/option-parity.test.ts

@@ -0,0 +1,163 @@
+/**
+ * Drift test: every documented v3 add/search/list param must be reachable from the Node CLI.
+ */
+
+import { execSync } from "node:child_process";
+import fs from "node:fs";
+import path from "node:path";
+import { describe, expect, it } from "vitest";
+
+const OPENAPI_PATH = path.join(
+	__dirname,
+	"..",
+	"..",
+	"..",
+	"docs",
+	"openapi.json",
+);
+
+const KNOWN_UNSURFACED: Record<string, Record<string, string>> = {
+	"/v3/memories/add/": {
+		includes: "extraction hint, no CLI flag yet",
+		excludes: "extraction hint, no CLI flag yet",
+		enable_graph: "graph memory toggle, no CLI flag yet",
+		output_format: "response envelope is pinned by the CLI",
+		prompt_profile_id: "no CLI flag yet",
+		temporal_reasoning: "no CLI flag yet",
+		timezone: "no CLI flag yet",
+		observation_datetime: "no CLI flag yet, --timestamp backdates instead",
+		observation_date: "no CLI flag yet, --timestamp backdates instead",
+	},
+	"/v3/memories/search/": {
+		categories: "expressible through --filter",
+		metadata: "expressible through --filter",
+	},
+	"/v3/memories/": {
+		start_date: "covered by --after via filters.created_at.gte",
+		end_date: "covered by --before via filters.created_at.lte",
+		categories: "covered by --category via filters.categories",
+		fields: "no CLI flag yet",
+		keywords: "no CLI flag yet",
+	},
+};
+
+const ADD_MAPPING: Record<string, string[]> = {
+	messages: ["--messages", "--file", "text"],
+	user_id: ["--user-id"],
+	agent_id: ["--agent-id"],
+	app_id: ["--app-id"],
+	run_id: ["--run-id"],
+	metadata: ["--metadata"],
+	expiration_date: ["--expires"],
+	custom_instructions: ["--custom-instructions"],
+	custom_categories: ["--custom-categories"],
+	infer: ["--no-infer"],
+	immutable: ["--immutable"],
+	structured_data_schema: ["--structured-data-schema"],
+	timestamp: ["--timestamp"],
+};
+
+const SEARCH_MAPPING: Record<string, string[]> = {
+	query: ["query"],
+	filters: ["--filter", "--user-id", "--agent-id", "--run-id"],
+	show_expired: ["--show-expired"],
+	top_k: ["--top-k"],
+	threshold: ["--threshold"],
+	rerank: ["--rerank"],
+	reference_date: ["--reference-date"],
+	fields: ["--fields"],
+};
+
+const LIST_MAPPING: Record<string, string[]> = {
+	filters: [
+		"--user-id",
+		"--agent-id",
+		"--run-id",
+		"--category",
+		"--after",
+		"--before",
+	],
+	show_expired: ["--show-expired"],
+	page: ["--page"],
+	page_size: ["--page-size"],
+};
+
+function documentedFields(endpoint: string): string[] {
+	const spec = JSON.parse(fs.readFileSync(OPENAPI_PATH, "utf-8"));
+	const schema =
+		spec.paths[endpoint].post.requestBody.content["application/json"].schema;
+	return Object.keys(schema.properties);
+}
+
+function helpText(command: string): string {
+	return execSync(`npx tsx src/index.ts ${command} --help`, {
+		cwd: path.join(__dirname, ".."),
+		encoding: "utf-8",
+		timeout: 15000,
+	});
+}
+
+function assertAllReachable(
+	endpoint: string,
+	mapping: Record<string, string[]>,
+	command: string,
+) {
+	const documented = documentedFields(endpoint);
+	const help = helpText(command);
+	for (const field of documented) {
+		if (KNOWN_UNSURFACED[endpoint]?.[field]) continue;
+		const candidates = mapping[field];
+		expect(
+			candidates,
+			`${endpoint}: documented field "${field}" has no mapping entry for command "${command}"`,
+		).toBeDefined();
+		const reachable = candidates.some((flag) =>
+			flag.startsWith("--") ? help.includes(flag) : true,
+		);
+		expect(
+			reachable,
+			`${endpoint}: documented field "${field}" not reachable via any of ${JSON.stringify(candidates)} on command "${command}"`,
+		).toBe(true);
+	}
+}
+
+describe("Option parity: Node CLI reachability of documented v3 params", () => {
+	it("add covers documented fields", () => {
+		assertAllReachable("/v3/memories/add/", ADD_MAPPING, "add");
+	});
+
+	it("search covers documented fields", () => {
+		assertAllReachable("/v3/memories/search/", SEARCH_MAPPING, "search");
+	});
+
+	it("list covers documented fields", () => {
+		assertAllReachable("/v3/memories/", LIST_MAPPING, "list");
+	});
+});
+
+describe("stdin fallback uses the shared piped-stdin guard", () => {
+	const SOURCES = ["src/index.ts", "src/commands/memory.ts"];
+
+	for (const rel of SOURCES) {
+		it(`${rel} never checks process.stdin.isTTY directly`, () => {
+			const src = fs.readFileSync(path.join(__dirname, "..", rel), "utf-8");
+			expect(
+				src.includes("process.stdin.isTTY"),
+				`${rel}: use stdinIsPiped() from state.ts. A bare !isTTY check is also true for /dev/null and sockets, so readFileSync(0) crashes with EAGAIN in scripts, CI, and agent mode.`,
+			).toBe(false);
+		});
+
+		it(`${rel} guards every readFileSync(0) with stdinIsPiped()`, () => {
+			const src = fs.readFileSync(path.join(__dirname, "..", rel), "utf-8");
+			const lines = src.split("\n");
+			for (const [i, line] of lines.entries()) {
+				if (!line.includes("readFileSync(0")) continue;
+				const guard = lines.slice(Math.max(0, i - 3), i).join("\n");
+				expect(
+					guard.includes("stdinIsPiped()"),
+					`${rel}:${i + 1}: readFileSync(0) must be guarded by stdinIsPiped()`,
+				).toBe(true);
+			}
+		});
+	}
+});

cli/node/tests/platform-backend.test.ts

@@ -0,0 +1,237 @@
+/**
+ * Tests for the Platform backend (mem0 Platform API client).
+ */
+
+import { beforeEach, describe, expect, it, vi } from "vitest";
+import { PlatformBackend } from "../src/backend/platform.js";
+import { createDefaultConfig } from "../src/config.js";
+
+function makeBackend(): PlatformBackend {
+	return new PlatformBackend(createDefaultConfig().platform);
+}
+
+function mockFetch() {
+	const fetchMock = vi.fn().mockResolvedValue({
+		ok: true,
+		status: 200,
+		headers: { get: vi.fn().mockReturnValue(null) },
+		json: vi.fn().mockResolvedValue({ message: "ok" }),
+	});
+	vi.stubGlobal("fetch", fetchMock);
+	return fetchMock;
+}
+
+beforeEach(() => {
+	vi.restoreAllMocks();
+	vi.unstubAllGlobals();
+});
+
+describe("deleteEntities", () => {
+	it("returns all results keyed by entity type for a multi-entity delete", async () => {
+		const backend = makeBackend();
+		const responses: Record<string, unknown> = {
+			"/v2/entities/user/alice/": { message: "user deleted" },
+			"/v2/entities/agent/bob/": { message: "agent deleted" },
+		};
+		const spy = vi
+			// biome-ignore lint/suspicious/noExplicitAny: spying on a private method
+			.spyOn(backend as any, "_request")
+			.mockImplementation(
+				async (_method: string, path: string) => responses[path],
+			);
+
+		const result = await backend.deleteEntities({
+			userId: "alice",
+			agentId: "bob",
+		});
+
+		expect(result).toEqual({
+			user: { message: "user deleted" },
+			agent: { message: "agent deleted" },
+		});
+		expect(spy).toHaveBeenCalledTimes(2);
+	});
+
+	it("keys a single-entity delete by its type", async () => {
+		const backend = makeBackend();
+		// biome-ignore lint/suspicious/noExplicitAny: spying on a private method
+		vi.spyOn(backend as any, "_request").mockResolvedValue({
+			message: "user deleted",
+		});
+
+		const result = await backend.deleteEntities({ userId: "alice" });
+		expect(result).toEqual({ user: { message: "user deleted" } });
+	});
+
+	it("throws when no entity id is provided", async () => {
+		const backend = makeBackend();
+		await expect(backend.deleteEntities({})).rejects.toThrow(
+			"At least one entity ID is required",
+		);
+	});
+});
+
+describe("PlatformBackend option-parity payloads (MEM-5893)", () => {
+	it("add: custom_instructions, custom_categories, structured_data_schema, timestamp reach the payload alongside existing fields", async () => {
+		const backend = makeBackend();
+		const spy = vi
+			// biome-ignore lint/suspicious/noExplicitAny: spying on a private method
+			.spyOn(backend as any, "_request")
+			.mockResolvedValue({ results: [] });
+
+		await backend.add("hello", undefined, {
+			userId: "alice",
+			metadata: { source: "test" },
+			expires: "2099-01-01",
+			customInstructions: "Extract only preferences.",
+			customCategories: [{ prefs: "user preferences" }],
+			structuredDataSchema: { type: "object" },
+			timestamp: 1700000000,
+		});
+
+		const payload = spy.mock.calls[0][2].json;
+		expect(payload.custom_instructions).toBe("Extract only preferences.");
+		expect(payload.custom_categories).toEqual([{ prefs: "user preferences" }]);
+		expect(payload.structured_data_schema).toEqual({ type: "object" });
+		expect(payload.timestamp).toBe(1700000000);
+		expect(payload.metadata).toEqual({ source: "test" });
+		expect(payload.expiration_date).toBe("2099-01-01");
+	});
+
+	it("add: omitted optional fields are absent from the payload", async () => {
+		const backend = makeBackend();
+		const spy = vi
+			// biome-ignore lint/suspicious/noExplicitAny: spying on a private method
+			.spyOn(backend as any, "_request")
+			.mockResolvedValue({ results: [] });
+
+		await backend.add("hello", undefined, { userId: "alice" });
+
+		const payload = spy.mock.calls[0][2].json;
+		expect(payload).not.toHaveProperty("custom_instructions");
+		expect(payload).not.toHaveProperty("custom_categories");
+		expect(payload).not.toHaveProperty("structured_data_schema");
+		expect(payload).not.toHaveProperty("timestamp");
+	});
+
+	it("search: show_expired, reference_date, latest_only reach the payload", async () => {
+		const backend = makeBackend();
+		// biome-ignore lint/suspicious/noExplicitAny: spying on a private method
+		const spy = vi.spyOn(backend as any, "_request").mockResolvedValue([]);
+
+		await backend.search("query", {
+			showExpired: true,
+			referenceDate: "2024-01-01",
+			latestOnly: true,
+		});
+
+		const payload = spy.mock.calls[0][2].json;
+		expect(payload.show_expired).toBe(true);
+		expect(payload.reference_date).toBe("2024-01-01");
+		expect(payload.latest_only).toBe(true);
+	});
+
+	it("search: keyword_search and fields reach the payload", async () => {
+		const backend = makeBackend();
+		// biome-ignore lint/suspicious/noExplicitAny: spying on a private method
+		const spy = vi.spyOn(backend as any, "_request").mockResolvedValue([]);
+
+		await backend.search("query", {
+			keyword: true,
+			fields: ["memory", "score"],
+		});
+
+		const payload = spy.mock.calls[0][2].json;
+		expect(payload.keyword_search).toBe(true);
+		expect(payload.fields).toEqual(["memory", "score"]);
+	});
+
+	it("search: omitted keyword and fields are absent from the payload", async () => {
+		const backend = makeBackend();
+		// biome-ignore lint/suspicious/noExplicitAny: spying on a private method
+		const spy = vi.spyOn(backend as any, "_request").mockResolvedValue([]);
+
+		await backend.search("query", {});
+
+		const payload = spy.mock.calls[0][2].json;
+		expect(payload).not.toHaveProperty("keyword_search");
+		expect(payload).not.toHaveProperty("fields");
+	});
+
+	it("listMemories: show_expired and latest_only are top-level, not nested inside filters", async () => {
+		const backend = makeBackend();
+		// biome-ignore lint/suspicious/noExplicitAny: spying on a private method
+		const spy = vi.spyOn(backend as any, "_request").mockResolvedValue([]);
+
+		await backend.listMemories({
+			userId: "alice",
+			showExpired: true,
+			latestOnly: true,
+		});
+
+		const payload = spy.mock.calls[0][2].json;
+		expect(payload.show_expired).toBe(true);
+		expect(payload.latest_only).toBe(true);
+		expect(payload.filters ?? {}).not.toHaveProperty("show_expired");
+		expect(payload.filters ?? {}).not.toHaveProperty("latest_only");
+	});
+
+	it("update: expiration_date and timestamp reach the payload", async () => {
+		const backend = makeBackend();
+		// biome-ignore lint/suspicious/noExplicitAny: spying on a private method
+		const spy = vi.spyOn(backend as any, "_request").mockResolvedValue({});
+
+		await backend.update("mem-123", undefined, undefined, {
+			expirationDate: "2099-01-01",
+			timestamp: 1700000000,
+		});
+
+		const payload = spy.mock.calls[0][2].json;
+		expect(payload.expiration_date).toBe("2099-01-01");
+		expect(payload.timestamp).toBe(1700000000);
+	});
+
+	it("delete: delete_linked is a query param, not part of the JSON body", async () => {
+		const backend = makeBackend();
+		// biome-ignore lint/suspicious/noExplicitAny: spying on a private method
+		const spy = vi.spyOn(backend as any, "_request").mockResolvedValue({});
+
+		await backend.delete("mem-123", { deleteLinked: true });
+
+		const opts = spy.mock.calls[0][2];
+		expect(opts.params.delete_linked).toBe("true");
+		expect(opts.json).toBeUndefined();
+	});
+});
+
+describe("PlatformBackend path encoding", () => {
+	it("encodes memory IDs before interpolating them into paths", async () => {
+		const fetchMock = mockFetch();
+		const backend = makeBackend();
+
+		await backend.get("mem/a?b#c");
+		await backend.update("mem/a?b#c", "updated");
+		await backend.delete("mem/a?b#c");
+
+		const urls = fetchMock.mock.calls.map((call) => call[0]);
+		expect(urls).toEqual([
+			"https://api.mem0.ai/v1/memories/mem%2Fa%3Fb%23c/?source=CLI",
+			"https://api.mem0.ai/v1/memories/mem%2Fa%3Fb%23c/",
+			"https://api.mem0.ai/v1/memories/mem%2Fa%3Fb%23c/?source=CLI",
+		]);
+	});
+
+	it("encodes entity and event IDs before interpolating them into paths", async () => {
+		const fetchMock = mockFetch();
+		const backend = makeBackend();
+
+		await backend.deleteEntities({ userId: "org/team?active#frag" });
+		await backend.getEvent("evt/a?b#c");
+
+		const urls = fetchMock.mock.calls.map((call) => call[0]);
+		expect(urls).toEqual([
+			"https://api.mem0.ai/v2/entities/user/org%2Fteam%3Factive%23frag/?source=CLI",
+			"https://api.mem0.ai/v1/event/evt%2Fa%3Fb%23c/",
+		]);
+	});
+});

cli/python/CHANGELOG.md

@@ -1,49 +0,0 @@
-# Changelog
-
-All notable changes to `mem0-cli` (Python) are documented here.
-
-The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
-and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
-
-## [0.2.8] — 2026-06-19
-
-### Security
-
-- Telemetry no longer passes the Mem0 API key to its child process via
-  command-line arguments. The context is now sent over stdin, so the key is no
-  longer visible in the process list (`ps`, `/proc/<pid>/cmdline`, Activity
-  Monitor). Fixes #4862.
-
-### Fixed
-
-- `__version__` now matches the packaged version (was stale at 0.2.4).
-
-## [0.2.7] — 2026-05-20
-
-### Added
-
-- `mem0 whoami` — print the active agent's `default_user_id` (the AGENTRUSH
-  leaderboard identifier). Reads from local config, no network call.
-- `mem0 agent-rush <add | search>` — subcommand group that wraps the new
-  `/v1/agent-rush/` platform endpoints for the 7-day AGENTRUSH game. Project
-  routing is implicit (resolved server-side); no flags exposed. Pretty-prints
-  platform error codes into actionable hints (e.g. `agentrush_search_first`
-  → "Run 3 'mem0 agent-rush search' commands before adding.").
-- PII safety prompt on first `mem0 agent-rush add`. Interactive runs require
-  explicit `y` to acknowledge that AGENTRUSH memories are public; the
-  acknowledgement is persisted in `~/.mem0/config.json` under
-  `agent_rush.acknowledged_at` so the prompt only appears once per machine.
-  Non-interactive (agent) invocations surface the warning to stderr without
-  blocking.
-- New config schema field: `agent_rush.acknowledged_at` (ISO timestamp,
-  empty until first interactive acknowledgement).
-
-### Changed
-
-- HTTP requests from the new agent-rush commands send `X-Mem0-Mode: agent-rush`
-  in addition to the existing source headers, so platform telemetry can split
-  game traffic from regular CLI usage.
-
-## [0.2.6] and earlier
-
-Unlogged historical releases. See git history under `cli/python/`.

cli/python/README.md

@@ -241,14 +241,6 @@ Verify your API connection and display the current project.
 mem0 status
 ```
 
-### `mem0 version`
-
-Print the CLI version.
-
-```bash
-mem0 version
-```
-
 ## Agent mode
 
 Pass `--agent` (or its alias `--json`) as a **global flag** on any command to get output designed for AI agent tool loops:
@@ -307,6 +299,8 @@ These flags are available on all commands:
 | `--base-url` | Override the configured API base URL for this request |
 | `-o, --output` | Set the output format |
 
+`mem0 --version` prints the CLI version. It is only valid before a subcommand, not after one.
+
 ## Environment variables
 
 | Variable | Description |

cli/python/development.md

@@ -80,7 +80,7 @@ mem0 --help
 # Using Python directly (with venv activated)
 source .venv/bin/activate
 mem0 --help
-mem0 version
+mem0 --version
 
 # Or run without activating
 .venv/bin/mem0 --help

cli/python/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "mem0-cli"
-version = "0.2.8"
+version = "0.2.11"
 description = "The official CLI for mem0 — the memory layer for AI agents"
 readme = "README.md"
 license = "Apache-2.0"

cli/python/src/mem0_cli/__init__.py

@@ -1,3 +1,3 @@
 """mem0 CLI — the command-line interface for the mem0 memory layer."""
 
-__version__ = "0.2.8"
+__version__ = "0.2.11"

cli/python/src/mem0_cli/app.py

@@ -273,7 +273,21 @@ def add(
     no_infer: bool = typer.Option(False, "--no-infer", help="Skip inference, store raw."),
     expires: str | None = typer.Option(None, "--expires", help="Expiration date (YYYY-MM-DD)."),
     categories: str | None = typer.Option(
-        None, "--categories", help="Categories (JSON array or comma-separated)."
+        None, "--categories", help="Not supported on add, use --custom-categories instead."
+    ),
+    custom_instructions: str | None = typer.Option(
+        None, "--custom-instructions", help="Custom instructions for fact extraction."
+    ),
+    custom_categories: str | None = typer.Option(
+        None,
+        "--custom-categories",
+        help="Custom categories as a JSON array of {name: description} objects.",
+    ),
+    structured_data_schema: str | None = typer.Option(
+        None, "--structured-data-schema", help="Schema for structured data extraction, as JSON."
+    ),
+    timestamp: int | None = typer.Option(
+        None, "--timestamp", help="Unix timestamp for the memory."
     ),
     output: str = typer.Option(
         "text", "--output", "-o", help="Output format: text, json, quiet.", rich_help_panel="Output"
@@ -312,6 +326,10 @@ def add(
         no_infer=no_infer,
         expires=expires,
         categories=categories,
+        custom_instructions=custom_instructions,
+        custom_categories=custom_categories,
+        structured_data_schema=structured_data_schema,
+        timestamp=timestamp,
         output=output,
     )
 
@@ -355,6 +373,21 @@ def search(
         help="Specific fields to return (comma-separated).",
         rich_help_panel="Search",
     ),
+    show_expired: bool = typer.Option(
+        False, "--show-expired", help="Include expired memories.", rich_help_panel="Search"
+    ),
+    reference_date: str | None = typer.Option(
+        None,
+        "--reference-date",
+        help="Reference date for relative queries (YYYY-MM-DD or unix timestamp).",
+        rich_help_panel="Search",
+    ),
+    latest_only: bool = typer.Option(
+        False,
+        "--latest-only",
+        help="Only return the latest version of each memory.",
+        rich_help_panel="Search",
+    ),
     output: str = typer.Option(
         "text", "--output", "-o", help="Output: text, json, table.", rich_help_panel="Output"
     ),
@@ -398,6 +431,9 @@ def search(
         keyword=keyword,
         filter_json=filter_json,
         fields=fields,
+        show_expired=show_expired,
+        reference_date=reference_date,
+        latest_only=latest_only,
         output=output,
     )
 
@@ -464,6 +500,15 @@ def list_cmd(
     before: str | None = typer.Option(
         None, "--before", help="Created before (YYYY-MM-DD).", rich_help_panel="Filters"
     ),
+    show_expired: bool = typer.Option(
+        False, "--show-expired", help="Include expired memories.", rich_help_panel="Filters"
+    ),
+    latest_only: bool = typer.Option(
+        False,
+        "--latest-only",
+        help="Only return the latest version of each memory.",
+        rich_help_panel="Filters",
+    ),
     output: str = typer.Option(
         "table", "--output", "-o", help="Output: text, json, table.", rich_help_panel="Output"
     ),
@@ -497,6 +542,8 @@ def list_cmd(
         category=category,
         after=after,
         before=before,
+        show_expired=show_expired,
+        latest_only=latest_only,
         output=output,
     )
 
@@ -509,6 +556,10 @@ def update(
     memory_id: str = typer.Argument(..., help="Memory ID to update."),
     text: str | None = typer.Argument(None, help="New memory text."),
     metadata: str | None = typer.Option(None, "--metadata", "-m", help="Update metadata (JSON)."),
+    expires: str | None = typer.Option(None, "--expires", help="Expiration date (YYYY-MM-DD)."),
+    timestamp: int | None = typer.Option(
+        None, "--timestamp", help="Unix timestamp for the memory."
+    ),
     output: str = typer.Option(
         "text", "--output", "-o", help="Output: text, json, quiet.", rich_help_panel="Output"
     ),
@@ -537,7 +588,15 @@ def update(
         text = _read_stdin()
 
     backend = _get_backend(api_key, base_url)
-    cmd_update(backend, memory_id, text, metadata=metadata, output=output)
+    cmd_update(
+        backend,
+        memory_id,
+        text,
+        metadata=metadata,
+        expires=expires,
+        timestamp=timestamp,
+        output=output,
+    )
 
 
 # ── Memory: delete ────────────────────────────────────────────────────────
@@ -559,6 +618,9 @@ def delete(
         False, "--dry-run", help="Show what would be deleted without deleting."
     ),
     force: bool = typer.Option(False, "--force", help="Skip confirmation."),
+    delete_linked: bool = typer.Option(
+        False, "--delete-linked", help="Also delete memories linked to this memory."
+    ),
     user_id: str | None = typer.Option(
         None, "--user-id", "-u", help="Scope to user.", rich_help_panel="Scope"
     ),
@@ -616,7 +678,14 @@ def delete(
         from mem0_cli.commands.memory import cmd_delete
 
         backend = _get_backend(api_key, base_url)
-        cmd_delete(backend, memory_id, dry_run=dry_run, force=force, output=output)
+        cmd_delete(
+            backend,
+            memory_id,
+            dry_run=dry_run,
+            force=force,
+            delete_linked=delete_linked,
+            output=output,
+        )
 
     elif all_:
         _fire_telemetry("delete", {"delete_mode": "all"})
@@ -1068,7 +1137,11 @@ def _build_help_json() -> dict:
                 "--immutable": "Prevent future updates.",
                 "--no-infer": "Skip inference, store raw.",
                 "--expires": "Expiration date (YYYY-MM-DD).",
-                "--categories": "Categories (JSON array or comma-separated).",
+                "--categories": "Not supported on add, use --custom-categories instead.",
+                "--custom-instructions": "Custom instructions for fact extraction.",
+                "--custom-categories": "Custom categories as a JSON array of {name: description} objects.",
+                "--structured-data-schema": "Schema for structured data extraction, as JSON.",
+                "--timestamp": "Unix timestamp for the memory.",
                 "--graph": "Enable graph memory extraction.",
                 "--no-graph": "Disable graph memory extraction.",
                 "--output, -o": "Output format: text, json, quiet.",
@@ -1087,6 +1160,9 @@ def _build_help_json() -> dict:
                 "--keyword": "Use keyword search instead of semantic.",
                 "--filter": "Advanced filter expression (JSON).",
                 "--fields": "Specific fields to return (comma-separated).",
+                "--show-expired": "Include expired memories.",
+                "--reference-date": "Reference date for relative queries (YYYY-MM-DD or unix timestamp).",
+                "--latest-only": "Only return the latest version of each memory.",
                 "--graph": "Enable graph in search.",
                 "--no-graph": "Disable graph in search.",
                 "--output, -o": "Output format: text, json, table.",
@@ -1110,6 +1186,8 @@ def _build_help_json() -> dict:
                 "--category": "Filter by category.",
                 "--after": "Created after (YYYY-MM-DD).",
                 "--before": "Created before (YYYY-MM-DD).",
+                "--show-expired": "Include expired memories.",
+                "--latest-only": "Only return the latest version of each memory.",
                 "--graph": "Enable graph in listing.",
                 "--no-graph": "Disable graph in listing.",
                 "--output, -o": "Output format: text, json, table.",
@@ -1124,6 +1202,8 @@ def _build_help_json() -> dict:
             },
             "options": {
                 "--metadata, -m": "Update metadata (JSON).",
+                "--expires": "Expiration date (YYYY-MM-DD).",
+                "--timestamp": "Unix timestamp for the memory.",
                 "--output, -o": "Output format: text, json, quiet.",
             },
         },
@@ -1140,6 +1220,7 @@ def _build_help_json() -> dict:
                 "--all": "Delete all memories matching scope filters.",
                 "--entity": "Delete the entity itself and all its memories (cascade).",
                 "--project": "With --all: delete ALL memories project-wide.",
+                "--delete-linked": "Also delete memories linked to this memory.",
                 "--dry-run": "Show what would be deleted without deleting.",
                 "--force": "Skip confirmation.",
                 "--user-id, -u": "Scope to user.",
@@ -1269,8 +1350,10 @@ def help(
       mem0 help
       mem0 help --json
     """
-    if json:
-        console.print(_json.dumps(_build_help_json(), indent=2))
+    from mem0_cli.state import is_agent_mode
+
+    if json or is_agent_mode():
+        console.print_json(_json.dumps(_build_help_json()))
     else:
         console.print(
             f"[{BRAND_COLOR}]◆ mem0 CLI[/] v{__version__} — The Memory Layer for AI Agents\n"

cli/python/src/mem0_cli/backend/base.py

@@ -25,7 +25,10 @@ class Backend(ABC):
         immutable: bool = False,
         infer: bool = True,
         expires: str | None = None,
-        categories: list[str] | None = None,
+        custom_instructions: str | None = None,
+        custom_categories: list[dict] | None = None,
+        structured_data_schema: dict | None = None,
+        timestamp: int | None = None,
     ) -> dict: ...
 
     @abstractmethod
@@ -43,6 +46,9 @@ class Backend(ABC):
         keyword: bool = False,
         filters: dict | None = None,
         fields: list[str] | None = None,
+        show_expired: bool = False,
+        reference_date: str | None = None,
+        latest_only: bool = False,
     ) -> list[dict]: ...
 
     @abstractmethod
@@ -61,11 +67,19 @@ class Backend(ABC):
         category: str | None = None,
         after: str | None = None,
         before: str | None = None,
+        show_expired: bool = False,
+        latest_only: bool = False,
     ) -> list[dict]: ...
 
     @abstractmethod
     def update(
-        self, memory_id: str, content: str | None = None, metadata: dict | None = None
+        self,
+        memory_id: str,
+        content: str | None = None,
+        metadata: dict | None = None,
+        *,
+        expiration_date: str | None = None,
+        timestamp: int | None = None,
     ) -> dict: ...
 
     @abstractmethod
@@ -78,6 +92,7 @@ class Backend(ABC):
         agent_id: str | None = None,
         app_id: str | None = None,
         run_id: str | None = None,
+        delete_linked: bool = False,
     ) -> dict: ...
 
     @abstractmethod

cli/python/src/mem0_cli/backend/platform.py

@@ -3,6 +3,7 @@
 from __future__ import annotations
 
 from typing import Any
+from urllib.parse import quote
 
 import httpx
 
@@ -11,6 +12,10 @@ from mem0_cli.backend.base import Backend
 from mem0_cli.config import PlatformConfig
 
 
+def _encode_path_segment(value: Any) -> str:
+    return quote(str(value), safe="")
+
+
 class PlatformBackend(Backend):
     """Backend that talks to the mem0 Platform API."""
 
@@ -82,7 +87,10 @@ class PlatformBackend(Backend):
         immutable: bool = False,
         infer: bool = True,
         expires: str | None = None,
-        categories: list[str] | None = None,
+        custom_instructions: str | None = None,
+        custom_categories: list[dict] | None = None,
+        structured_data_schema: dict | None = None,
+        timestamp: int | None = None,
     ) -> dict:
         payload: dict[str, Any] = {}
 
@@ -107,8 +115,14 @@ class PlatformBackend(Backend):
             payload["infer"] = False
         if expires:
             payload["expiration_date"] = expires
-        if categories:
-            payload["categories"] = categories
+        if custom_instructions:
+            payload["custom_instructions"] = custom_instructions
+        if custom_categories:
+            payload["custom_categories"] = custom_categories
+        if structured_data_schema:
+            payload["structured_data_schema"] = structured_data_schema
+        if timestamp is not None:
+            payload["timestamp"] = timestamp
         payload["source"] = "CLI"
 
         return self._request("POST", "/v3/memories/add/", json=payload)
@@ -168,6 +182,9 @@ class PlatformBackend(Backend):
         keyword: bool = False,
         filters: dict | None = None,
         fields: list[str] | None = None,
+        show_expired: bool = False,
+        reference_date: str | None = None,
+        latest_only: bool = False,
     ) -> list[dict]:
         payload: dict[str, Any] = {"query": query, "top_k": top_k, "threshold": threshold}
 
@@ -186,6 +203,12 @@ class PlatformBackend(Backend):
             payload["keyword_search"] = True
         if fields:
             payload["fields"] = fields
+        if show_expired:
+            payload["show_expired"] = True
+        if reference_date is not None:
+            payload["reference_date"] = reference_date
+        if latest_only:
+            payload["latest_only"] = True
         payload["source"] = "CLI"
 
         result = self._request("POST", "/v3/memories/search/", json=payload)
@@ -196,7 +219,11 @@ class PlatformBackend(Backend):
         )
 
     def get(self, memory_id: str) -> dict:
-        return self._request("GET", f"/v1/memories/{memory_id}/", params={"source": "CLI"})
+        return self._request(
+            "GET",
+            f"/v1/memories/{_encode_path_segment(memory_id)}/",
+            params={"source": "CLI"},
+        )
 
     def list_memories(
         self,
@@ -210,6 +237,8 @@ class PlatformBackend(Backend):
         category: str | None = None,
         after: str | None = None,
         before: str | None = None,
+        show_expired: bool = False,
+        latest_only: bool = False,
     ) -> list[dict]:
         payload: dict[str, Any] = {}
         params = {"page": str(page), "page_size": str(page_size)}
@@ -232,6 +261,10 @@ class PlatformBackend(Backend):
         )
         if api_filters:
             payload["filters"] = api_filters
+        if show_expired:
+            payload["show_expired"] = True
+        if latest_only:
+            payload["latest_only"] = True
         payload["source"] = "CLI"
 
         result = self._request("POST", "/v3/memories/", json=payload, params=params)
@@ -242,15 +275,29 @@ class PlatformBackend(Backend):
         )
 
     def update(
-        self, memory_id: str, content: str | None = None, metadata: dict | None = None
+        self,
+        memory_id: str,
+        content: str | None = None,
+        metadata: dict | None = None,
+        *,
+        expiration_date: str | None = None,
+        timestamp: int | None = None,
     ) -> dict:
         payload: dict[str, Any] = {}
         if content:
             payload["text"] = content
         if metadata:
             payload["metadata"] = metadata
+        if expiration_date:
+            payload["expiration_date"] = expiration_date
+        if timestamp is not None:
+            payload["timestamp"] = timestamp
         payload["source"] = "CLI"
-        return self._request("PUT", f"/v1/memories/{memory_id}/", json=payload)
+        return self._request(
+            "PUT",
+            f"/v1/memories/{_encode_path_segment(memory_id)}/",
+            json=payload,
+        )
 
     def delete(
         self,
@@ -261,6 +308,7 @@ class PlatformBackend(Backend):
         agent_id: str | None = None,
         app_id: str | None = None,
         run_id: str | None = None,
+        delete_linked: bool = False,
     ) -> dict:
         if all:
             params: dict[str, str] = {"source": "CLI"}
@@ -274,7 +322,14 @@ class PlatformBackend(Backend):
                 params["run_id"] = run_id
             return self._request("DELETE", "/v1/memories/", params=params)
         elif memory_id:
-            return self._request("DELETE", f"/v1/memories/{memory_id}/", params={"source": "CLI"})
+            params = {"source": "CLI"}
+            if delete_linked:
+                params["delete_linked"] = "true"
+            return self._request(
+                "DELETE",
+                f"/v1/memories/{_encode_path_segment(memory_id)}/",
+                params=params,
+            )
         else:
             raise ValueError("Either memory_id or --all is required")
 
@@ -296,13 +351,17 @@ class PlatformBackend(Backend):
         entities = {t: v for t, v in type_map.items() if v}
         if not entities:
             raise ValueError("At least one entity ID is required for delete_entities.")
-        # Delete each provided entity via the v2 path-based endpoint
-        result: dict = {}
+        # Delete each provided entity via the v2 path-based endpoint. Key each
+        # response by entity type so a multi-entity delete (e.g. --user-id and
+        # --agent-id together) doesn't discard everything but the last result.
+        results: dict = {}
         for entity_type, entity_id in entities.items():
-            result = self._request(
-                "DELETE", f"/v2/entities/{entity_type}/{entity_id}/", params={"source": "CLI"}
+            results[entity_type] = self._request(
+                "DELETE",
+                f"/v2/entities/{_encode_path_segment(entity_type)}/{_encode_path_segment(entity_id)}/",
+                params={"source": "CLI"},
             )
-        return result
+        return results
 
     def ping(self, timeout: float | None = None) -> dict:
         """Call the ping endpoint and return the raw response.
@@ -346,7 +405,7 @@ class PlatformBackend(Backend):
         return result if isinstance(result, list) else result.get("results", [])
 
     def get_event(self, event_id: str) -> dict:
-        return self._request("GET", f"/v1/event/{event_id}/")
+        return self._request("GET", f"/v1/event/{_encode_path_segment(event_id)}/")
 
 
 class AuthError(Exception):

cli/python/src/mem0_cli/commands/memory.py

@@ -4,9 +4,11 @@ from __future__ import annotations
 
 import json
 import os
+import re
 import stat as _stat_mod
 import sys
 import time as _time
+from datetime import date
 from pathlib import Path
 
 import typer
@@ -47,6 +49,18 @@ def _stdin_is_piped() -> bool:
         return False
 
 
+def _validate_expires(value: str) -> None:
+    """Exit 1 if value is not a future YYYY-MM-DD date."""
+    if not re.match(r"^\d{4}-\d{2}-\d{2}$", value):
+        print_error(
+            err_console, "Invalid date format for --expires. Use YYYY-MM-DD (e.g. 2025-12-31)."
+        )
+        raise typer.Exit(1)
+    if date.fromisoformat(value) <= date.today():
+        print_error(err_console, "--expires date must be in the future.")
+        raise typer.Exit(1)
+
+
 def cmd_add(
     backend: Backend,
     text: str | None,
@@ -62,6 +76,10 @@ def cmd_add(
     no_infer: bool,
     expires: str | None,
     categories: str | None,
+    custom_instructions: str | None = None,
+    custom_categories: str | None = None,
+    structured_data_schema: str | None = None,
+    timestamp: int | None = None,
     output: str = "text",
 ) -> None:
     """Add a memory."""
@@ -70,6 +88,13 @@ def cmd_add(
     set_current_command("add")
     if is_agent_mode():
         output = "agent"
+
+    if categories:
+        print_error(
+            err_console, "--categories is not supported on add. Use --custom-categories instead."
+        )
+        raise typer.Exit(1)
+
     msgs = None
     content = text
 
@@ -108,27 +133,24 @@ def cmd_add(
             print_error(err_console, "Invalid JSON in --metadata.")
             raise typer.Exit(1) from None
 
-    cats = None
-    if categories:
+    custom_cats = None
+    if custom_categories:
         try:
-            cats = json.loads(categories)
+            custom_cats = json.loads(custom_categories)
         except json.JSONDecodeError:
-            cats = [c.strip() for c in categories.split(",")]
+            print_error(err_console, "Invalid JSON in --custom-categories.")
+            raise typer.Exit(1) from None
+
+    schema = None
+    if structured_data_schema:
+        try:
+            schema = json.loads(structured_data_schema)
+        except json.JSONDecodeError:
+            print_error(err_console, "Invalid JSON in --structured-data-schema.")
+            raise typer.Exit(1) from None
 
-    # Validate --expires
     if expires:
-        import re
-
-        if not re.match(r"^\d{4}-\d{2}-\d{2}$", expires):
-            print_error(
-                err_console, "Invalid date format for --expires. Use YYYY-MM-DD (e.g. 2025-12-31)."
-            )
-            raise typer.Exit(1)
-        from datetime import date
-
-        if date.fromisoformat(expires) <= date.today():
-            print_error(err_console, "--expires date must be in the future.")
-            raise typer.Exit(1)
+        _validate_expires(expires)
 
     with timed_status(err_console, "Adding memory...") as ts:
         try:
@@ -143,7 +165,10 @@ def cmd_add(
                 immutable=immutable,
                 infer=not no_infer,
                 expires=expires,
-                categories=cats,
+                custom_instructions=custom_instructions,
+                custom_categories=custom_cats,
+                structured_data_schema=schema,
+                timestamp=timestamp,
             )
         except Exception as e:
             ts.error_msg = str(e)
@@ -224,6 +249,9 @@ def cmd_search(
     keyword: bool,
     filter_json: str | None,
     fields: str | None,
+    show_expired: bool = False,
+    reference_date: str | None = None,
+    latest_only: bool = False,
     output: str = "text",
 ) -> None:
     """Search memories."""
@@ -266,6 +294,9 @@ def cmd_search(
                 keyword=keyword,
                 filters=filters,
                 fields=field_list,
+                show_expired=show_expired,
+                reference_date=reference_date,
+                latest_only=latest_only,
             )
         except Exception as e:
             print_error(err_console, str(e))
@@ -352,6 +383,8 @@ def cmd_list(
     category: str | None,
     after: str | None,
     before: str | None,
+    show_expired: bool = False,
+    latest_only: bool = False,
     output: str = "table",
 ) -> None:
     """List memories."""
@@ -380,6 +413,8 @@ def cmd_list(
                 category=category,
                 after=after,
                 before=before,
+                show_expired=show_expired,
+                latest_only=latest_only,
             )
         except Exception as e:
             print_error(err_console, str(e))
@@ -446,6 +481,8 @@ def cmd_update(
     text: str | None,
     *,
     metadata: str | None,
+    expires: str | None = None,
+    timestamp: int | None = None,
     output: str,
 ) -> None:
     """Update a memory."""
@@ -462,10 +499,19 @@ def cmd_update(
             print_error(err_console, "Invalid JSON in --metadata.")
             raise typer.Exit(1) from None
 
+    if expires:
+        _validate_expires(expires)
+
     _start = _time.perf_counter()
     with timed_status(err_console, "Updating memory...") as _ts:
         try:
-            result = backend.update(memory_id, content=text, metadata=meta)
+            result = backend.update(
+                memory_id,
+                content=text,
+                metadata=meta,
+                expiration_date=expires,
+                timestamp=timestamp,
+            )
         except Exception as e:
             print_error(err_console, str(e))
             raise typer.Exit(1) from None
@@ -490,6 +536,7 @@ def cmd_delete(
     *,
     dry_run: bool = False,
     force: bool = False,
+    delete_linked: bool = False,
     output: str,
 ) -> None:
     """Delete a single memory by ID."""
@@ -512,7 +559,7 @@ def cmd_delete(
     _start = _time.perf_counter()
     with timed_status(err_console, "Deleting...") as _ts:
         try:
-            result = backend.delete(memory_id=memory_id)
+            result = backend.delete(memory_id=memory_id, delete_linked=delete_linked)
         except Exception as e:
             print_error(err_console, str(e))
             raise typer.Exit(1) from None

cli/python/src/mem0_cli/config.py

@@ -235,7 +235,10 @@ def set_nested_value(config: Mem0Config, dotted_key: str, value: str) -> bool:
     if isinstance(current, bool):
         value = value.lower() in ("true", "1", "yes")  # type: ignore[assignment]
     elif isinstance(current, int):
-        value = int(value)  # type: ignore[assignment]
+        try:
+            value = int(value)  # type: ignore[assignment]
+        except ValueError:
+            return False
 
     setattr(obj, final_key, value)
     return True

cli/python/src/mem0_cli/output.py

@@ -20,8 +20,8 @@ def format_memories_text(console: Console, memories: list[dict], title: str = "m
     console.print(f"\n[{BRAND_COLOR}]Found {count} {title}:[/]\n")
 
     for i, mem in enumerate(memories, 1):
-        memory_text = mem.get("memory", mem.get("text", ""))
-        mem_id = mem.get("id", "")[:8]
+        memory_text = mem.get("memory") or mem.get("text") or ""
+        mem_id = (mem.get("id") or "")[:8]
         score = mem.get("score")
         created = _format_date(mem.get("created_at"))
         category = mem.get("categories", [None])
@@ -67,8 +67,8 @@ def format_memories_table(
     table.add_column("Created", max_width=12)
 
     for mem in memories:
-        mem_id = mem.get("id", "")
-        memory_text = mem.get("memory", mem.get("text", ""))
+        mem_id = mem.get("id") or ""
+        memory_text = mem.get("memory") or mem.get("text") or ""
         if len(memory_text) > 60:
             memory_text = memory_text[:57] + "..."
         categories = mem.get("categories", [])
@@ -104,8 +104,8 @@ def format_single_memory(console: Console, mem: dict, output: str = "text") -> N
         format_json(console, mem)
         return
 
-    memory_text = mem.get("memory", mem.get("text", ""))
-    mem_id = mem.get("id", "")
+    memory_text = mem.get("memory") or mem.get("text") or ""
+    mem_id = mem.get("id") or ""
 
     lines = []
     lines.append(f"  [white bold]{memory_text}[/]")
@@ -262,16 +262,32 @@ def sanitize_agent_data(command: str, data: Any) -> Any:
         return result
 
     if command == "search":
-        return [pick(r, ["id", "memory", "score", "created_at", "categories"]) for r in data]
+        return [
+            pick(r, ["id", "memory", "score", "created_at", "categories", "expiration_date"])
+            for r in data
+        ]
 
     if command == "list":
-        return [pick(r, ["id", "memory", "created_at", "categories"]) for r in data]
+        return [
+            pick(r, ["id", "memory", "created_at", "categories", "expiration_date"]) for r in data
+        ]
 
     if command == "get":
-        return pick(data, ["id", "memory", "created_at", "updated_at", "categories", "metadata"])
+        return pick(
+            data,
+            [
+                "id",
+                "memory",
+                "created_at",
+                "updated_at",
+                "categories",
+                "metadata",
+                "expiration_date",
+            ],
+        )
 
     if command == "update":
-        return pick(data, ["id", "memory"])
+        return pick(data, ["id", "memory", "expiration_date"])
 
     if command in ("delete", "delete-all", "entity delete"):
         return data

cli/python/tests/test_cli_integration.py

@@ -7,6 +7,7 @@ boundaries).
 
 from __future__ import annotations
 
+import json
 import os
 import re
 import subprocess
@@ -84,6 +85,31 @@ class TestCLIIntegration:
         assert "add" in result.stdout
         assert "search" in result.stdout
 
+    def test_version_flag_only(self):
+        from mem0_cli import __version__
+
+        flag = _run(["--version"])
+        assert flag.returncode == 0
+        assert __version__ in flag.stdout
+        assert _run(["version"]).returncode != 0
+
+    @pytest.mark.parametrize(
+        "args",
+        [["help", "--json"], ["--json", "help"], ["help", "--agent"], ["--agent", "help"]],
+    )
+    def test_help_json_produces_valid_json(self, args):
+        result = _run(args)
+        assert result.returncode == 0
+        spec = json.loads(result.stdout)
+        assert spec["name"] == "mem0"
+        assert "add" in spec["commands"]
+
+    def test_help_without_json_is_text(self):
+        result = _run(["help"])
+        assert result.returncode == 0
+        with pytest.raises(json.JSONDecodeError):
+            json.loads(result.stdout)
+
     def test_add_help(self):
         result = _run(["add", "--help"])
         assert result.returncode == 0

cli/python/tests/test_commands.py

@@ -252,12 +252,13 @@ class TestAddCommand:
             )
         mock_backend.add.assert_called_once()
 
-    def test_add_categories_csv(self, mock_backend):
+    def test_add_categories_rejected(self, mock_backend):
         console, _buf = _make_console()
-        err_console, _err_buf = _make_err_console()
+        err_console, err_buf = _make_err_console()
         with (
             patch("mem0_cli.commands.memory.console", console),
             patch("mem0_cli.commands.memory.err_console", err_console),
+            pytest.raises((SystemExit, TyperExit)),
         ):
             cmd_add(
                 mock_backend,
@@ -275,7 +276,93 @@ class TestAddCommand:
                 categories="health,prefs",
                 output="text",
             )
-        mock_backend.add.assert_called_once()
+        assert "--custom-categories" in err_buf.getvalue()
+        mock_backend.add.assert_not_called()
+
+    def test_add_invalid_custom_categories_json(self, mock_backend):
+        console, _buf = _make_console()
+        err_console, err_buf = _make_err_console()
+        with (
+            patch("mem0_cli.commands.memory.console", console),
+            patch("mem0_cli.commands.memory.err_console", err_console),
+            pytest.raises((SystemExit, TyperExit)),
+        ):
+            cmd_add(
+                mock_backend,
+                "test",
+                user_id="alice",
+                agent_id=None,
+                app_id=None,
+                run_id=None,
+                messages=None,
+                file=None,
+                metadata=None,
+                immutable=False,
+                no_infer=False,
+                expires=None,
+                categories=None,
+                custom_categories="not-json",
+                output="text",
+            )
+        assert "--custom-categories" in err_buf.getvalue()
+        mock_backend.add.assert_not_called()
+
+    def test_add_invalid_structured_data_schema_json(self, mock_backend):
+        console, _buf = _make_console()
+        err_console, err_buf = _make_err_console()
+        with (
+            patch("mem0_cli.commands.memory.console", console),
+            patch("mem0_cli.commands.memory.err_console", err_console),
+            pytest.raises((SystemExit, TyperExit)),
+        ):
+            cmd_add(
+                mock_backend,
+                "test",
+                user_id="alice",
+                agent_id=None,
+                app_id=None,
+                run_id=None,
+                messages=None,
+                file=None,
+                metadata=None,
+                immutable=False,
+                no_infer=False,
+                expires=None,
+                categories=None,
+                structured_data_schema="not-json",
+                output="text",
+            )
+        assert "--structured-data-schema" in err_buf.getvalue()
+        mock_backend.add.assert_not_called()
+
+    def test_add_regression_metadata_expiration_custom_categories_together(self, mock_backend):
+        console, _buf = _make_console()
+        err_console, _err_buf = _make_err_console()
+        with (
+            patch("mem0_cli.commands.memory.console", console),
+            patch("mem0_cli.commands.memory.err_console", err_console),
+        ):
+            cmd_add(
+                mock_backend,
+                "test",
+                user_id="alice",
+                agent_id=None,
+                app_id=None,
+                run_id=None,
+                messages=None,
+                file=None,
+                metadata='{"source": "test"}',
+                immutable=False,
+                no_infer=False,
+                expires="2099-01-01",
+                categories=None,
+                custom_categories='[{"prefs": "user preferences"}]',
+                output="text",
+            )
+        call_kwargs = mock_backend.add.call_args.kwargs
+        assert call_kwargs["metadata"] == {"source": "test"}
+        assert call_kwargs["expires"] == "2099-01-01"
+        assert call_kwargs["custom_categories"] == [{"prefs": "user preferences"}]
 
 
 class TestAddDeduplicatesPending:
@@ -464,6 +551,36 @@ class TestSearchCommand:
             )
         mock_backend.search.assert_called_once()
 
+    def test_search_new_flags_reach_backend(self, mock_backend):
+        console, _buf = _make_console()
+        err_console, _err_buf = _make_err_console()
+        with (
+            patch("mem0_cli.commands.memory.console", console),
+            patch("mem0_cli.commands.memory.err_console", err_console),
+        ):
+            cmd_search(
+                mock_backend,
+                "preferences",
+                user_id="alice",
+                agent_id=None,
+                app_id=None,
+                run_id=None,
+                top_k=10,
+                threshold=0.3,
+                rerank=False,
+                keyword=False,
+                filter_json=None,
+                fields=None,
+                show_expired=True,
+                reference_date="2024-01-01",
+                latest_only=True,
+                output="text",
+            )
+        call_kwargs = mock_backend.search.call_args.kwargs
+        assert call_kwargs["show_expired"] is True
+        assert call_kwargs["reference_date"] == "2024-01-01"
+        assert call_kwargs["latest_only"] is True
+
 
 class TestGetCommand:
     def test_get_text(self, mock_backend):
@@ -561,6 +678,32 @@ class TestListCommand:
         output = buf.getvalue()
         assert "No memories found" in output
 
+    def test_list_new_flags_reach_backend(self, mock_backend):
+        console, _buf = _make_console()
+        err_console, _err_buf = _make_err_console()
+        with (
+            patch("mem0_cli.commands.memory.console", console),
+            patch("mem0_cli.commands.memory.err_console", err_console),
+        ):
+            cmd_list(
+                mock_backend,
+                user_id="alice",
+                agent_id=None,
+                app_id=None,
+                run_id=None,
+                page=1,
+                page_size=100,
+                category=None,
+                after=None,
+                before=None,
+                show_expired=True,
+                latest_only=True,
+                output="table",
+            )
+        call_kwargs = mock_backend.list_memories.call_args.kwargs
+        assert call_kwargs["show_expired"] is True
+        assert call_kwargs["latest_only"] is True
+
 
 class TestUpdateCommand:
     def test_update(self, mock_backend):
@@ -585,6 +728,26 @@ class TestUpdateCommand:
         output = buf.getvalue()
         assert '"memory"' in output
 
+    def test_update_new_fields_reach_backend(self, mock_backend):
+        console, _buf = _make_console()
+        err_console, _err_buf = _make_err_console()
+        with (
+            patch("mem0_cli.commands.memory.console", console),
+            patch("mem0_cli.commands.memory.err_console", err_console),
+        ):
+            cmd_update(
+                mock_backend,
+                "abc-123",
+                "New text",
+                metadata=None,
+                expires="2099-01-01",
+                timestamp=1700000000,
+                output="text",
+            )
+        call_kwargs = mock_backend.update.call_args.kwargs
+        assert call_kwargs["expiration_date"] == "2099-01-01"
+        assert call_kwargs["timestamp"] == 1700000000
+
 
 class TestDeleteCommand:
     def test_delete_single(self, mock_backend):
@@ -610,6 +773,17 @@ class TestDeleteCommand:
         assert "dry run" in output.lower()
         mock_backend.delete.assert_not_called()
 
+    def test_delete_linked_reaches_backend(self, mock_backend):
+        console, _buf = _make_console()
+        err_console, _err_buf = _make_err_console()
+        with (
+            patch("mem0_cli.commands.memory.console", console),
+            patch("mem0_cli.commands.memory.err_console", err_console),
+        ):
+            cmd_delete(mock_backend, "abc-123", delete_linked=True, output="text")
+        call_kwargs = mock_backend.delete.call_args.kwargs
+        assert call_kwargs["delete_linked"] is True
+
 
 class TestDeleteAllCommand:
     def test_delete_all_force(self, mock_backend):

cli/python/tests/test_config.py

@@ -139,6 +139,11 @@ class TestNestedAccess:
         assert set_nested_value(config, "platform.api_key", "new-key")
         assert config.platform.api_key == "new-key"
 
+    def test_set_int_value_rejects_invalid_input(self):
+        config = Mem0Config()
+        assert set_nested_value(config, "version", "abc") is False
+        assert config.version == 1
+
     def test_set_nonexistent_key(self):
         config = Mem0Config()
         assert set_nested_value(config, "nonexistent.key", "val") is False

cli/python/tests/test_option_parity.py

@@ -0,0 +1,102 @@
+"""Drift test: every documented v3 add/search/list param must be reachable from the Python CLI."""
+
+import json
+from pathlib import Path
+
+import typer.main
+
+from mem0_cli.app import app
+
+REPO_ROOT = Path(__file__).resolve().parents[3]
+OPENAPI_PATH = REPO_ROOT / "docs" / "openapi.json"
+
+KNOWN_UNSURFACED: dict[tuple[str, str], str] = {
+    ("/v3/memories/add/", "includes"): "extraction hint, no CLI flag yet",
+    ("/v3/memories/add/", "excludes"): "extraction hint, no CLI flag yet",
+    ("/v3/memories/add/", "enable_graph"): "graph memory toggle, no CLI flag yet",
+    ("/v3/memories/add/", "output_format"): "response envelope is pinned by the CLI",
+    ("/v3/memories/add/", "prompt_profile_id"): "no CLI flag yet",
+    ("/v3/memories/add/", "temporal_reasoning"): "no CLI flag yet",
+    ("/v3/memories/add/", "timezone"): "no CLI flag yet",
+    ("/v3/memories/add/", "observation_datetime"): "no CLI flag yet, --timestamp backdates instead",
+    ("/v3/memories/add/", "observation_date"): "no CLI flag yet, --timestamp backdates instead",
+    ("/v3/memories/search/", "categories"): "expressible through --filter",
+    ("/v3/memories/search/", "metadata"): "expressible through --filter",
+    ("/v3/memories/", "start_date"): "covered by --after via filters.created_at.gte",
+    ("/v3/memories/", "end_date"): "covered by --before via filters.created_at.lte",
+    ("/v3/memories/", "categories"): "covered by --category via filters.categories",
+    ("/v3/memories/", "fields"): "no CLI flag yet",
+    ("/v3/memories/", "keywords"): "no CLI flag yet",
+}
+
+ADD_MAPPING: dict[str, list[str]] = {
+    "messages": ["messages", "file", "text"],
+    "user_id": ["user_id"],
+    "agent_id": ["agent_id"],
+    "app_id": ["app_id"],
+    "run_id": ["run_id"],
+    "metadata": ["metadata"],
+    "expiration_date": ["expires"],
+    "custom_instructions": ["custom_instructions"],
+    "custom_categories": ["custom_categories"],
+    "infer": ["no_infer"],
+    "immutable": ["immutable"],
+    "structured_data_schema": ["structured_data_schema"],
+    "timestamp": ["timestamp"],
+}
+
+SEARCH_MAPPING: dict[str, list[str]] = {
+    "query": ["query"],
+    "filters": ["filter_json", "user_id", "agent_id", "run_id"],
+    "show_expired": ["show_expired"],
+    "top_k": ["top_k"],
+    "threshold": ["threshold"],
+    "rerank": ["rerank"],
+    "reference_date": ["reference_date"],
+    "fields": ["fields"],
+}
+
+LIST_MAPPING: dict[str, list[str]] = {
+    "filters": ["user_id", "agent_id", "run_id", "category", "after", "before"],
+    "show_expired": ["show_expired"],
+    "page": ["page"],
+    "page_size": ["page_size"],
+}
+
+
+def _documented_fields(endpoint: str) -> set[str]:
+    spec = json.loads(OPENAPI_PATH.read_text())
+    schema = spec["paths"][endpoint]["post"]["requestBody"]["content"]["application/json"]["schema"]
+    return set(schema["properties"])
+
+
+def _cli_param_names(command_name: str) -> set[str]:
+    click_app = typer.main.get_command(app)
+    command = click_app.commands[command_name]
+    return {param.name for param in command.params}
+
+
+def _assert_all_reachable(endpoint: str, mapping: dict[str, list[str]], command_name: str) -> None:
+    documented = _documented_fields(endpoint)
+    reachable = _cli_param_names(command_name)
+    for field in documented:
+        if (endpoint, field) in KNOWN_UNSURFACED:
+            continue
+        candidates = mapping.get(field)
+        assert candidates, (
+            f"{endpoint}: documented field {field!r} has no mapping entry for command {command_name!r}"
+        )
+        assert any(candidate in reachable for candidate in candidates), (
+            f"{endpoint}: documented field {field!r} not reachable via any of {candidates} on command {command_name!r}"
+        )
+
+
+class TestOptionParity:
+    def test_add_covers_documented_fields(self):
+        _assert_all_reachable("/v3/memories/add/", ADD_MAPPING, "add")
+
+    def test_search_covers_documented_fields(self):
+        _assert_all_reachable("/v3/memories/search/", SEARCH_MAPPING, "search")
+
+    def test_list_covers_documented_fields(self):
+        _assert_all_reachable("/v3/memories/", LIST_MAPPING, "list")

cli/python/tests/test_output.py

@@ -54,6 +54,11 @@ class TestTextFormat:
         output = buf.getvalue()
         assert "Found 0" in output
 
+    def test_format_memories_text_handles_null_fields(self):
+        console, buf = _make_console()
+        format_memories_text(console, [{"id": None, "memory": None, "created_at": None}])
+        assert "Found 1 memories" in buf.getvalue()
+
 
 class TestTableFormat:
     def test_format_memories_table(self):
@@ -70,6 +75,13 @@ class TestTableFormat:
         # Should still render (empty table)
         assert "ID" in output
 
+    def test_format_memories_table_handles_null_fields(self):
+        console, buf = _make_console()
+        format_memories_table(console, [{"id": None, "memory": None, "created_at": None}])
+        output = buf.getvalue()
+        assert "ID" in output
+        assert "Memory" in output
+
 
 class TestSingleMemory:
     def test_format_single_memory_text(self):
@@ -87,6 +99,17 @@ class TestSingleMemory:
         output = buf.getvalue()
         assert '"memory"' in output
 
+    def test_format_single_memory_handles_null_fields(self):
+        console, buf = _make_console()
+        format_single_memory(
+            console,
+            {"id": None, "memory": None, "text": "Fallback memory", "created_at": None},
+            "text",
+        )
+        output = buf.getvalue()
+        assert "Fallback memory" in output
+        assert "ID:" not in output
+
 
 class TestAddResult:
     def test_format_add_result_text(self):

cli/python/tests/test_platform_backend.py

@@ -0,0 +1,46 @@
+"""Tests for the Platform backend (mem0 Platform API client)."""
+
+from __future__ import annotations
+
+from unittest.mock import patch
+
+from mem0_cli.backend.platform import PlatformBackend
+from mem0_cli.config import PlatformConfig
+
+
+def _make_backend() -> PlatformBackend:
+    # api_key/base_url are only used to build the httpx client; every test here
+    # patches _request, so no real network calls are made.
+    return PlatformBackend(PlatformConfig(api_key="test-key", base_url="https://api.mem0.ai"))
+
+
+class TestDeleteEntities:
+    def test_multiple_entities_returns_all_results(self):
+        backend = _make_backend()
+        responses = {
+            "/v2/entities/user/alice/": {"message": "user deleted"},
+            "/v2/entities/agent/bob/": {"message": "agent deleted"},
+        }
+        with patch.object(backend, "_request") as mock_request:
+            mock_request.side_effect = lambda method, path, **kw: responses[path]
+            result = backend.delete_entities(user_id="alice", agent_id="bob")
+
+        # Regression: previously only the last entity's response survived.
+        assert result == {
+            "user": {"message": "user deleted"},
+            "agent": {"message": "agent deleted"},
+        }
+        assert mock_request.call_count == 2
+
+    def test_single_entity_keyed_by_type(self):
+        backend = _make_backend()
+        with patch.object(backend, "_request", return_value={"message": "user deleted"}):
+            result = backend.delete_entities(user_id="alice")
+        assert result == {"user": {"message": "user deleted"}}
+
+    def test_no_entities_raises(self):
+        backend = _make_backend()
+        import pytest
+
+        with pytest.raises(ValueError):
+            backend.delete_entities()

cli/python/tests/test_platform_backend_options.py

@@ -0,0 +1,109 @@
+"""Tests that the MEM-5893 option-parity flags reach the correct request payload/params."""
+
+from __future__ import annotations
+
+from unittest.mock import patch
+
+from mem0_cli.backend.platform import PlatformBackend
+from mem0_cli.config import PlatformConfig
+
+
+def _make_backend() -> PlatformBackend:
+    return PlatformBackend(PlatformConfig(api_key="test-key", base_url="https://api.mem0.ai"))
+
+
+class TestAddOptions:
+    def test_new_fields_and_existing_fields_land_in_payload_together(self):
+        backend = _make_backend()
+        with patch.object(backend, "_request", return_value={"results": []}) as mock_request:
+            backend.add(
+                content="hello",
+                user_id="alice",
+                metadata={"source": "test"},
+                expires="2099-01-01",
+                custom_instructions="Extract only preferences.",
+                custom_categories=[{"prefs": "user preferences"}],
+                structured_data_schema={"type": "object"},
+                timestamp=1700000000,
+            )
+        payload = mock_request.call_args.kwargs["json"]
+        assert payload["custom_instructions"] == "Extract only preferences."
+        assert payload["custom_categories"] == [{"prefs": "user preferences"}]
+        assert payload["structured_data_schema"] == {"type": "object"}
+        assert payload["timestamp"] == 1700000000
+        assert payload["metadata"] == {"source": "test"}
+        assert payload["expiration_date"] == "2099-01-01"
+
+    def test_omitted_fields_are_absent_from_payload(self):
+        backend = _make_backend()
+        with patch.object(backend, "_request", return_value={"results": []}) as mock_request:
+            backend.add(content="hello", user_id="alice")
+        payload = mock_request.call_args.kwargs["json"]
+        assert "custom_instructions" not in payload
+        assert "custom_categories" not in payload
+        assert "structured_data_schema" not in payload
+        assert "timestamp" not in payload
+
+
+class TestSearchOptions:
+    def test_show_expired_reference_date_latest_only_reach_payload(self):
+        backend = _make_backend()
+        with patch.object(backend, "_request", return_value=[]) as mock_request:
+            backend.search(
+                "query",
+                show_expired=True,
+                reference_date="2024-01-01",
+                latest_only=True,
+            )
+        payload = mock_request.call_args.kwargs["json"]
+        assert payload["show_expired"] is True
+        assert payload["reference_date"] == "2024-01-01"
+        assert payload["latest_only"] is True
+
+    def test_keyword_and_fields_reach_payload(self):
+        backend = _make_backend()
+        with patch.object(backend, "_request", return_value=[]) as mock_request:
+            backend.search("query", keyword=True, fields=["memory", "score"])
+        payload = mock_request.call_args.kwargs["json"]
+        assert payload["keyword_search"] is True
+        assert payload["fields"] == ["memory", "score"]
+
+    def test_keyword_and_fields_omitted_are_absent_from_payload(self):
+        backend = _make_backend()
+        with patch.object(backend, "_request", return_value=[]) as mock_request:
+            backend.search("query")
+        payload = mock_request.call_args.kwargs["json"]
+        assert "keyword_search" not in payload
+        assert "fields" not in payload
+
+
+class TestListOptions:
+    def test_show_expired_and_latest_only_are_top_level_not_in_filters(self):
+        backend = _make_backend()
+        with patch.object(backend, "_request", return_value=[]) as mock_request:
+            backend.list_memories(user_id="alice", show_expired=True, latest_only=True)
+        payload = mock_request.call_args.kwargs["json"]
+        assert payload["show_expired"] is True
+        assert payload["latest_only"] is True
+        assert "show_expired" not in payload.get("filters", {})
+        assert "latest_only" not in payload.get("filters", {})
+
+
+class TestUpdateOptions:
+    def test_expires_and_timestamp_reach_payload(self):
+        backend = _make_backend()
+        with patch.object(backend, "_request", return_value={}) as mock_request:
+            backend.update("mem-123", expiration_date="2099-01-01", timestamp=1700000000)
+        payload = mock_request.call_args.kwargs["json"]
+        assert payload["expiration_date"] == "2099-01-01"
+        assert payload["timestamp"] == 1700000000
+
+
+class TestDeleteOptions:
+    def test_delete_linked_is_a_query_param_not_json_body(self):
+        backend = _make_backend()
+        with patch.object(backend, "_request", return_value={}) as mock_request:
+            backend.delete(memory_id="mem-123", delete_linked=True)
+        call = mock_request.call_args
+        assert call.kwargs["params"]["delete_linked"] == "true"
+        assert "json" not in call.kwargs

cli/python/tests/test_platform_backend_paths.py

@@ -0,0 +1,43 @@
+from unittest.mock import MagicMock
+
+from mem0_cli.backend.platform import PlatformBackend
+
+
+def _backend(sample_config):
+    backend = PlatformBackend(sample_config.platform)
+    backend._client = MagicMock()
+    backend._client.request.return_value = MagicMock(
+        status_code=200,
+        json=lambda: {"message": "ok"},
+        headers={},
+        raise_for_status=lambda: None,
+    )
+    return backend
+
+
+def test_memory_id_path_segments_are_encoded(sample_config):
+    backend = _backend(sample_config)
+
+    backend.get("mem/a?b#c")
+    backend.update("mem/a?b#c", content="updated")
+    backend.delete("mem/a?b#c")
+
+    paths = [call.args[1] for call in backend._client.request.call_args_list]
+    assert paths == [
+        "/v1/memories/mem%2Fa%3Fb%23c/",
+        "/v1/memories/mem%2Fa%3Fb%23c/",
+        "/v1/memories/mem%2Fa%3Fb%23c/",
+    ]
+
+
+def test_entity_and_event_path_segments_are_encoded(sample_config):
+    backend = _backend(sample_config)
+
+    backend.delete_entities(user_id="org/team?active#frag")
+    backend.get_event("evt/a?b#c")
+
+    paths = [call.args[1] for call in backend._client.request.call_args_list]
+    assert paths == [
+        "/v2/entities/user/org%2Fteam%3Factive%23frag/",
+        "/v1/event/evt%2Fa%3Fb%23c/",
+    ]

docs/README.md

@@ -24,7 +24,7 @@ mintlify dev
 
 ### Publishing Changes
 
-Install our Github App to auto propagate changes from your repo to your deployment. Changes will be deployed to production automatically after pushing to the default branch. Find the link to install on your dashboard. 
+Install our GitHub App to auto-propagate changes from your repo to your deployment. Changes will be deployed to production automatically after pushing to the default branch. Find the link to install on your dashboard. 
 
 #### Troubleshooting
 

docs/_snippets/star-on-github.mdx

@@ -0,0 +1,5 @@
+{/* Subtle, value-anchored nudge to star the repo. Drop in at peak-end "win" moments in the OSS docs (after a successful add/search, a server bootstrap, etc.). Keep it off the Platform/API pages. */}
+{/* Clicks are tracked via PostHog autocapture: the data-ph-capture-attribute-cta below tags each click with cta="star-on-github" so it's filterable as an event property. Metric = count of $autocapture where cta = star-on-github; break down by Current URL to see which win-moment converts. */}
+<Callout icon="star" iconType="solid" color="#FACC15">
+  **Using Mem0?** <a href="https://github.com/mem0ai/mem0" data-ph-capture-attribute-cta="star-on-github">Star us on GitHub</a> to help more developers discover memory for AI apps.
+</Callout>

docs/api-reference.mdx

@@ -97,7 +97,7 @@ Get your API key from the <a href="https://app.mem0.ai/dashboard/api-keys?utm_so
 
 ## Next Steps
 
-<CardGroup cols={2}>
+<CardGroup cols={3}>
   <Card title="Add Your First Memory" icon="rocket" href="/api-reference/memory/add-memories">
     Start storing memories via the REST API
   </Card>
@@ -105,4 +105,8 @@ Get your API key from the <a href="https://app.mem0.ai/dashboard/api-keys?utm_so
   <Card title="Search with Filters" icon="filter" href="/api-reference/memory/search-memories">
     Learn advanced search and filtering techniques
   </Card>
+
+  <Card title="Build with cookbooks" icon="book-open" href="/cookbooks/overview">
+    See the API used end to end in real projects.
+  </Card>
 </CardGroup>

docs/api-reference/memory/add-memories.mdx

@@ -4,7 +4,7 @@ description: "Add facts, messages, or metadata to a user memory store with async
 openapi: post /v3/memories/add/
 ---
 
-Extract and store memories from a conversation using the V3 additive pipeline. The endpoint uses single-pass ADD-only extraction — one LLM call, no UPDATE/DELETE. Memories accumulate over time; nothing is overwritten.
+Extract and store memories from a conversation using the V3 additive pipeline. The endpoint uses single-pass ADD-only extraction: one LLM call, no UPDATE/DELETE. Memories accumulate over time; nothing is overwritten.
 
 ## Endpoint
 
@@ -50,6 +50,7 @@ Provide conversation messages for Mem0 to extract memories from. At least one en
 | `app_id` | string | No* | Associates the memory with an app. |
 | `metadata` | object | Optional | Custom key/value metadata (e.g., `{"topic": "preferences"}`). |
 | `infer` | boolean (default `true`) | Optional | Set to `false` to skip inference and store the provided text as-is. |
+| `expiration_date` | string | Optional | Date in `YYYY-MM-DD` format. The memory is visible through this date and hidden by default after it passes. |
 
 > \* At least one entity ID (`user_id`, `agent_id`, `app_id`, or `run_id`) is required.
 
@@ -64,9 +65,8 @@ The request is queued for background processing. The response contains an `event
 <CodeGroup>
 ```json 200 response
 {
-  "message": "Memory processing has been queued for background execution",
-  "status": "PENDING",
-  "event_id": "evt-uuid"
+  "event_id": "evt-uuid",
+  "status": "PENDING"
 }
 ```
 
@@ -83,3 +83,11 @@ The request is queued for background processing. The response contains an `event
 <Info>
 Poll the event status via `GET /v1/event/{event_id}/`. Status will be `SUCCEEDED` or `FAILED` once processing completes.
 </Info>
+
+<Info>
+Memories with `expiration_date` remain stored after they expire. Search and get-all hide them by default; pass `show_expired: true` to include them.
+</Info>
+
+<Info>
+Python uses `expiration_date`; TypeScript uses `expirationDate`.
+</Info>

docs/api-reference/memory/create-memory-export.mdx

@@ -4,4 +4,4 @@ description: "Submit an export job to create a structured memory export using a
 openapi: post /v1/exports/
 ---
 
-Submit a job to create a structured export of memories using a customizable Pydantic schema. This process may take some time to complete, especially if you're exporting a large number of memories. You can tailor the export by applying various filters (e.g., `user_id`, `agent_id`, `run_id`, or `session_id`) and by modifying the Pydantic schema to ensure the final data matches your exact needs.
+Submit a job to create a structured export of memories using a customizable Pydantic schema. This process may take some time to complete, especially if you're exporting a large number of memories. You can tailor the export by applying various filters (e.g., `user_id`, `agent_id`, `app_id`, or `run_id`) and by modifying the Pydantic schema to ensure the final data matches your exact needs.

docs/api-reference/memory/get-memories.mdx

@@ -4,7 +4,11 @@ description: "Retrieve memories with paginated results and advanced filtering us
 openapi: post /v3/memories/
 ---
 
-List memories scoped by filters with paginated results. Entity IDs (`user_id`, `agent_id`, `app_id`, `run_id`) **must** be passed inside the `filters` object — top-level entity IDs are rejected with 400.
+List memories scoped by filters with paginated results. Entity IDs (`user_id`, `agent_id`, `app_id`, `run_id`) **must** be passed inside the `filters` object: top-level entity IDs are rejected with 400.
+
+Expired memories are hidden by default. Pass `show_expired: true` to include memories whose `expiration_date` has passed.
+
+Python uses `show_expired`; TypeScript uses `showExpired`.
 
 The `filters` object supports complex logical operations (AND, OR, NOT) and comparison operators:
 
@@ -32,6 +36,7 @@ memories = client.get_all(
             }
         ]
     },
+    show_expired=False,
     page=1,
     page_size=50
 )
@@ -46,12 +51,14 @@ memories = client.get_all(
         {
             "id": "f4cbdb08-7062-4f3e-8eb2-9f5c80dfe64c",
             "memory": "Alex is planning a trip to San Francisco from July 1st to July 10th",
+            "expiration_date": null,
             "created_at": "2024-07-01T12:00:00Z",
             "updated_at": "2024-07-01T12:00:00Z"
         },
         {
             "id": "a2b8c3d4-5e6f-7g8h-9i0j-1k2l3m4n5o6p",
             "memory": "Alex prefers vegetarian restaurants",
+            "expiration_date": null,
             "created_at": "2024-07-05T15:30:00Z",
             "updated_at": "2024-07-05T15:30:00Z"
         }

docs/api-reference/memory/get-memory-export.mdx

@@ -4,4 +4,4 @@ description: "Retrieve the latest structured memory export after submitting an e
 openapi: post /v1/exports/get
 ---
 
-Retrieve the latest structured memory export after submitting an export job. You can filter the export by `user_id`, `run_id`, `session_id`, or `app_id` to get the most recent export matching your filters.
+Retrieve the latest structured memory export after submitting an export job. You can filter the export by `user_id`, `agent_id`, `app_id`, `run_id`, `created_at`, or `updated_at` to get the most recent export matching your filters.

docs/api-reference/memory/search-memories.mdx

@@ -4,9 +4,13 @@ description: "Search memories with hybrid retrieval (semantic + BM25 + entity ma
 openapi: post /v3/memories/search/
 ---
 
-Relevance-ranked hybrid search across stored memories. V3 uses multi-signal retrieval — semantic, BM25 keyword, and entity matching scored in parallel and fused. The returned `score` is a combined `[0, 1]` value.
+Relevance-ranked hybrid search across stored memories. V3 uses multi-signal retrieval: semantic, BM25 keyword, and entity matching scored in parallel and fused. The returned `score` is a combined `[0, 1]` value.
 
-Entity IDs (`user_id`, `agent_id`, `app_id`, `run_id`) **must** be passed inside the `filters` object — top-level entity IDs are rejected with 400. At least one entity ID is required.
+Entity IDs (`user_id`, `agent_id`, `app_id`, `run_id`) **must** be passed inside the `filters` object: top-level entity IDs are rejected with 400. At least one entity ID is required.
+
+Expired memories are hidden by default. Pass `show_expired: true` to include memories whose `expiration_date` has passed.
+
+Python uses `show_expired`; TypeScript uses `showExpired`.
 
 The `filters` object supports complex logical operations (AND, OR, NOT) and comparison operators:
 - `in`: Matches any of the values specified
@@ -20,16 +24,17 @@ The `filters` object supports complex logical operations (AND, OR, NOT) and comp
 
 ### Search parameter defaults
 
-| Parameter | V1/V2 | V3 |
-| --- | --- | --- |
-| `top_k` | Supported (default 10) | Supported (1-1000, default 10) |
-| `threshold` | No default | Default `0.1` (pass `0.0` to disable) |
-| `rerank` | Default `true` | Default `false` (pass `true` to enable) |
+| Parameter | Default |
+| --- | --- |
+| `top_k` | `10` (range 1–1000) |
+| `threshold` | `0.1` (pass `0.0` to disable) |
+| `rerank` | `false` (pass `true` to enable) |
 
 <CodeGroup>
 ```python Platform API Example
 related_memories = client.search(
     query="What are Alice's hobbies?",
+    show_expired=False,
     filters={
         "OR": [
             {
@@ -54,6 +59,7 @@ related_memories = client.search(
         "category": "hobbies"
       },
       "score": 0.82,
+      "expiration_date": null,
       "created_at": "2024-07-26T10:29:36.630547-07:00",
       "updated_at": null,
       "categories": ["hobbies"]

docs/api-reference/memory/update-memory.mdx

@@ -1,5 +1,14 @@
 ---
 title: 'Update Memory'
-description: "Update the content or metadata of a single memory by its unique ID using the PUT endpoint."
+description: "Update the content, metadata, timestamp, or expiration date of a single memory by its unique ID using the PUT endpoint."
 openapi: put /v1/memories/{memory_id}/
----
+---
+
+Use this endpoint to update mutable memory fields. To make a memory expire, set `expiration_date` to a `YYYY-MM-DD` date. To make it permanent again, send `expiration_date: null`.
+
+```python
+client.update("mem_123", expiration_date="2030-01-31")
+client.update("mem_123", expiration_date=None)
+```
+
+TypeScript uses `expirationDate`.

docs/api-reference/organization/remove-org-member.mdx

@@ -0,0 +1,5 @@
+---
+title: "Remove Organization Member"
+description: "Remove a member from an organization to revoke their access to its projects and resources."
+openapi: "delete /api/v1/orgs/organizations/{org_id}/members/"
+---

docs/api-reference/organization/update-org-member.mdx

@@ -0,0 +1,5 @@
+---
+title: "Update Organization Member"
+description: "Update an existing member's role within an organization to change their permissions and access level."
+openapi: "put /api/v1/orgs/organizations/{org_id}/members/"
+---

docs/api-reference/organizations-projects.mdx

@@ -14,7 +14,7 @@ Organizations and projects are **optional** features. You can use Mem0 without t
 
 ## Key Capabilities
 
-- **Multi-org/project Support**: Specify organization and project when initializing the Mem0 client to attribute API usage appropriately
+- **Multi-org/project Support**: Organization and project are resolved automatically from your API key via `/v1/ping/`: no org or project params are accepted by `MemoryClient.__init__`. Use a project-specific API key to target a particular project.
 - **Member Management**: Control access to data through organization and project membership
 - **Access Control**: Only members can access memories and data within their organization/project scope
 - **Team Isolation**: Maintain data separation between different teams and projects for secure collaboration
@@ -79,7 +79,7 @@ new_project = client.project.create(
 
 ### Update Project Settings
 
-Modify project configuration including custom instructions, categories, and language preferences:
+Modify project configuration including custom instructions, categories, language preferences, and memory decay:
 
 ```python
 # Update project with custom categories
@@ -98,6 +98,9 @@ client.project.update(
 # Use the input language for memory storage and retrieval
 client.project.update(multilingual=True)
 
+# Enable Memory Decay (boosts recently-accessed memories at search time)
+client.project.update(decay=True)
+
 # Update multiple settings at once
 client.project.update(
     custom_instructions="...",
@@ -111,7 +114,7 @@ client.project.update(
 
 #### Toggle Memory Decay
 
-`decay` is a per-project boolean that turns on [Memory Decay](/platform/features/memory-decay) — a search-time ranking bias that reinforces recently-accessed memories and gently dampens stale ones. The flag is `false` by default; set it via the same project-update endpoint:
+`decay` is a per-project boolean that turns on [Memory Decay](/platform/features/memory-decay): a search-time ranking bias that reinforces recently-accessed memories and gently dampens stale ones. The flag is `false` by default; set it via the same project-update endpoint:
 
 ```bash cURL
 curl -X PATCH https://api.mem0.ai/api/v1/orgs/organizations/$ORG_ID/projects/$PROJECT_ID/ \

docs/api-reference/project/remove-project-member.mdx

@@ -0,0 +1,5 @@
+---
+title: "Remove Project Member"
+description: "Remove a member from a project to revoke their access to its memories, configuration, and resources."
+openapi: "delete /api/v1/orgs/organizations/{org_id}/projects/{project_id}/members/"
+---

docs/api-reference/project/update-project-member.mdx

@@ -0,0 +1,5 @@
+---
+title: "Update Project Member"
+description: "Update an existing member's role within a project to change their permissions and access level."
+openapi: "put /api/v1/orgs/organizations/{org_id}/projects/{project_id}/members/"
+---

docs/api-reference/project/update-project.mdx

@@ -0,0 +1,5 @@
+---
+title: "Update Project"
+description: "Update a project's settings, including name, custom instructions, and other configuration options."
+openapi: "patch /api/v1/orgs/organizations/{org_id}/projects/{project_id}/"
+---

docs/changelog/highlights.mdx

@@ -4,16 +4,154 @@ description: "Major product launches, headline features, and milestones for Mem0
 mode: "wide"
 ---
 
+<Update label="2026-07-30" description="n8n and Zapier integrations">
+
+**Workflow Automation: Mem0 Memory in n8n and Zapier**
+
+Mem0 now plugs into two no-code automation platforms, so workflows that used to start from zero on every run can store durable facts and recall them later.
+
+- **n8n community node:** [`@mem0/n8n-nodes-mem0`](https://www.npmjs.com/package/@mem0/n8n-nodes-mem0) adds a **Mem0** node with a Memory resource covering Add, Search, Get, Get Many, Update, and Delete. Install it from **Settings → Community Nodes** on a self-hosted instance, then connect your API key once as a Mem0 API credential. See [n8n](/integrations/n8n).
+- **n8n AI Agent tool:** Attach the same node to an [AI Agent](https://docs.n8n.io/advanced-ai/) node and it becomes a tool the agent calls on its own, so it can decide when to remember and when to recall.
+- **Zapier app:** Add Memory, Search Memories, Get Memories, and Delete Memory actions let any of Zapier's thousands of apps write and read Mem0 context with no code and no server. See [Zapier](/integrations/zapier).
+- **One-time connection:** Both integrations authenticate with a single Mem0 API key and default to `https://api.mem0.ai`, with a configurable base URL for self-hosted deployments.
+
+<Note>
+  The Zapier app is not yet listed in Zapier's public App Directory. Email [support@mem0.ai](mailto:support@mem0.ai) for an invite link.
+</Note>
+
+</Update>
+
+<Update label="2026-07-13" description="TypeScript provider expansion">
+
+**TypeScript OSS SDK: 26 New Providers, Reranking, and Zero-Dependency Imports**
+
+TypeScript SDK v3.1.0 is the largest provider release for the OSS SDK so far, closing most of the remaining gap with the Python SDK. Python SDK v2.0.12 ships alongside it with fixes and security patches.
+
+- **17 new vector stores:** Pinecone, Weaviate, Milvus, Chroma, MongoDB, Elasticsearch, OpenSearch, Databricks, AWS Neptune Analytics, S3 Vectors, Azure MySQL, Google Vertex AI Vector Search, Turbopuffer, Upstash Vector, Valkey, Cassandra, and Baidu Mochow.
+- **5 new LLM providers:** AWS Bedrock, xAI Grok, Together, vLLM, and Sarvam.
+- **4 new embedding providers:** Vertex AI, HuggingFace, FastEmbed, and Together.
+- **Reranking in TypeScript:** Four rerankers (Cohere, ZeroEntropy, cross-encoder, and LLM-based) with per-search rerank via a `rerank` option on `search()`.
+- **Install only what you use:** Importing `mem0ai/oss` no longer pulls in any provider SDK. Provider packages are resolved lazily on first use, so an app that configures only OpenAI and Qdrant does not need the other provider SDKs installed.
+
+See [SDK & Tools](/changelog/sdk) for version details and PR links.
+
+</Update>
+
+<Update label="2026-06-27" description="SDK memory expiration">
+
+**SDK Memory Expiration: Expiring Memories Across Python and TypeScript**
+
+The latest SDK releases add first-class expiration controls to memory writes, updates, and reads, plus new TypeScript provider coverage for production deployments.
+
+- **Python client updates:** `MemoryClient.update()` and `AsyncMemoryClient.update()` now accept `expiration_date`, including `None` to clear an existing expiration.
+- **TypeScript client updates:** `AddMemoryOptions`, `update()`, and `Memory` now support `expirationDate`; `search()` and `getAll()` can include expired memories with `showExpired`.
+- **New TypeScript LLM providers:** `MiniMaxLLM` and `LiteLLM` are now available for OpenAI-compatible MiniMax and LiteLLM proxy deployments.
+- **PGVector deployment flexibility:** TypeScript PGVector config now supports `connectionString` and `ssl`, so apps can use a managed Postgres URI instead of separate connection fields.
+
+See [SDK & Tools](/changelog/sdk) for version details and PR links.
+
+</Update>
+
+<Update label="2026-06-25" description="Mem0 Plugin v0.2.11">
+
+**Mem0 Plugin: Shared Memory for Claude Code, Cursor, Codex, and Antigravity**
+
+The shared Mem0 editor plugin is current through v0.2.11:
+
+- **Automatic context injection:** File reads, bash errors, session resume prompts, and startup timelines can retrieve relevant memories automatically.
+- **Project and global scopes:** Project-scoped memories remain the default, while `global_search` supports team-wide recall across users and app scopes.
+- **Coding categories:** A 17-category coding taxonomy installs in the background and is cached per Mem0 account.
+- **Reliable capture:** Auto-capture, compaction summaries, session summaries, and metadata defaults keep memories scoped and readable.
+- **Editor correctness:** Telemetry now reports Claude Code, Cursor, Codex, and Antigravity separately with each editor's real plugin version.
+
+</Update>
+
+<Update label="2026-06-25" description="Antigravity Plugin v0.1.3">
+
+**Antigravity Plugin: Mem0 for Google Antigravity**
+
+Antigravity support in the shared Mem0 editor plugin family is current through v0.1.3:
+
+- **Self-contained plugin:** Includes its own plugin manifest, MCP config, hooks, shared scripts, and skills.
+- **AGENTS.md convention:** Uses Antigravity's `contextFileName: "AGENTS.md"` convention.
+- **Lifecycle hooks:** Wires session start, prompt recall, file-read context, memory-tool metadata enforcement, bash-error lookup, post-tool tracking, and stop summaries.
+- **Shared memory layer:** Reuses the Mem0 Platform MCP tools and the shared 16-skill command bundle.
+- **Better automatic recall:** v0.1.3 adds reranked injected context and clean `files_touched` metadata in session summaries.
+- **Telemetry correctness:** v0.1.2 reports Antigravity as `antigravity` with the plugin's own version.
+
+</Update>
+
+<Update label="2026-06-22" description="OpenCode Plugin v0.2.0">
+
+**OpenCode Plugin: Native SDK Memory Tools for OpenCode**
+
+`@mem0/opencode-plugin` adds memory to OpenCode and is current through v0.2.0:
+
+- **Native SDK tools:** Memory tools register through `@opencode-ai/plugin` and call the `mem0ai` SDK directly, so the plugin no longer depends on `mcp.mem0.ai`.
+- **Memory scopes:** Operations support `project`, `session`, and `global` scope, with `/mem0-scope` to change the default.
+- **Automatic context:** File-context injection, structured compaction summaries, and a recent-activity timeline surface relevant memories without manual recall.
+- **Auto-dream consolidation:** Gated consolidation merges duplicates, drops stale or sensitive entries, and rewrites vague memories.
+- **Skills load in place:** The `config` hook adds bundled skills to `skills.paths` instead of copying them into user config directories.
+- **Safety controls:** Blocks `MEMORY.md` writes and redacts secrets before storing memories.
+
+</Update>
+
+<Update label="2026-06-12" description="Pi Agent Plugin v0.1.2">
+
+**Pi Agent Plugin: Persistent Memory for Pi Agent**
+
+`@mem0/pi-agent-plugin` adds semantic memory to Pi Agent and has been updated through v0.1.2:
+
+- **Agent memory tool:** Registers `mem0_memory` for scoped search, add, get, delete, and delete-all operations.
+- **Slash commands:** Adds `/mem0-remember`, `/mem0-search`, `/mem0-forget`, `/mem0-tour`, `/mem0-dream`, `/mem0-pin`, `/mem0-scope`, and `/mem0-status`.
+- **Auto-capture:** Stores user and assistant memories after agent turns.
+- **Dream consolidation:** Merges duplicates, resolves contradictions, and prunes stale memories behind session, time, and memory-count gates.
+- **Project scoping:** Uses git-root detection for stable `app_id` values across monorepos.
+- **Relevant command results:** v0.1.2 adds visible command feedback and thresholded, reranked search for search, forget, and pin commands.
+
+</Update>
+
+<Update label="2026-06-12" description="OpenClaw v1.0.13">
+
+**OpenClaw Plugin: Current Memory Backend for OpenClaw**
+
+`@mem0/openclaw-mem0` is current through v1.0.13, with the original production-ready memory backend plus newer setup, security, and runtime work:
+
+- **Skills-based memory architecture:** Triage, recall, and dream skills handle extraction, recall, consolidation, and tool guidance.
+- **Chat and CLI setup:** Supports chat-based platform setup, `openclaw mem0 init`, direct API keys, email OTP, autonomous agent setup, and OSS onboarding.
+- **Platform and OSS modes:** Works with Mem0 Platform or self-hosted OSS providers including OpenAI, Anthropic, Ollama, Qdrant, and PGVector.
+- **Agent-friendly CLI:** All 16 CLI commands support `--json` for machine-driven setup and diagnostics.
+- **Runtime integration:** Exposes OpenClaw memory capability APIs for search manager and backend config status.
+- **Security and compliance:** Added path containment checks, sensitive config metadata, dependency overrides, telemetry hashing, and metadata-only registration safety.
+
+</Update>
+
+<Update label="2026-06-10" description="Vercel AI SDK Provider v3.0.0">
+
+**Vercel AI SDK Provider: Memory-Augmented Generation for AI SDK v6**
+
+The Vercel AI SDK provider moved to the v6 provider contract and Mem0 v3 APIs:
+
+- **AI SDK v6 support:** Migrated to `LanguageModelV3` / `ProviderV3`, including v3 stream lifecycle events and content arrays.
+- **Mem0 v3 API support:** Memory writes and searches now use `/v3/memories/add/` and `/v3/memories/search/`.
+- **Mem0 sources in responses:** `generateText` and `streamText` responses include memories as sources with `providerMetadata.mem0.memories`.
+- **Safer prompt handling:** Prompts are cloned before memory injection, avoiding caller-side mutation.
+- **Async storage fix:** `addMemories` is awaited so generated memories are not silently dropped.
+- **Raw memory utilities:** Exports `searchMemories`, `retrieveMemories`, `getMemories`, and `addMemories` for apps that need direct memory control.
+- **Deployment controls:** Per-request `mem0ApiKey` and `host` support Mem0 Platform, custom API keys, and self-hosted API endpoints.
+
+</Update>
+
 <Update label="2026-05-13" description="Temporal Reasoning for Mem0 Platform v3">
 
-**Temporal Reasoning — Time-Aware Retrieval for Platform v3**
+**Temporal Reasoning: Time-Aware Retrieval for Platform v3**
 
 Mem0 Platform v3 can now interpret time-aware memories and queries so assistants retrieve the right information for questions about the past, upcoming plans, and current state.
 
-- **Time-aware search intent** — Queries like `last week`, `upcoming`, `right now`, and `as of March 2025` return contextually appropriate results automatically
-- **Enabled by default** — No per-request toggle required for v3 writes or searches
-- **Anchored relative queries** — `reference_date` anchors relative search phrases for tests, backfills, and reproducible demos
-- **Normal response shape** — Temporal reasoning affects ranking while preserving existing client response patterns
+- **Search intent parsing:** Queries like `last week`, `upcoming`, `right now`, and `as of March 2025` now resolve against memory timestamps automatically.
+- **Default v3 behavior:** No per-request toggle is needed for v3 writes or searches.
+- **Deterministic testing:** Pass `reference_date` to anchor relative phrases in tests, backfills, and demos.
+- **Stable API shape:** Temporal reasoning changes ranking, not the client response contract.
 
 See [Temporal Reasoning](/platform/features/temporal-reasoning) for usage details.
 
@@ -21,11 +159,11 @@ See [Temporal Reasoning](/platform/features/temporal-reasoning) for usage detail
 
 <Update label="2026-05-08" description="Memory Decay">
 
-**Memory Decay — Recently-Used Memories Surface Higher, Automatically**
+**Memory Decay: Recently-Used Memories Surface Higher**
 
 Per-project search-time ranking bias that boosts recently-touched memories and gently dampens stale ones. Off by default; opt in per project via the `decay` field on the project endpoint, or via `client.project.update(decay=True)` in the SDKs (Python `v2.0.2` / TypeScript `v3.0.3`).
 
-- **Soft bias, never a filter.** The scaling factor stays in `0.3×–1.5×`. Decay can reorder candidates but never zeros them out — anything that surfaced before decay can still surface after.
+- **Soft bias, never a filter.** The scaling factor stays in `0.3×–1.5×`. Decay can reorder candidates but never removes them; anything that surfaced before decay can still surface after.
 - **Reinforcement loop.** Every memory returned in a search has its access history updated, so frequently-used facts naturally float to the top over time.
 - **Public score still clamped to `[0, 1]`.** Existing API contract preserved; no client-side changes needed.
 - **v3 search only**, fully reversible. See [Memory Decay docs](/platform/features/memory-decay).
@@ -34,18 +172,18 @@ Per-project search-time ranking bias that boosts recently-touched memories and g
 
 <Update label="2026-04-14" description="Mem0 SDK v2.0.0 / v3.0.0">
 
-**New Memory Algorithm — State-of-the-Art Accuracy at ~3-4x Lower Cost**
+**New Memory Algorithm: State-of-the-Art Accuracy at ~3-4x Lower Cost**
 
 Ground-up rewrite of the memory pipeline with 20+ point benchmark improvements:
 
-- **LoCoMo:** 71.4 → **91.6** (+20) — multi-turn conversation recall
-- **LongMemEval:** 67.8 → **93.4** (+26) — long-term memory across sessions
-- **BEAM (1M tokens):** **64.1** — production-scale memory evaluation
-- **Agent memories are first-class** — Previous algorithm: 46% on assistant recall. New: **100%**
-- **Temporal reasoning works** — "Where did I live before SF?" Previous: 51%. New: **93%**
-- **~3-4x fewer tokens** — Under 7K tokens per retrieval vs 25K+ for full-context approaches
-- **ADD-only extraction** — Memories accumulate; nothing is overwritten or deleted
-- **Hybrid retrieval** — Semantic + BM25 keyword + entity boost, scored in parallel
+- **LoCoMo:** 71.4 → **91.6** (+20) for multi-turn conversation recall.
+- **LongMemEval:** 67.8 → **93.4** (+26) for long-term memory across sessions.
+- **BEAM (1M tokens):** **64.1** on production-scale memory evaluation.
+- **Agent memories:** Assistant recall moves from 46% to **100%**.
+- **Temporal reasoning:** "Where did I live before SF?" improves from 51% to **93%**.
+- **Lower token use:** Retrieval stays under 7K tokens versus 25K+ for full-context approaches.
+- **ADD-only extraction:** Memories accumulate; nothing is overwritten or deleted.
+- **Hybrid retrieval:** Semantic search, BM25 keyword search, and entity boost are scored in parallel.
 - **Graph memory (built-in)**: entities extracted, embedded, and linked across memories, with no external graph store required
 
 Breaking changes: external graph stores removed from OSS (replaced by built-in graph memory), `search()` defaults changed, deprecated params removed. See [migration guide](/migration/oss-v2-to-v3).
@@ -54,56 +192,28 @@ Breaking changes: external graph stores removed from OSS (replaced by built-in g
 
 <Update label="2026-04-06" description="Mem0 Skill Graph">
 
-**Mem0 Skill Graph — In-Context Documentation for AI Agents**
+**Mem0 Skill Graph: In-Context Documentation for AI Agents**
 
-AI coding agents in Claude Code, Cursor, and Codex can now access Mem0 knowledge directly in their workflow — no doc searching required. Three interconnected skills launched:
+AI coding agents in Claude Code, Cursor, and Codex can now access Mem0 knowledge directly in their workflow without leaving the editor. Three interconnected skills launched:
 
-- **mem0 Core Skill** — Complete Python and TypeScript SDK reference, REST API patterns, and integration guides for LangChain, CrewAI, Autogen, and more
-- **mem0-cli Skill** — Terminal command reference, configuration walkthroughs, and CI/CD recipes
-- **mem0-vercel-ai-sdk Skill** — Vercel AI SDK provider API, memory-augmented generation patterns, and multi-provider setup
+- **mem0 Core Skill:** Python and TypeScript SDK reference, REST API patterns, and integration guides for LangChain, CrewAI, Autogen, and more.
+- **mem0-cli Skill:** Terminal command reference, configuration walkthroughs, and CI/CD recipes.
+- **mem0-vercel-ai-sdk Skill:** Vercel AI SDK provider API, memory-augmented generation patterns, and multi-provider setup.
 
 </Update>
 
 <Update label="2026-04-06" description="Mem0 CLI v0.2.2">
 
-**Official Mem0 CLI — Now on PyPI and npm**
+**Official Mem0 CLI: Now on PyPI and npm**
 
 A full-featured command-line interface for Mem0, available in both Python and Node.js:
 
 - **Install:** `pip install mem0-cli` or `npm install -g @mem0/cli`
-- **Full command suite** — `add`, `search`, `list`, `get`, `update`, `delete`, `import`, `config`, `init`, `status`, `entity`, `event`
-- **Interactive setup** — `mem0 init` with email verification or direct API key entry
-- **Works everywhere** — Platform (Mem0 Cloud) and self-hosted OSS modes
-- **Scriptable** — `--json` flag for CI/CD pipelines and automation
-- **Dual SDK** — Same commands, same experience across Python and Node.js
-
-</Update>
-
-<Update label="2026-04-06" description="OpenClaw v1.0.4">
-
-**OpenClaw Plugin — Production-Ready**
-
-The OpenClaw Mem0 plugin went from initial release to production-ready in one week (v1.0.0 → v1.0.4):
-
-- **Skills-based memory architecture** — New extraction pipeline with skill-loader, batched extraction, and domain-aware memory triage
-- **Dream gate** — Automatic memory consolidation during idle periods for higher-quality long-term recall
-- **Interactive CLI** — `openclaw mem0 init`, `status`, `config`, `import`, and `event` commands
-- **Unified tool naming** — `memory_add` and `memory_delete` replace 4 legacy tools, matching the platform API
-- **Security hardened** — Path traversal protection, pinned dependencies, 329 tests across 10 files
-
-</Update>
-
-<Update label="2026-04-02" description="Mem0 Plugin for AI Editors">
-
-**Mem0 Plugin for Claude Code, Cursor, and Codex**
-
-Launched a unified Mem0 plugin across three major AI development environments — Claude Code and Cursor first (March 25), then Codex (April 2):
-
-- **9 MCP memory tools** — add, search, get, update, delete, bulk delete, entity management via `mcp.mem0.ai`
-- **Lifecycle hooks** — Automatic memory capture at session start, context compaction, task completion, and session end
-- **Cloud MCP server** — Managed endpoint replaces local MCP and Smithery setup
-- **Streamable HTTP transport** — New MCP transport protocol for real-time streaming
-- **Codex-specific skill** — Dedicated skill in `mem0-plugin/skills/mem0-codex` for Codex workflows
+- **Full command suite:** `add`, `search`, `list`, `get`, `update`, `delete`, `import`, `config`, `init`, `status`, `entity`, `event`.
+- **Interactive setup:** `mem0 init` supports email verification and direct API key entry.
+- **Runtime coverage:** Works with Mem0 Platform and self-hosted OSS modes.
+- **Automation support:** Use `--json` for CI/CD pipelines and agent workflows.
+- **Dual implementation:** Same commands and behavior across Python and Node.js.
 
 </Update>
 
@@ -113,11 +223,11 @@ Launched a unified Mem0 plugin across three major AI development environments
 
 Major expansion of the provider ecosystem:
 
-- **Apache AGE** — New graph store support, bringing the total to 4 graph store backends (Neo4j, Memgraph, Kuzu, Apache AGE)
-- **Turbopuffer** — New vector database provider for Python SDK
-- **MiniMax** — New LLM provider with dedicated AWS Bedrock support
-- **pgvector for Node.js** — PostgreSQL vector support added to the TypeScript OSS SDK
-- **Reasoning models** — `reasoning_effort` parameter for OpenAI o1/o3-style models
+- **Apache AGE:** New graph store support, bringing the total to 4 graph store backends (Neo4j, Memgraph, Kuzu, Apache AGE). **Note:** All external graph store backends (Neo4j, Memgraph, Kuzu, Apache AGE) were subsequently removed in v2.0.0 (2026-04-14). Graph memory is now built-in entity linking with no external graph store required; see the [v2.0.0 entry above](#mem0-sdk-v2-0-0-v3-0-0).
+- **Turbopuffer:** New vector database provider for Python SDK.
+- **MiniMax:** New LLM provider with dedicated AWS Bedrock support.
+- **pgvector for Node.js:** PostgreSQL vector support added to the TypeScript OSS SDK.
+- **Reasoning models:** `reasoning_effort` parameter for OpenAI o1/o3-style models.
 
 </Update>
 
@@ -125,6 +235,6 @@ Major expansion of the provider ecosystem:
 
 **Mem0 Platform Skill on skills.sh**
 
-First skill launch — a dedicated Mem0 skill providing platform API reference, quickstart patterns, and integration examples directly inside agent sessions. Available on [skills.sh](https://skills.sh) for any compatible AI coding agent.
+First skill launch: a dedicated Mem0 skill providing platform API reference, quickstart patterns, and integration examples directly inside agent sessions. Available on [skills.sh](https://skills.sh) for any compatible AI coding agent.
 
 </Update>

docs/changelog/openclaw.mdx

@@ -1,336 +0,0 @@
----
-title: "OpenClaw"
-description: "Release notes for the OpenClaw plugin and agent harness."
-mode: "wide"
----
-
-<Update label="2026-06-12" description="v1.0.13">
-
-**Fixes:**
-- **Custom categories payload:** `customCategories` (a `Record<string, string>` map) is now converted via the new `customCategoryMapToList()` helper into the `Array<Record<string, string>>` shape the Mem0 SDK expects on `add` calls — previously the raw object was passed as `custom_categories` and silently ignored ([#5345](https://github.com/mem0ai/mem0/pull/5345))
-- **Skip runtime setup during metadata registration:** `register()` now detects `registrationMode === "cli-metadata"`, registers only the CLI commands, and returns early — avoiding backend initialization, service/tool registration, and hook installation during OpenClaw's metadata-only registration pass ([#5383](https://github.com/mem0ai/mem0/pull/5383))
-
-**Security:**
-- Bumped `mem0ai` from `3.0.3` to `3.0.7` (latest Node SDK) — includes the transitive axios CVE remediation shipped in `3.0.6` ([#5460](https://github.com/mem0ai/mem0/pull/5460))
-- Added pnpm override `uuid@<11.1.1` → `>=11.1.1` to resolve an open MEDIUM Dependabot alert ([#5489](https://github.com/mem0ai/mem0/pull/5489))
-
-**Improvements:**
-- **Repo consolidation:** Plugin moved from repo-root `openclaw/` to `integrations/openclaw/`; `package.json` `repository.directory` updated to match so npm provenance links to the correct subdirectory ([#5491](https://github.com/mem0ai/mem0/pull/5491))
-
-**Tests:**
-- Added `customCategoryMapToList` unit tests and a `PlatformProvider` test asserting `custom_categories` is passed to the Mem0 SDK as a list ([#5345](https://github.com/mem0ai/mem0/pull/5345))
-- Added a regression test asserting `cli-metadata` registration registers only CLI commands and triggers no runtime side effects ([#5383](https://github.com/mem0ai/mem0/pull/5383))
-
-</Update>
-
-<Update label="2026-06-02" description="v1.0.12">
-
-**Docs:**
-- **Agent Mode onboarding:** README now documents an autonomous setup path for AI agents — `mem0 init --agent --json` mints an evaluation Mem0 API key with no email, OTP, or browser and exports it as `MEM0_API_KEY` for `openclaw mem0 init`; a human owner can later run `mem0 init --email <email>` to claim ownership without disrupting the agent ([#5123](https://github.com/mem0ai/mem0/pull/5123))
-
-**Security:**
-- Added pnpm overrides to remediate advisories in transitive dependencies: `langsmith@<0.6.0` → `^0.6.0`, `picomatch@<2.3.2` → `^2.3.2`, `vite` → `^8.0.5`, and `@qdrant/js-client-rest` → `^1.18.0` ([#5294](https://github.com/mem0ai/mem0/pull/5294))
-
-**Dependencies:**
-- Bumped `mem0ai` from `3.0.2` to `3.0.3` ([#5212](https://github.com/mem0ai/mem0/pull/5212))
-- Bumped dev dependencies `@vitest/coverage-v8` and `vitest` from `^4.0.18` to `^4.1.7`; added `vite@^8.0.5` and `@qdrant/js-client-rest@^1.18.0` ([#5294](https://github.com/mem0ai/mem0/pull/5294))
-
-</Update>
-
-<Update label="2026-04-29" description="v1.0.11">
-
-**New Features:**
-- **Skills-mode auto-setup:** `enableSkillsConfig()` now runs automatically after onboarding — enables triage, recall (with reranking + keyword search), and dream consolidation with `tools.profile = "full"` and disables the built-in session-memory hook to avoid conflicts
-- **Memory runtime capability:** Plugin now exposes `runtime.getMemorySearchManager()` and `resolveMemoryBackendConfig()` on the registered memory capability, enabling OpenClaw gateway to query memory status and backend config directly
-- **Dimension-aware collections:** OSS wizard detects embedder dimension changes and creates a new collection (`mem0_<dims>d`) automatically, with a warning about old memories being inaccessible under the new embedder
-- **Tool documentation in skills:** Both `memory-triage` and `memory-dream` SKILL.md files now include full tool reference sections listing all available tools with parameters
-
-**Improvements:**
-- **Auto-capture and auto-recall default to enabled:** `autoCapture` and `autoRecall` now default to `true` (was `false`). Manifest descriptions updated accordingly. Ignored in skills mode
-- **`memory_update` over delete+add:** Skills now prefer `memory_update` for in-place edits — atomic and preserves edit history. Consolidation pattern updated: update best memory, delete redundant ones
-- **Search threshold lowered:** Default `searchThreshold` reduced from `0.5` to `0.1` for broader recall. Removed hardcoded `0.6` recall-specific override — all searches now use the configured threshold
-- **Embedder dimension propagation:** Vector store config auto-resolves dimensions from embedder config when not explicitly set. Syncs `dimension` and `embeddingModelDims` fields for Qdrant/PGVector compatibility
-- **Config file write safety:** `writeFullConfig()` now re-reads and deep-merges the `plugins` section before writing, preserving `installs` and `slots` written by the OpenClaw gateway
-- **Additional embedder models:** Added `mxbai-embed-large` (1024), `all-minilm` (384), and `snowflake-arctic-embed` (1024) to known embedder dimensions
-
-**Security:**
-- Bumped `protobufjs` to `>=7.5.5` via pnpm overrides (GHSA-xq3m-2v4x-88gg) ([#5012](https://github.com/mem0ai/mem0/pull/5012))
-
-**Fixes:**
-- Moved `bootstrapTelemetryFlag()` and removed `ensureInstallRecord()` from module-level side effects — both now run inside `register()` to avoid crashes when loaded outside OpenClaw gateway
-- Fixed OSS history DB path resolution: absolute paths no longer passed through `resolvePath()`, preventing double-prefix bugs
-- Manifest `providerAuthEnvVars` replaced with spec-compliant `setup.providers` format using `id` + `envVars`
-
-**Dependencies:**
-- Bumped `mem0ai` from `3.0.1` to `3.0.2`
-- Bumped `pluginApi` and `minGatewayVersion` compat to `>=2026.4.24`
-
-</Update>
-
-<Update label="2026-04-23" description="v1.0.10">
-
-**Security:**
-- Telemetry `distinct_id` now uses SHA-256 instead of MD5 — prevents rainbow-table reversal of API key hashes
-- User email is now SHA-256 hashed before sending as `distinct_id` — no PII in telemetry payloads
-- Declared PostHog telemetry endpoint (`us.i.posthog.com`) in `providerEndpoints`
-
-**Fixes:**
-- Fixed version-pinned install records preventing plugin updates. `ensureInstallRecord()` now detects semver-pinned specs (e.g. `@mem0/openclaw-mem0@1.0.7`) and rewrites them to `@latest` or `clawhub:` prefix so `openclaw plugins update` resolves to the newest release
-- Fixed `searchThreshold` default inconsistency: standardized to `0.3` across docs, README, and manifest
-- `PLUGIN_VERSION` now injected at build time via tsup `define` from `package.json` — no more hardcoded version strings
-
-**Manifest Compliance:**
-- Removed non-spec fields: `requiredEnvVars`, `dataLocations`, `privacy`, `setup` (with `externalEndpoints`, `providers`, `requiresRuntime`, `postInstallHint`)
-- Replaced `setup.externalEndpoints` with spec-compliant `providerEndpoints` using `endpointClass` + `hosts` format
-- Env var declarations now rely solely on `providerAuthEnvVars` (already spec-compliant)
-
-**Docs:**
-- Fixed `openclaw plugins update` command: uses plugin ID (`openclaw-mem0`), not npm package name (`@mem0/openclaw-mem0`)
-- Added update section to README
-- Removed redundant "Key Features" and "Conclusion" sections from integration docs
-
-</Update>
-
-<Update label="2026-04-22" description="v1.0.9">
-
-**Security & Compliance:**
-- Added top-level `requiredEnvVars` to plugin manifest, declaring env vars per mode (platform, OSS OpenAI, OSS Anthropic, OSS Ollama). Fixes ClaHub scanner "required env vars: none" mismatch
-- Added `sensitive: true` and descriptions to `apiKey` and `userEmail` in `configSchema` — previously only declared in `uiHints`
-- Added `default: false` with descriptions to `autoCapture` and `autoRecall` in `configSchema` so scanner can confirm opt-in defaults
-- Added `dataLocations` field to manifest declaring all persistence paths (config, vectorStore, historyDb, dreamState)
-- Added `privacy` field to manifest documenting data flow for platform vs open-source mode and credential storage guidance
-- Added `externalEndpoints` to `setup` section declaring api.mem0.ai and app.mem0.ai with purpose and requirement context
-
-**Tests:**
-- Replaced direct `process.env` access in `tests/cli-commands.test.ts` and `tests/fs-safe.test.ts` with `vi.stubEnv`/`vi.unstubAllEnvs`. Fixes ClaHub static analysis flag for "environment variable access combined with network send"
-- 421 tests across 15 test files
-
-</Update>
-
-<Update label="2026-04-21" description="v1.0.8">
-
-**New Features:**
-- **OSS Onboarding Wizard:** New guided 4-step interactive setup for open-source mode — walks through LLM provider, embedding provider, vector store, and user ID selection with prefilled defaults
-- **Agent-Friendly CLI:** Added `--json` flag to all 16 CLI commands for machine-readable output. Agents can call `openclaw mem0 help --json` to discover every command and flag
-- **Non-Interactive OSS Setup:** Added `--mode open-source` with `--oss-llm`, `--oss-embedder`, `--oss-vector` flags for fully automated OSS configuration without prompts
-- **JSON Helpers Module:** New `cli/json-helpers.ts` with `jsonOut`, `jsonErr`, and `redactSecrets` utilities for consistent structured output
-
-**Improvements:**
-- **Init Flow Redesigned:** Replaced 3-option flat menu with 2-level structure: Platform (email login or API key) and Open Source (guided wizard)
-- **Provider Selection:** LLM providers: OpenAI, Ollama, Anthropic. Embedding providers: OpenAI, Ollama. Vector stores: Qdrant, PGVector
-- **Input Prefill:** All prompts with defaults (base URL, user ID) now prefill the input field instead of showing defaults in brackets
-- **Smart Reuse:** When LLM and embedder use the same provider, API key and base URL are automatically reused from the LLM step
-- **Default Model:** Updated default LLM model to `gpt-5-mini`
-- **Manifest Compliance:** Removed undocumented fields, aligned env var declarations between SKILL.md and manifest, fixed `configSchema.required` for clean installs
-
-**Tests:**
-- 404 tests across 15 test files (+3 new: `json-helpers.test.ts`, `oss-wizard.test.ts`, `cli-commands.test.ts`)
-
-</Update>
-
-<Update label="2026-04-20" description="v1.0.7">
-
-**New Features:**
-- **Chat-Based Setup:** Added chat-based Platform setup flow — users can now configure the plugin conversationally instead of editing config files manually
-- **Installation Docs Rewrite:** Rewrote README and integration docs with chat-first setup, numbered manual steps.
-
-**Improvements:**
-- **SDK Upgrade:** Bumped `mem0ai` dependency to 3.0.1 for V3 API compatibility
-- **Config Cleanup:** Dropped deprecated `orgId`, `projectId`, `enableGraph` config options; updated CLI prompts ([#4734](https://github.com/mem0ai/mem0/pull/4734), [#4764](https://github.com/mem0ai/mem0/pull/4764))
-- **Noise Filtering:** Expanded noise patterns in memory add tool; handle leading text in JSON extraction
-
-</Update>
-
-<Update label="2026-04-11" description="v1.0.6">
-
-**Bug Fixes:**
-- **Telemetry:** Replaced shared `"anonymous-openclaw"` fallback with a persistent per-machine random hash (`openclaw-anon-<uuid>`), so anonymous plugin users are counted individually in PostHog ([#4790](https://github.com/mem0ai/mem0/pull/4790))
-- **Telemetry:** Added PostHog `$identify` event on first authenticated run to stitch anonymous history onto the authenticated profile ([#4790](https://github.com/mem0ai/mem0/pull/4790))
-- **Telemetry:** Fixed event loss on short-lived CLI invocations — added `beforeExit` handler to flush queued events before the process exits ([#4790](https://github.com/mem0ai/mem0/pull/4790))
-- **Telemetry:** Added lazy `/v1/ping/` email resolution so users who configure API key outside `mem0 init` show as their email in PostHog, not an md5 hash ([#4790](https://github.com/mem0ai/mem0/pull/4790))
-- **Telemetry:** Unified CLI event prefix from `openclaw.<cmd>` to `openclaw.cli.<cmd>` on the needsSetup branch to match the authenticated branch ([#4790](https://github.com/mem0ai/mem0/pull/4790))
-
-**Improvements:**
-- **API:** Added `source: "OPENCLAW"` to all provider calls (`add`, `search`, `getAll`) across tools, CLI commands, recall, and the OSS backend adapter ([#4790](https://github.com/mem0ai/mem0/pull/4790))
-
-</Update>
-
-<Update label="2026-04-07" description="v1.0.5">
-
-**Bug Fixes:**
-- **Init interactive choice bug**: Fixed number selection in `openclaw mem0 init` — entering 1/2/3 now correctly selects the corresponding option (was broken by readline prefill concatenating with user input)
-- **OSS pgvector crash** ([#4727](https://github.com/mem0ai/mem0/issues/4727)): Fixed "Client has already been connected" cascade when using pgvector in OSS mode. The warmup call swallowed errors leaving a half-initialized pg client; concurrent recall/capture then all hit `client.connect()` on the same client. Fix: let warmup errors propagate (so `initPromise` resets and retries with a fresh Memory + fresh pg client) and build fresh config objects per attempt instead of mutating shared state.
-
-**Removed:**
-- **`orgId` / `projectId` config parameters**: Removed from config schema, CLI (`config show/get/set`), init display, and providers. The API key is project-scoped, so separate org/project IDs are unnecessary and could cause access errors if mismatched.
-- **`enableGraph` config parameter**: Removed from all config surfaces, providers, backend, and tools. Graph memory is being deprecated — removing the flag avoids unnecessary exposure.
-
-</Update>
-
-<Update label="2026-04-04" description="v1.0.4">
-
-**New Features:**
-- **Interactive init flow**: `openclaw mem0 init` with interactive menu (email verification or direct API key). Non-interactive modes: `--api-key`, `--email`, `--email --code`
-- **`memory_add` tool**: Replaces `memory_store` — name now matches `mem0` CLI and platform API
-- **`memory_delete` tool**: Unified delete — single ID, search-then-delete, bulk, entity cascade. Replaces `memory_forget` and `memory_delete_all`
-- **CLI subcommands**: `openclaw mem0 init`, `openclaw mem0 status`, `openclaw mem0 config show`, `openclaw mem0 config set`
-- **`import` CLI command**: Bulk-import memories from a JSON file with `--user-id` and `--agent-id` overrides
-- **`event list` / `event status` CLI commands**: Monitor background processing events
-- **`fs-safe.ts` module**: Isolated filesystem wrappers in a separate entry point
-- **`backend/` module**: `PlatformBackend` with direct HTTP API access for CLI commands
-- **Plugin manifest**: Added `contracts.tools`, `configSchema`, and `uiHints` to `openclaw.plugin.json`
-- **Test suite**: 329 tests across 10 test files
-
-**Changes:**
-- **Modular architecture**: Extracted tools into `tools/` directory (6 files) and CLI into `cli/commands.ts`
-- **Code splitting**: tsup builds with `splitting: true` and two entry points
-- **Skills updated**: All SKILL.md files reference new tool names (`memory_add`, `memory_delete`)
-- **Auto-recall timeout**: Recall wrapped in 8-second `Promise.race`
-- **Auto-capture fire-and-forget**: `provider.add()` runs in background via `.then()/.catch()`
-- **Auto-capture minimum content gate**: Skips extraction when total user content is fewer than 50 chars
-
-**Removed:**
-- `memory_store` tool — replaced by `memory_add`
-- `memory_forget` tool — replaced by `memory_delete`
-- `memory_delete_all` tool — merged into `memory_delete`
-- `memory_history` tool and `history` CLI command — deprecated
-
-</Update>
-
-<Update label="2026-04-03" description="v1.0.3">
-
-**Bug Fixes:**
-- **Security**: Added `safePath()` containment helper to `readSkillFile` and `readDomainOverlay` in `skill-loader.ts` — prevents directory traversal
-- **Noise filter**: Reverted incorrect `After-Compaction` regex rename back to `Post-Compaction`
-
-**Changes:**
-- **Supply-chain hardening**: Pinned `mem0ai` dependency to exact `2.3.0` (was `^2.3.0`)
-
-**Tests:**
-- 12 new tests covering `safePath`, `readSkillFile`, `readDomainOverlay`, and `loadSkill` with traversal inputs
-
-</Update>
-
-<Update label="2026-04-02" description="v1.0.2">
-
-**Bug Fixes:**
-- **Security**: Removed `resolveEnvVars()` and `resolveEnvVarsDeep()` from `config.ts` — plugin-side env resolution was redundant and triggered static analysis warnings ([#4676](https://github.com/mem0ai/mem0/pull/4676))
-
-</Update>
-
-<Update label="2026-04-02" description="v1.0.1">
-
-**New Features:**
-- **CD workflow**: Added continuous deployment workflow with OIDC trusted publishing ([#4672](https://github.com/mem0ai/mem0/pull/4672))
-- **Plugin configuration manifest**: Added `compat` and `build` metadata to `package.json` ([#4667](https://github.com/mem0ai/mem0/pull/4667))
-- **LICENSE**: Added Apache-2.0 license file ([#4667](https://github.com/mem0ai/mem0/pull/4667))
-
-**Bug Fixes:**
-- **Dream gate**: Fixed cheap-first ordering, session isolation, and verified completion ([#4666](https://github.com/mem0ai/mem0/pull/4666))
-- **Graceful startup**: Plugin now starts gracefully when no API key is configured ([#4669](https://github.com/mem0ai/mem0/pull/4669))
-
-</Update>
-
-<Update label="2026-04-01" description="v1.0.0">
-
-**New Features:**
-- **Skills-based memory architecture**: New skill-loader and skill-based extraction pipeline with batched extraction ([#4624](https://github.com/mem0ai/mem0/pull/4624))
-- **Dream gate**: Memory consolidation and dream-cycle processing during idle periods
-- **Enhanced recall**: New `recall.ts` module with improved recall logic and skill-aware retrieval
-- **Memory triage skill**: Domain-aware memory triage with companion domain support and recall protocol
-- **Memory dream skill**: Skill for memory consolidation during idle periods
-- **Plugin configuration**: Added `openclaw.plugin.json` manifest and `scripts/configure.py` setup helper
-
-**Changes:**
-- Extraction pipeline refactored to use skills-based architecture for more contextual and higher quality memory capture
-
-</Update>
-
-<Update label="2026-03-26" description="v0.4.1">
-
-**New Features:**
-- **Improved extraction quality**: Enhanced noise filtering, deduplication, and better extraction instructions
-
-**Bug Fixes:**
-- **Credential detection**: Improved detection of credentials, API keys, and secrets in extraction instructions (#4552)
-- **Standalone timestamps**: Prevented extraction of standalone timestamps as memories (#4550)
-
-</Update>
-
-<Update label="2026-03-16" description="v0.4.0">
-
-**New Features:**
-- **Non-interactive trigger filtering**: Skips recall and capture for `cron`, `heartbeat`, `automation`, and `schedule` triggers
-- **Subagent hallucination prevention**: Detects ephemeral subagent sessions and routes recall to parent namespace
-- **Dynamic recall thresholding**: Memories scoring less than 50% of top result are dropped
-- **SQLite resilience**: Init error recovery with automatic retry for OSS mode
-- **`disableHistory` config option**: New `oss.disableHistory` flag
-- 78 unit tests covering filtering, isolation, trigger filtering, subagent detection, and SQLite resilience
-
-**Changes:**
-- Auto-recall threshold raised from 0.5 to 0.6 for stricter precision
-- Recall candidate pool increased to `topK * 2` for better filtering headroom
-- Relaxed extraction instructions: related facts kept together to preserve context
-
-**Bug Fixes:**
-- **Concurrent session race condition**: Lifecycle hooks now use `ctx.sessionKey` directly instead of a shared mutable variable
-
-</Update>
-
-<Update label="2026-03-12" description="v0.3.1">
-
-**New Features:**
-- **Message filtering pipeline**: Multi-stage noise removal before extraction
-- **Broad recall for new sessions**: Short or new-session prompts trigger secondary broad search
-- **Client-side threshold filtering**: Safety net that drops low-relevance results
-- **Temporal anchoring**: Extraction instructions now include current date
-- 55 unit tests covering filtering and isolation helpers
-
-**Changes:**
-- Extraction window expanded from last 10 to last 20 messages
-- Rewritten custom extraction instructions for conciseness and deduplication
-- Refactored monolithic `index.ts` (1772 lines) into 6 focused modules
-
-</Update>
-
-<Update label="2026-03-10" description="v0.3.0">
-
-**Bug Fixes:**
-- Updated `mem0ai` dependency with sqlite3 to better-sqlite3 migration (#4270)
-
-</Update>
-
-<Update label="2026-03-09" description="v0.2.0">
-
-**New Features:**
-- Per-agent memory isolation for multi-agent setups via `agentId`
-- "Understanding userId" section in docs
-
-**Changes:**
-- Updated config examples to use concrete `userId` values instead of placeholders
-
-**Bug Fixes:**
-- Migrated platform search to Mem0 v2 API
-
-</Update>
-
-<Update label="2026-02-19" description="v0.1.2">
-
-**New Features:**
-- Source field for openclaw memory entries
-
-**Bug Fixes:**
-- Auto-recall injection and auto-capture message drop
-
-</Update>
-
-<Update label="2026-02-02" description="v0.1.0">
-
-**New Features:**
-- Initial release of the OpenClaw Mem0 plugin
-- Platform mode (Mem0 Cloud) and open-source mode support
-- Auto-recall: inject relevant memories before each turn
-- Auto-capture: store facts after each turn
-- Configurable `topK`, `threshold`, and `apiVersion` options
-
-</Update>

docs/changelog/platform.mdx

@@ -1,6 +1,6 @@
 ---
 title: "Platform"
-description: "Release notes for the Mem0 hosted platform — backend, dashboard, billing, and infrastructure changes."
+description: "Release notes for the Mem0 hosted platform: backend, dashboard, billing, and infrastructure changes."
 mode: "wide"
 ---
 

docs/components/embedders/models/aws_bedrock.mdx

@@ -3,11 +3,27 @@ title: AWS Bedrock
 description: "Configure AWS Bedrock as an embedding provider in Mem0 with IAM credentials and boto3 authentication."
 ---
 
-To use AWS Bedrock embedding models, you need to have the appropriate AWS credentials and permissions. The embeddings implementation relies on the `boto3` library.
+To use AWS Bedrock embedding models, you need the appropriate AWS credentials and permissions. Python uses `boto3`, and TypeScript uses `@aws-sdk/client-bedrock-runtime`.
+
+Both SDKs support the Amazon Titan and Cohere embedding model families.
 
 ### Setup
-- Ensure you have model access from the [AWS Bedrock Console](https://us-east-1.console.aws.amazon.com/bedrock/home?region=us-east-1#/modelaccess)
-- Authenticate the boto3 client using a method described in the [AWS documentation](https://boto3.amazonaws.com/v1/documentation/api/latest/guide/credentials.html)
+
+- Model access is automatic: Bedrock enables serverless foundation models on first invocation in AWS commercial regions, and the [Model access page has been retired](https://docs.aws.amazon.com/bedrock/latest/userguide/model-access.html). Cohere models are served from AWS Marketplace, so an account's first invocation must come from a principal with the `aws-marketplace:Subscribe` permission; after that, any user in the account can invoke them. Browse the models available to you in the [Bedrock model catalog](https://console.aws.amazon.com/bedrock/).
+- Install the AWS client for your language:
+
+  <CodeGroup>
+  ```bash Python
+  pip install boto3
+  ```
+
+  ```bash TypeScript
+  npm install @aws-sdk/client-bedrock-runtime
+  ```
+  </CodeGroup>
+
+  In TypeScript this package is an optional peer dependency, so it is only required when you actually use the Bedrock embedder.
+
 - Set up environment variables for authentication:
   ```bash
   export AWS_REGION=us-east-1
@@ -15,6 +31,8 @@ To use AWS Bedrock embedding models, you need to have the appropriate AWS creden
   export AWS_SECRET_ACCESS_KEY=your-secret-key
   ```
 
+Both SDKs fall back to the standard AWS credential chain (environment variables, shared config, SSO, or an instance role) when you do not pass credentials in the config, so you rarely need to hardcode keys. See the [boto3 credentials guide](https://boto3.amazonaws.com/v1/documentation/api/latest/guide/credentials.html) for the Python resolution order.
+
 ### Usage
 
 <CodeGroup>
@@ -48,8 +66,46 @@ messages = [
 ]
 m.add(messages, user_id="alice")
 ```
+
+```typescript TypeScript
+import { Memory } from "mem0ai/oss";
+
+// Credentials are read from the AWS default chain (AWS_REGION,
+// AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, SSO, or an instance role).
+const memory = new Memory({
+  embedder: {
+    provider: "aws_bedrock",
+    config: {
+      model: "amazon.titan-embed-text-v2:0",
+      awsRegion: "us-west-2",
+    },
+  },
+});
+
+const messages = [
+  { role: "user", content: "I'm planning to watch a movie tonight. Any recommendations?" },
+  { role: "assistant", content: "How about thriller movies? They can be quite engaging." },
+  { role: "user", content: "I'm not a big fan of thriller movies but I love sci-fi movies." },
+  { role: "assistant", content: "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future." },
+];
+await memory.add(messages, { userId: "alice" });
+```
 </CodeGroup>
 
+### Choosing a model
+
+| Model | Notes |
+| --- | --- |
+| `amazon.titan-embed-text-v1` | Default. Fixed 1536-dimension output. |
+| `amazon.titan-embed-text-v2:0` | Supports a configurable output size of 256, 512, or 1024. |
+| `cohere.embed-english-v3` | English text. Embeds up to 96 texts per request. |
+| `cohere.embed-multilingual-v3` | Multilingual text. Embeds up to 96 texts per request. |
+| `cohere.embed-v4:0` | Text. Embeds up to 96 texts per request. Supports a configurable output size of 256, 512, 1024, or 1536. TypeScript only. |
+
+Custom output sizes are model specific. In Python, only Titan Text Embeddings V2 accepts one. In TypeScript, Titan Text Embeddings V2 and Cohere Embed v4 both do, and `embeddingDims` is ignored on Titan V1 and on Cohere v3, which have no such parameter. When you do set it, make sure your vector store dimension matches, otherwise inserts will fail.
+
+Bedrock caps a Cohere embedding call at 96 texts. The TypeScript SDK splits larger batches into multiple requests for you, so a 200 text batch becomes 3 calls.
+
 ### Config
 
 Here are the parameters available for configuring AWS Bedrock embedder:
@@ -59,5 +115,21 @@ Here are the parameters available for configuring AWS Bedrock embedder:
 | Parameter | Description | Default Value |
 | --- | --- | --- |
 | `model` | The name of the embedding model to use | `amazon.titan-embed-text-v1` |
+| `aws_region` | AWS region for the Bedrock client | `us-west-2` |
+| `aws_access_key_id` | AWS access key ID for authentication | `None` |
+| `aws_secret_access_key` | AWS secret access key for authentication | `None` |
+| `aws_session_token` | AWS session token for temporary credentials | `None` |
+</Tab>
+<Tab title="TypeScript">
+| Parameter | Description | Default Value |
+| --- | --- | --- |
+| `model` | The name of the embedding model to use | `amazon.titan-embed-text-v1` |
+| `awsRegion` | AWS region for the Bedrock client. Falls back to the `AWS_REGION` environment variable | `us-west-2` |
+| `embeddingDims` | Output vector size. Titan Text Embeddings V2 (256, 512, or 1024) and Cohere Embed v4 (256, 512, 1024, or 1536) only | `undefined` |
+| `awsAccessKeyId` | AWS access key ID for authentication | `undefined` |
+| `awsSecretAccessKey` | AWS secret access key for authentication | `undefined` |
+| `awsSessionToken` | AWS session token for temporary credentials | `undefined` |
+
+Omit the three credential fields to use the AWS default credential chain. If you do pass them, `awsAccessKeyId` and `awsSecretAccessKey` are both required.
 </Tab>
 </Tabs>

docs/components/embedders/models/azure_openai.mdx

@@ -3,7 +3,7 @@ title: Azure OpenAI
 description: "Configure Azure OpenAI as an embedding provider in Mem0 with API key, deployment, and endpoint settings."
 ---
 
-To use Azure OpenAI embedding models, set the `EMBEDDING_AZURE_OPENAI_API_KEY`, `EMBEDDING_AZURE_DEPLOYMENT`, `EMBEDDING_AZURE_ENDPOINT` and `EMBEDDING_AZURE_API_VERSION` environment variables. You can obtain the Azure OpenAI API key from the Azure.
+To use Azure OpenAI embedding models, set the `EMBEDDING_AZURE_OPENAI_API_KEY`, `EMBEDDING_AZURE_DEPLOYMENT`, `EMBEDDING_AZURE_ENDPOINT` and `EMBEDDING_AZURE_API_VERSION` environment variables. You can obtain the Azure OpenAI API key from the Azure Portal.
 
 ### Usage
 

docs/components/embedders/models/fastembed.mdx

@@ -0,0 +1,111 @@
+---
+title: "FastEmbed"
+description: "Configure FastEmbed as an embedding provider in Mem0 to generate embeddings locally using ONNX-based models without a GPU."
+---
+
+You can use FastEmbed to run embedding models locally in Mem0. FastEmbed is an ONNX-based embedding library that runs efficiently on CPU without requiring a GPU or an external API key.
+
+### Installation
+
+FastEmbed is an optional dependency, so install it alongside Mem0.
+
+<CodeGroup>
+```bash Python
+pip install fastembed
+```
+
+```bash TypeScript
+npm install fastembed
+```
+</CodeGroup>
+
+### Usage
+
+<CodeGroup>
+```python Python
+import os
+from mem0 import Memory
+
+os.environ["OPENAI_API_KEY"] = "your_api_key" # For LLM
+
+config = {
+    "embedder": {
+        "provider": "fastembed",
+        "config": {
+            "model": "thenlper/gte-large"
+        }
+    }
+}
+
+m = Memory.from_config(config)
+messages = [
+    {"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
+    {"role": "assistant", "content": "How about thriller movies? They can be quite engaging."},
+    {"role": "user", "content": "I'm not a big fan of thriller movies but I love sci-fi movies."},
+    {"role": "assistant", "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future."}
+]
+m.add(messages, user_id="john")
+```
+
+```typescript TypeScript
+import { Memory } from "mem0ai/oss";
+
+// FastEmbed needs no API key. Leave the embedder config empty to use the
+// default model (fast-bge-small-en-v1.5), or set `model` to one of the
+// supported models listed below.
+const memory = new Memory({
+  embedder: {
+    provider: "fastembed",
+    config: {
+      model: "fast-bge-small-en-v1.5",
+    },
+  },
+  llm: {
+    provider: "openai",
+    config: { apiKey: process.env.OPENAI_API_KEY }, // For fact extraction
+  },
+});
+
+const messages = [
+  { role: "user", content: "I'm planning to watch a movie tonight. Any recommendations?" },
+  { role: "assistant", content: "How about thriller movies? They can be quite engaging." },
+  { role: "user", content: "I'm not a big fan of thriller movies but I love sci-fi movies." },
+  { role: "assistant", content: "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future." },
+];
+await memory.add(messages, { userId: "john" });
+```
+</CodeGroup>
+
+<Note>
+  **The Python and TypeScript SDKs default to different models.** Python defaults to `thenlper/gte-large` (1024 dimensions), while TypeScript defaults to `fast-bge-small-en-v1.5` (384 dimensions). The TypeScript package (`fastembed` on npm) ships a fixed set of ONNX models and does not include `thenlper/gte-large`. Because the two defaults produce vectors of different dimensions, do not point both SDKs at the same vector store collection unless you configure them to use the same model.
+</Note>
+
+The TypeScript SDK supports these FastEmbed models. Pass the exact string as `model`:
+
+- `fast-bge-small-en-v1.5` (default)
+- `fast-bge-small-en`
+- `fast-bge-base-en`
+- `fast-bge-base-en-v1.5`
+- `fast-bge-small-zh-v1.5`
+- `fast-all-MiniLM-L6-v2`
+- `fast-multilingual-e5-large`
+
+### Config
+
+Here are the parameters available for configuring the FastEmbed embedder:
+
+<Tabs>
+<Tab title="Python">
+| Parameter | Description | Default Value |
+| --- | --- | --- |
+| `model` | The name of the FastEmbed model to use | `thenlper/gte-large` |
+| `embedding_dims` | Dimensions of the embedding model (auto-derived from the model if not set) | `None` |
+</Tab>
+<Tab title="TypeScript">
+| Parameter | Description | Default Value |
+| --- | --- | --- |
+| `model` | The FastEmbed model to use (see the supported list above) | `fast-bge-small-en-v1.5` |
+
+The embedding dimension is detected automatically at startup, so you do not need to set it manually.
+</Tab>
+</Tabs>

docs/components/embedders/models/google_AI.mdx

@@ -67,14 +67,15 @@ Here are the parameters available for configuring Gemini embedder:
 | Parameter        | Description                          | Default Value           |
 | ---------------- | ------------------------------------ | ----------------------- |
 | `model`          | The name of the embedding model to use| `models/gemini-embedding-001` |
-| `embedding_dims` | Dimensions of the embedding model     | `1536`                  |
+| `embedding_dims` | Dimensions of the embedding model     | `768`                   |
 | `api_key`        | The Google API key                   | `None`                  |
+| `output_dimensionality` | Output dimensionality for the embedding model (Gemini-specific; used when `embedding_dims` is not set) | `None` |
 </Tab>
 <Tab title="TypeScript">
 | Parameter         | Description                                   | Default Value              |
 | ----------------- | --------------------------------------------- | -------------------------- |
 | `model`           | The name of the embedding model to use        | `gemini-embedding-001`     |
-| `embeddingDims`   | Dimensions of the embedding model             | `1536`                     |
+| `embeddingDims`   | Dimensions of the embedding model. When not set, uses the model's native output dimensionality (3072 for `gemini-embedding-001`; MRL truncation to 768, 1536, or 3072 is supported) | `None`                     |
 | `apiKey`          | Google API key                                | `None`                     |
 </Tab>
 </Tabs>

docs/components/embedders/models/huggingface.mdx

@@ -5,6 +5,10 @@ description: "Configure Hugging Face as an embedding provider in Mem0 for local
 
 You can use embedding models from Huggingface to run Mem0 locally.
 
+<Note>
+The TypeScript SDK supports Hugging Face only through a hosted [Text Embeddings Inference (TEI)](#using-text-embeddings-inference-tei) endpoint, or any OpenAI-compatible Hugging Face endpoint. The local `sentence-transformers` mode shown first is Python-only.
+</Note>
+
 ### Usage
 
 ```python
@@ -34,9 +38,10 @@ m.add(messages, user_id="john")
 
 ### Using Text Embeddings Inference (TEI)
 
-You can also use Hugging Face's Text Embeddings Inference service for faster and more efficient embeddings:
+You can also use Hugging Face's Text Embeddings Inference service for faster and more efficient embeddings. This is the mode the TypeScript SDK uses.
 
-```python
+<CodeGroup>
+```python Python
 import os
 from mem0 import Memory
 
@@ -56,6 +61,24 @@ m = Memory.from_config(config)
 m.add("This text will be embedded using the TEI service.", user_id="john")
 ```
 
+```typescript TypeScript
+import { Memory } from 'mem0ai/oss';
+
+// Point at a running TEI server, or any OpenAI-compatible HF endpoint
+const config = {
+  embedder: {
+    provider: 'huggingface',
+    config: {
+      huggingfaceBaseUrl: 'http://localhost:3000/v1',
+    },
+  },
+};
+
+const memory = new Memory(config);
+await memory.add("This text will be embedded using the TEI service.", { userId: "john" });
+```
+</CodeGroup>
+
 To run the TEI service, you can use Docker:
 
 ```bash
@@ -66,11 +89,22 @@ docker run -d -p 3000:80 -v huggingfacetei:/data --platform linux/amd64 \
 
 ### Config
 
-Here are the parameters available for configuring Huggingface embedder:
+Here are the parameters available for configuring the Hugging Face embedder:
 
+<Tabs>
+<Tab title="Python">
 | Parameter | Description | Default Value |
 | --- | --- | --- |
 | `model` | The name of the model to use | `multi-qa-MiniLM-L6-cos-v1` |
 | `embedding_dims` | Dimensions of the embedding model | `selected_model_dimensions` |
 | `model_kwargs` | Additional arguments for the model | `None` |
-| `huggingface_base_url` | URL to connect to Text Embeddings Inference (TEI) API | `None` |
+| `huggingface_base_url` | URL to connect to Text Embeddings Inference (TEI) API | `None` |
+</Tab>
+<Tab title="TypeScript">
+| Parameter | Description | Default Value |
+| --- | --- | --- |
+| `huggingfaceBaseUrl` | TEI or OpenAI-compatible endpoint URL. Required; falls back to `baseURL`, `url`, then the `HUGGINGFACE_BASE_URL` env var | `None` |
+| `model` | Model name sent to the endpoint (TEI ignores it) | `tei` |
+| `apiKey` | API key for the endpoint; falls back to the `HUGGINGFACE_API_KEY` env var | `"hf"` |
+</Tab>
+</Tabs>

docs/components/embedders/models/lmstudio.mdx

@@ -16,7 +16,7 @@ config = {
     "embedder": {
         "provider": "lmstudio",
         "config": {
-            "model": "nomic-embed-text-v1.5-GGUF/nomic-embed-text-v1.5.f16.gguf"
+            "model": "nomic-ai/nomic-embed-text-v1.5-GGUF"
         }
     }
 }
@@ -37,6 +37,6 @@ Here are the parameters available for configuring LM Studio embedder:
 
 | Parameter | Description | Default Value |
 | --- | --- | --- |
-| `model` | The name of the LM Studio model to use | `nomic-embed-text-v1.5-GGUF/nomic-embed-text-v1.5.f16.gguf` |
+| `model` | The name of the LM Studio model to use | `nomic-ai/nomic-embed-text-v1.5-GGUF` |
 | `embedding_dims` | Dimensions of the embedding model | `1536` |
 | `lmstudio_base_url` | Base URL for LM Studio connection | `http://localhost:1234/v1` |

docs/components/embedders/models/together.mdx

@@ -1,15 +1,20 @@
 ---
 title: Together
-description: "Configure Together AI as an embedding provider in Mem0 with support for 768-dimensional embedding models."
+description: "Configure Together AI as an embedding provider in Mem0 with support for 1024-dimensional embedding models."
 ---
 
-To use Together embedding models, set the `TOGETHER_API_KEY` environment variable. You can obtain the Together API key from the [Together Platform](https://api.together.xyz/settings/api-keys).
+To use Together embedding models, set the `TOGETHER_API_KEY` environment variable. You can obtain the Together API key from the [Together Platform](https://api.together.ai/settings/projects/~current/api-keys).
 
 ### Usage
 
-<Note> The `embedding_model_dims` parameter for `vector_store` should be set to `768` for Together embedder. </Note>
+<Note> The `embedding_model_dims` parameter for `vector_store` should be set to `1024` for Together embedder. </Note>
 
-```python
+<Warning>
+**Breaking default change.** The default Together embedding model is now `intfloat/multilingual-e5-large-instruct` (**1024-dim**), replacing the previous default `togethercomputer/m2-bert-80M-8k-retrieval` (**768-dim**). If you created a self-hosted vector store with the old default, its collection is 768-dim and will reject the new 1024-dim vectors **recreate/reindex the collection at 1024 dimensions** after upgrading. To defer the change, pin the previous values explicitly (`model="togethercomputer/m2-bert-80M-8k-retrieval"`, `embedding_dims=768`) note Together no longer lists this model among its recommended embeddings, so reindexing at 1024 is the durable path.
+</Warning>
+
+<CodeGroup>
+```python Python
 import os
 from mem0 import Memory
 
@@ -20,7 +25,7 @@ config = {
     "embedder": {
         "provider": "together",
         "config": {
-            "model": "togethercomputer/m2-bert-80M-8k-retrieval"
+            "model": "intfloat/multilingual-e5-large-instruct"
         }
     }
 }
@@ -29,18 +34,50 @@ m = Memory.from_config(config)
 messages = [
     {"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
     {"role": "assistant", "content": "How about thriller movies? They can be quite engaging."},
-    {"role": "user", "content": "I’m not a big fan of thriller movies but I love sci-fi movies."},
+    {"role": "user", "content": "I'm not a big fan of thriller movies but I love sci-fi movies."},
     {"role": "assistant", "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future."}
 ]
 m.add(messages, user_id="john")
 ```
 
+```typescript TypeScript
+import { Memory } from 'mem0ai/oss';
+
+const config = {
+  embedder: {
+    provider: 'together',
+    config: {
+      apiKey: process.env.TOGETHER_API_KEY || '',
+      model: 'intfloat/multilingual-e5-large-instruct',
+      embeddingDims: 1024,
+    },
+  },
+};
+
+const memory = new Memory(config);
+await memory.add("I'm visiting Paris", { userId: "john" });
+```
+
+</CodeGroup>
+
 ### Config
 
 Here are the parameters available for configuring Together embedder:
 
+<Tabs>
+<Tab title="Python">
 | Parameter | Description | Default Value |
 | --- | --- | --- |
-| `model` | The name of the embedding model to use | `togethercomputer/m2-bert-80M-8k-retrieval` |
-| `embedding_dims` | Dimensions of the embedding model | `768` |
+| `model` | The name of the embedding model to use | `intfloat/multilingual-e5-large-instruct` |
+| `embedding_dims` | Dimensions of the embedding model | `1024` |
 | `api_key` | The Together API key | `None` |
+</Tab>
+<Tab title="TypeScript">
+| Parameter | Description | Default Value |
+| --- | --- | --- |
+| `model` | The name of the embedding model to use | `intfloat/multilingual-e5-large-instruct` |
+| `embeddingDims` | Dimensions of the embedding model for vector store configuration | `1024` |
+| `apiKey` | The Together API key | `TOGETHER_API_KEY` |
+| `baseURL` | Base URL for an OpenAI-compatible Together endpoint | `https://api.together.ai/v1` |
+</Tab>
+</Tabs>

docs/components/embedders/models/vertexai.mdx

@@ -4,11 +4,36 @@ description: "Configure Google Cloud Vertex AI as an embedding provider in Mem0
 ---
 ### Vertex AI
 
-To use Google Cloud's Vertex AI for text embedding models, set the `GOOGLE_APPLICATION_CREDENTIALS` environment variable to point to the path of your service account's credentials JSON file. These credentials can be created in the [Google Cloud Console](https://console.cloud.google.com/).
+Google Cloud's Vertex AI serves text embedding models such as `gemini-embedding-001`. Mem0 uses them through the provider's own SDK, which you install alongside Mem0.
+
+### Installation
+
+The Vertex AI client is an optional dependency, so install it yourself.
+
+<CodeGroup>
+```bash Python
+pip install vertexai
+```
+
+```bash TypeScript
+npm install @google-cloud/aiplatform
+```
+</CodeGroup>
+
+### Authentication
+
+Both SDKs authenticate with [Application Default Credentials](https://cloud.google.com/docs/authentication/application-default-credentials). Pick whichever fits your environment:
+
+- **Local development:** run `gcloud auth application-default login`.
+- **Service account:** create a key in the [Google Cloud Console](https://console.cloud.google.com/) and point `GOOGLE_APPLICATION_CREDENTIALS` at the JSON file, or pass its path through the embedder config.
+- **Google Cloud runtimes** (Cloud Run, GKE, Compute Engine): the attached service account is picked up automatically.
+
+The TypeScript SDK reads the project ID from `googleProjectId`, then the `GCP_PROJECT_ID`, `GOOGLE_CLOUD_PROJECT`, and `GCLOUD_PROJECT` environment variables, and finally from your credentials. Set it explicitly when your credentials cover more than one project.
 
 ### Usage
 
-```python
+<CodeGroup>
+```python Python
 import os
 from mem0 import Memory
 
@@ -32,28 +57,87 @@ m = Memory.from_config(config)
 messages = [
     {"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
     {"role": "assistant", "content": "How about thriller movies? They can be quite engaging."},
-    {"role": "user", "content": "I’m not a big fan of thriller movies but I love sci-fi movies."},
+    {"role": "user", "content": "I'm not a big fan of thriller movies but I love sci-fi movies."},
     {"role": "assistant", "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future."}
 ]
 m.add(messages, user_id="john")
 ```
-The embedding types can be one of the following:
+
+```typescript TypeScript
+import { Memory } from "mem0ai/oss";
+
+const config = {
+  embedder: {
+    provider: "vertexai",
+    config: {
+      model: "gemini-embedding-001",
+      // Optional. Falls back to GCP_PROJECT_ID / GOOGLE_CLOUD_PROJECT /
+      // GCLOUD_PROJECT, then to the project on your credentials.
+      googleProjectId: process.env.GCP_PROJECT_ID,
+      location: "us-central1",
+      // Optional. Path to a service account key file, or pass the JSON inline
+      // via googleServiceAccountJson.
+      vertexCredentialsJson: "/path/to/your/credentials.json",
+      embeddingDims: 256,
+      memoryAddEmbeddingType: "RETRIEVAL_DOCUMENT",
+      memoryUpdateEmbeddingType: "RETRIEVAL_DOCUMENT",
+      memorySearchEmbeddingType: "RETRIEVAL_QUERY",
+    },
+  },
+};
+
+const memory = new Memory(config);
+await memory.add("I love sci-fi movies but not thrillers", { userId: "john" });
+```
+</CodeGroup>
+
+### Embedding types
+
+Vertex AI embeds the same text differently depending on the task you declare. The embedding types can be one of the following:
 - SEMANTIC_SIMILARITY
 - CLASSIFICATION
 - CLUSTERING
 - RETRIEVAL_DOCUMENT, RETRIEVAL_QUERY, QUESTION_ANSWERING, FACT_VERIFICATION
-- CODE_RETRIEVAL_QUERY  
-Check out the [Vertex AI documentation](https://cloud.google.com/vertex-ai/generative-ai/docs/embeddings/task-types#supported_task_types) for more information.  
-  
+- CODE_RETRIEVAL_QUERY
+
+Check out the [Vertex AI documentation](https://cloud.google.com/vertex-ai/generative-ai/docs/embeddings/task-types#supported_task_types) for more information.
+
+<Note>
+These embedding types map to the add, update, and search memory actions in both the Python and TypeScript SDKs. Stored memories use the add or update type, and searches use the search type.
+</Note>
+
+### Choosing a model
+
+<Warning>
+`gemini-embedding-001` accepts **one input text per request**. When Mem0 embeds several texts at once, such as the memories extracted from a single conversation turn, it issues one request per text. The older `text-embedding-005` and `text-multilingual-embedding-002` models accept up to 250 texts per request, so they are faster and cheaper for large batches. See [Get text embeddings](https://cloud.google.com/vertex-ai/generative-ai/docs/embeddings/get-text-embeddings).
+</Warning>
+
 ### Config
 
 Here are the parameters available for configuring the Vertex AI embedder:
 
-| Parameter                 | Description                                      | Default Value        |
-| ------------------------- | ------------------------------------------------ | -------------------- |
-| `model`                   | The name of the Vertex AI embedding model to use | `gemini-embedding-001` |
-| `vertex_credentials_json` | Path to the Google Cloud credentials JSON file   | `None`               |
-| `embedding_dims`          | Dimensions of the embedding model                | `256`                |
-| `memory_add_embedding_type` | The type of embedding to use for the add memory action | `RETRIEVAL_DOCUMENT` |
-| `memory_update_embedding_type` | The type of embedding to use for the update memory action | `RETRIEVAL_DOCUMENT` |
-| `memory_search_embedding_type` | The type of embedding to use for the search memory action | `RETRIEVAL_QUERY` |
+<Tabs>
+<Tab title="Python">
+| Parameter                        | Description                                                | Default Value          |
+| -------------------------------- | ---------------------------------------------------------- | ---------------------- |
+| `model`                          | The name of the Vertex AI embedding model to use           | `gemini-embedding-001` |
+| `vertex_credentials_json`        | Path to the Google Cloud credentials JSON file             | `None`                 |
+| `embedding_dims`                 | Dimensions of the embedding model                          | `256`                  |
+| `memory_add_embedding_type`      | The embedding type to use for the add memory action        | `RETRIEVAL_DOCUMENT`   |
+| `memory_update_embedding_type`   | The embedding type to use for the update memory action     | `RETRIEVAL_DOCUMENT`   |
+| `memory_search_embedding_type`   | The embedding type to use for the search memory action     | `RETRIEVAL_QUERY`      |
+</Tab>
+<Tab title="TypeScript">
+| Parameter                     | Description                                                                 | Default Value          |
+| ----------------------------- | -------------------------------------------------------------------------- | ---------------------- |
+| `model`                       | The name of the Vertex AI embedding model to use                           | `gemini-embedding-001` |
+| `googleProjectId`             | Google Cloud project ID (falls back to `GCP_PROJECT_ID` env var, then to your credentials) | Resolved from credentials |
+| `location`                    | Google Cloud region (falls back to `GCP_LOCATION` env var)                 | `us-central1`          |
+| `vertexCredentialsJson`       | Path to the Google Cloud credentials JSON file                             | `None`                 |
+| `googleServiceAccountJson`    | Service account credentials as a JSON string or object                     | `None`                 |
+| `embeddingDims`               | Dimensions of the embedding model                                          | `256`                  |
+| `memoryAddEmbeddingType`      | The embedding type to use for the add memory action                        | `RETRIEVAL_DOCUMENT`   |
+| `memoryUpdateEmbeddingType`   | The embedding type to use for the update memory action                     | `RETRIEVAL_DOCUMENT`   |
+| `memorySearchEmbeddingType`   | The embedding type to use for the search memory action                     | `RETRIEVAL_QUERY`      |
+</Tab>
+</Tabs>

docs/components/embedders/overview.mdx

@@ -10,20 +10,21 @@ Mem0 offers support for various embedding models, allowing users to choose the o
 See the list of supported embedders below.
 
 <Note>
-  The following embedders are supported in the Python implementation. The TypeScript implementation currently only supports OpenAI.
+  All embedders listed below are supported in the Python implementation. The TypeScript implementation supports: **OpenAI**, **Azure OpenAI**, **AWS Bedrock**, **FastEmbed**, **Google AI**, **Hugging Face**, **Langchain**, **LM Studio**, **Ollama**, **Together**, and **Vertex AI**.
 </Note>
 
 <CardGroup cols={4}>
-  <Card title="OpenAI" href="/components/embedders/models/openai"></Card>
-  <Card title="Azure OpenAI" href="/components/embedders/models/azure_openai"></Card>
-  <Card title="Ollama" href="/components/embedders/models/ollama"></Card>
-  <Card title="Hugging Face" href="/components/embedders/models/huggingface"></Card>
-  <Card title="Google AI" href="/components/embedders/models/google_AI"></Card>
-  <Card title="Vertex AI" href="/components/embedders/models/vertexai"></Card>
-  <Card title="Together" href="/components/embedders/models/together"></Card>
-  <Card title="LM Studio" href="/components/embedders/models/lmstudio"></Card>
-  <Card title="Langchain" href="/components/embedders/models/langchain"></Card>
-  <Card title="AWS Bedrock" href="/components/embedders/models/aws_bedrock"></Card>
+  <Card title="OpenAI" icon="/images/provider-icons/openai.svg" href="/components/embedders/models/openai"></Card>
+  <Card title="Azure OpenAI" icon="/images/provider-icons/azure-color.svg" href="/components/embedders/models/azure_openai"></Card>
+  <Card title="Ollama" icon="/images/provider-icons/ollama.svg" href="/components/embedders/models/ollama"></Card>
+  <Card title="Hugging Face" icon="/images/provider-icons/huggingface.svg" href="/components/embedders/models/huggingface"></Card>
+  <Card title="Google AI" icon="/images/provider-icons/google-color.svg" href="/components/embedders/models/google_AI"></Card>
+  <Card title="Vertex AI" icon="/images/provider-icons/vertexai.svg" href="/components/embedders/models/vertexai"></Card>
+  <Card title="Together" icon="/images/provider-icons/together-color.svg" href="/components/embedders/models/together"></Card>
+  <Card title="LM Studio" icon="/images/provider-icons/lmstudio.svg" href="/components/embedders/models/lmstudio"></Card>
+  <Card title="Langchain" icon="/images/provider-icons/langchain-color.svg" href="/components/embedders/models/langchain"></Card>
+  <Card title="AWS Bedrock" icon="/images/provider-icons/bedrock-color.svg" href="/components/embedders/models/aws_bedrock"></Card>
+  <Card title="FastEmbed" icon="/images/provider-icons/qdrant.svg" href="/components/embedders/models/fastembed"></Card>
 </CardGroup>
 
 ## Usage

docs/components/llms/config.mdx

@@ -98,7 +98,7 @@ Here's a comprehensive list of all parameters that can be used across different
     | `max_tokens`         | Tokens to generate                            | All               |
     | `top_p`              | Probability threshold for nucleus sampling    | All               |
     | `top_k`              | Number of highest probability tokens to keep  | All               |
-    | `http_client_proxies`| Allow proxy server settings                   | AzureOpenAI       |
+    | `http_client_proxies`| Allow proxy server settings                   | All               |
     | `models`             | List of models                                | Openrouter        |
     | `route`              | Routing strategy                              | Openrouter        |
     | `openrouter_base_url`| Base URL for Openrouter API                   | Openrouter        |
@@ -110,7 +110,7 @@ Here's a comprehensive list of all parameters that can be used across different
     | `deepseek_base_url`  | Base URL for DeepSeek API                     | DeepSeek          |
     | `xai_base_url`       | Base URL for XAI API                          | XAI               |
     | `sarvam_base_url`    | Base URL for Sarvam API                       | Sarvam            |
-    | `reasoning_effort`   | Reasoning level (low, medium, high)           | Sarvam            |
+    | `reasoning_effort`   | Reasoning level (low, medium, high)           | All               |
     | `frequency_penalty`  | Penalize frequent tokens (-2.0 to 2.0)        | Sarvam            |
     | `presence_penalty`   | Penalize existing tokens (-2.0 to 2.0)        | Sarvam            |
     | `seed`               | Seed for deterministic sampling               | Sarvam            |

docs/components/llms/models/anthropic.mdx

@@ -20,7 +20,7 @@ config = {
     "llm": {
         "provider": "anthropic",
         "config": {
-            "model": "claude-sonnet-4-20250514",
+            "model": "claude-sonnet-4-6",
             "temperature": 0.1,
             "max_tokens": 2000,
         }
@@ -45,7 +45,7 @@ const config = {
     provider: 'anthropic',
     config: {
       apiKey: process.env.ANTHROPIC_API_KEY || '',
-      model: 'claude-sonnet-4-20250514',
+      model: 'claude-sonnet-4-6',
       temperature: 0.1,
       maxTokens: 2000,
     },

docs/components/llms/models/aws_bedrock.mdx

@@ -5,16 +5,18 @@ description: "Configure AWS Bedrock as an LLM provider in Mem0 with IAM authenti
 
 ### Setup
 - Before using the AWS Bedrock LLM, make sure you have the appropriate model access from [Bedrock Console](https://us-east-1.console.aws.amazon.com/bedrock/home?region=us-east-1#/modelaccess).
-- You will also need to authenticate the `boto3` client by using a method in the [AWS documentation](https://boto3.amazonaws.com/v1/documentation/api/latest/guide/credentials.html#configuring-credentials)
-- You will have to export `AWS_REGION`, `AWS_ACCESS_KEY`, and `AWS_SECRET_ACCESS_KEY` to set environment variables.
+- Model availability is per-region. `anthropic.claude-sonnet-4-20250514-v1:0` supports on-demand inference in `us-east-1` and `ap-southeast-4`; from any other region, use the cross-region inference profile ID `us.anthropic.claude-sonnet-4-20250514-v1:0` instead.
+- Install the AWS SDK for your language: `pip install boto3` (Python) or `npm install @aws-sdk/client-bedrock-runtime` (TypeScript).
+- Both SDKs fall back to the standard AWS credential chain (environment variables, `~/.aws/credentials`, or an attached IAM role), so exporting `AWS_REGION`, `AWS_ACCESS_KEY_ID`, and `AWS_SECRET_ACCESS_KEY` is the quickest way to get started. In TypeScript you can also pass credentials inline with `awsRegion`, `awsAccessKeyId`, `awsSecretAccessKey`, and `awsSessionToken`, as shown below.
 
 ### Usage
 
-```python
+<CodeGroup>
+```python Python
 import os
 from mem0 import Memory
 
-os.environ['AWS_REGION'] = 'us-west-2'
+os.environ['AWS_REGION'] = 'us-east-1'
 os.environ["AWS_ACCESS_KEY_ID"] = "xx"
 os.environ["AWS_SECRET_ACCESS_KEY"] = "xx"
 
@@ -22,7 +24,7 @@ config = {
     "llm": {
         "provider": "aws_bedrock",
         "config": {
-            "model": "anthropic.claude-3-5-haiku-20241022-v1:0",
+            "model": "anthropic.claude-sonnet-4-20250514-v1:0",
             "temperature": 0.2,
             "max_tokens": 2000,
         }
@@ -39,6 +41,43 @@ messages = [
 m.add(messages, user_id="alice", metadata={"category": "movies"})
 ```
 
+```typescript TypeScript
+import { Memory } from 'mem0ai/oss';
+
+const config = {
+  llm: {
+    provider: 'aws_bedrock',
+    config: {
+      model: 'anthropic.claude-sonnet-4-20250514-v1:0',
+      temperature: 0.2,
+      maxTokens: 2000,
+      // Optional. Omit these to use the default AWS credential chain.
+      awsRegion: process.env.AWS_REGION,
+      awsAccessKeyId: process.env.AWS_ACCESS_KEY_ID,
+      awsSecretAccessKey: process.env.AWS_SECRET_ACCESS_KEY,
+    },
+  },
+};
+
+const memory = new Memory(config);
+const messages = [
+    {"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
+    {"role": "assistant", "content": "How about thriller movies? They can be quite engaging."},
+    {"role": "user", "content": "I’m not a big fan of thriller movies but I love sci-fi movies."},
+    {"role": "assistant", "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future."}
+];
+await memory.add(messages, { userId: 'alice', metadata: { category: 'movies' } });
+```
+</CodeGroup>
+
+<Note>
+  `@aws-sdk/client-bedrock-runtime` is an optional peer dependency of `mem0ai`, so npm will not install it for you. The TypeScript provider loads it lazily and throws a clear error on the first request if the package is missing.
+</Note>
+
+<Note>
+  The TypeScript provider calls the Bedrock [Converse API](https://docs.aws.amazon.com/bedrock/latest/userguide/conversation-inference.html), a single uniform interface across the current Bedrock model families. Streaming and `InvokeModel`-only models are not supported yet.
+</Note>
+
 ### Config
 
-All available parameters for the `aws_bedrock` config are present in [Master List of All Params in Config](../config).
+All available parameters for the `aws_bedrock` config are present in [Master List of All Params in Config](../config).

docs/components/llms/models/azure_openai.mdx

@@ -5,7 +5,7 @@ description: "Configure Azure OpenAI as an LLM provider in Mem0 with Azure Ident
 
 <Note> Mem0 Now Supports Azure OpenAI Models in TypeScript SDK </Note>
 
-To use Azure OpenAI models, you have to set the `LLM_AZURE_OPENAI_API_KEY`, `LLM_AZURE_ENDPOINT`, `LLM_AZURE_DEPLOYMENT` and `LLM_AZURE_API_VERSION` environment variables. You can obtain the Azure API key from the [Azure](https://azure.microsoft.com/).
+To use Azure OpenAI models, you have to set the `LLM_AZURE_OPENAI_API_KEY`, `LLM_AZURE_ENDPOINT`, `LLM_AZURE_DEPLOYMENT` and `LLM_AZURE_API_VERSION` environment variables. You can obtain the Azure API key from the [Azure Portal](https://azure.microsoft.com/).
 
 Optionally, you can use Azure Identity to authenticate with Azure OpenAI, which allows you to use managed identities or service principals for production and Azure CLI login for development instead of an API key. If an Azure Identity is to be used, ***do not*** set the `LLM_AZURE_OPENAI_API_KEY` environment variable or the api_key in the config dictionary.
 

docs/components/llms/models/groq.mdx

@@ -21,7 +21,7 @@ config = {
     "llm": {
         "provider": "groq",
         "config": {
-            "model": "mixtral-8x7b-32768",
+            "model": "llama-3.3-70b-versatile",
             "temperature": 0.1,
             "max_tokens": 2000,
         }
@@ -46,7 +46,7 @@ const config = {
     provider: 'groq',
     config: {
       apiKey: process.env.GROQ_API_KEY || '',
-      model: 'mixtral-8x7b-32768',
+      model: 'llama3-70b-8192',
       temperature: 0.1,
       maxTokens: 1000,
     },

docs/components/llms/models/litellm.mdx

@@ -4,9 +4,12 @@ description: "Use LiteLLM as an LLM provider in Mem0 to access over 100 language
 ---
 [Litellm](https://litellm.vercel.app/docs/) is compatible with over 100 large language models (LLMs), all using a standardized input/output format. You can explore the [available models](https://litellm.vercel.app/docs/providers) to use with Litellm. Ensure you set the `API_KEY` for the model you choose to use.
 
+In the TypeScript SDK, run LiteLLM as a [proxy server](https://docs.litellm.ai/docs/simple_proxy) (an OpenAI-compatible endpoint) and point Mem0 at it via `LITELLM_API_BASE` (defaults to `http://localhost:4000`).
+
 ## Usage
 
-```python
+<CodeGroup>
+```python Python
 import os
 from mem0 import Memory
 
@@ -33,6 +36,33 @@ messages = [
 m.add(messages, user_id="alice", metadata={"category": "movies"})
 ```
 
+```typescript TypeScript
+import { Memory } from 'mem0ai/oss';
+
+// Point Mem0 at your LiteLLM proxy. apiKey defaults to "sk-anything"
+// (the proxy handles real auth); baseURL defaults to http://localhost:4000.
+const config = {
+  llm: {
+    provider: 'litellm',
+    config: {
+      apiKey: process.env.LITELLM_API_KEY || 'sk-anything',
+      baseURL: process.env.LITELLM_API_BASE || 'http://localhost:4000',
+      model: 'gpt-5-mini',
+    },
+  },
+};
+
+const memory = new Memory(config);
+const messages = [
+    {"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
+    {"role": "assistant", "content": "How about thriller movies? They can be quite engaging."},
+    {"role": "user", "content": "I’m not a big fan of thriller movies but I love sci-fi movies."},
+    {"role": "assistant", "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future."}
+];
+await memory.add(messages, { userId: 'alice', metadata: { category: 'movies' } });
+```
+</CodeGroup>
+
 ## Config
 
 All available parameters for the `litellm` config are present in [Master List of All Params in Config](../config).

docs/components/llms/models/minimax.mdx

@@ -7,7 +7,8 @@ To use MiniMax LLM models, you have to set the `MINIMAX_API_KEY` environment var
 
 ## Usage
 
-```python
+<CodeGroup>
+```python Python
 import os
 from mem0 import Memory
 
@@ -36,9 +37,37 @@ messages = [
 m.add(messages, user_id="alice", metadata={"category": "movies"})
 ```
 
+```typescript TypeScript
+import { Memory } from 'mem0ai/oss';
+
+const config = {
+  llm: {
+    provider: 'minimax',
+    config: {
+      apiKey: process.env.MINIMAX_API_KEY || '',
+      model: 'MiniMax-M2.7',
+      temperature: 0.2,
+      maxTokens: 2000,
+      topP: 1.0,
+    },
+  },
+};
+const memory = new Memory(config);
+const messages = [
+  { role: "user", content: "I'm planning to watch a movie tonight. Any recommendations?" },
+  { role: "assistant", content: "How about thriller movies? They can be quite engaging." },
+  { role: "user", content: "I'm not a big fan of thriller movies but I love sci-fi movies." },
+  { role: "assistant", content: "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future." },
+];
+await memory.add(messages, { userId: 'alice', metadata: { category: 'movies' } });
+```
+
+</CodeGroup>
+
 You can also configure the API base URL in the config:
 
-```python
+<CodeGroup>
+```python Python
 config = {
     "llm": {
         "provider": "minimax",
@@ -51,6 +80,20 @@ config = {
 }
 ```
 
+```typescript TypeScript
+const config = {
+  llm: {
+    provider: 'minimax',
+    config: {
+      model: 'MiniMax-M2.7',
+      baseURL: 'https://your-custom-endpoint.com',
+      apiKey: 'your-api-key', // alternatively to using the environment variable
+    },
+  },
+};
+```
+</CodeGroup>
+
 ## Config
 
 All available parameters for the `minimax` config are present in [Master List of All Params in Config](../config).

docs/components/llms/models/sarvam.mdx

@@ -9,7 +9,8 @@ To use Sarvam AI's models, please set the `SARVAM_API_KEY` which you can get fro
 
 ## Usage
 
-```python
+<CodeGroup>
+```python Python
 import os
 from mem0 import Memory
 
@@ -34,8 +35,35 @@ messages = [
     {"role": "assistant", "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future."}
 ]
 m.add(messages, user_id="alex")
+
 ```
 
+```typescript TypeScript
+import { Memory } from 'mem0ai/oss';
+
+const config = {
+  llm: {
+    provider: 'sarvam',
+    config: {
+      apiKey: process.env.SARVAM_API_KEY || '',
+      model: 'sarvam-m',
+      temperature: 0.7,
+    },
+  },
+};
+
+const memory = new Memory(config);
+const messages = [
+    {"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
+    {"role": "assistant", "content": "How about thriller movies? They can be quite engaging."},
+    {"role": "user", "content": "I'm not a big fan of thriller movies but I love sci-fi movies."},
+    {"role": "assistant", "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future."}
+];
+await memory.add(messages, { userId: 'alex' });
+```
+
+</CodeGroup>
+
 ## Advanced Usage with Sarvam-Specific Features
 
 ```python

docs/components/llms/models/together.mdx

@@ -1,13 +1,15 @@
 ---
 title: Together
-description: "Configure Together AI as an LLM provider in Mem0 with API key setup and Mixtral model configuration."
+description: "Configure Together AI as an LLM provider in Mem0 with API key setup and optional custom endpoint configuration."
 ---
 
-To use Together LLM models, you have to set the `TOGETHER_API_KEY` environment variable. You can obtain the Together API key from their [Account settings page](https://api.together.xyz/settings/api-keys).
+To use Together LLM models, you have to set the `TOGETHER_API_KEY` environment variable. You can obtain the Together API key from their [Account settings page](https://api.together.ai/settings/projects/~current/api-keys).
+In the TypeScript SDK, you can optionally set `TOGETHER_API_BASE` or pass `baseURL` in the config (defaults to `https://api.together.ai/v1`).
 
 ## Usage
 
-```python
+<CodeGroup>
+```python Python
 import os
 from mem0 import Memory
 
@@ -18,7 +20,7 @@ config = {
     "llm": {
         "provider": "together",
         "config": {
-            "model": "mistralai/Mixtral-8x7B-Instruct-v0.1",
+            "model": "MiniMaxAI/MiniMax-M3",
             "temperature": 0.2,
             "max_tokens": 2000,
         }
@@ -29,12 +31,68 @@ m = Memory.from_config(config)
 messages = [
     {"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
     {"role": "assistant", "content": "How about thriller movies? They can be quite engaging."},
-    {"role": "user", "content": "I’m not a big fan of thriller movies but I love sci-fi movies."},
+    {"role": "user", "content": "I'm not a big fan of thriller movies but I love sci-fi movies."},
     {"role": "assistant", "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future."}
 ]
 m.add(messages, user_id="alice", metadata={"category": "movies"})
 ```
 
+```typescript TypeScript
+import { Memory } from 'mem0ai/oss';
+
+const config = {
+  llm: {
+    provider: 'together',
+    config: {
+      apiKey: process.env.TOGETHER_API_KEY || '',
+      model: 'MiniMaxAI/MiniMax-M3',
+      temperature: 0.2,
+      maxTokens: 2000,
+    },
+  },
+};
+
+const memory = new Memory(config);
+const messages = [
+  { role: "user", content: "I'm planning to watch a movie tonight. Any recommendations?" },
+  { role: "assistant", content: "How about thriller movies? They can be quite engaging." },
+  { role: "user", content: "I'm not a big fan of thriller movies but I love sci-fi movies." },
+  { role: "assistant", content: "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future." },
+];
+await memory.add(messages, { userId: 'alice', metadata: { category: 'movies' } });
+```
+</CodeGroup>
+
+You can also configure the API base URL in the config:
+
+<CodeGroup>
+```python Python
+config = {
+    "llm": {
+        "provider": "together",
+        "config": {
+            "model": "MiniMaxAI/MiniMax-M3",
+            "api_key": "your-api-key"
+        }
+    }
+}
+```
+
+```typescript TypeScript
+const config = {
+  llm: {
+    provider: "together",
+    config: {
+      model: "MiniMaxAI/MiniMax-M3",
+      baseURL: "https://api.together.ai/v1",
+      apiKey: "your-api-key",
+    },
+  },
+};
+```
+
+</CodeGroup>
+
 ## Config
 
-All available parameters for the `together` config are present in [Master List of All Params in Config](../config).
+All available parameters for the `together` config are present in [Master List of All Params in Config](../config).

docs/components/llms/models/vllm.mdx

@@ -25,7 +25,8 @@ description: "Configure vLLM as an LLM provider in Mem0 for high-performance loc
 
 ## Usage
 
-```python
+<CodeGroup>
+```python Python
 import os
 from mem0 import Memory
 
@@ -53,6 +54,46 @@ messages = [
 m.add(messages, user_id="alice", metadata={"category": "movies"})
 ```
 
+```typescript TypeScript
+import { Memory } from "mem0ai/oss";
+
+const config = {
+  llm: {
+    provider: "vllm",
+    config: {
+      model: "Qwen/Qwen2.5-32B-Instruct",
+      baseURL: "http://localhost:8000/v1",
+      apiKey: process.env.VLLM_API_KEY || "vllm-api-key",
+      temperature: 0.1,
+      maxTokens: 2000,
+    },
+  },
+};
+
+const memory = new Memory(config);
+const messages = [
+  {
+    role: "user",
+    content: "I'm planning to watch a movie tonight. Any recommendations?",
+  },
+  {
+    role: "assistant",
+    content: "How about thriller movies? They can be quite engaging.",
+  },
+  {
+    role: "user",
+    content: "I'm not a big fan of thrillers, but I love sci-fi movies.",
+  },
+  {
+    role: "assistant",
+    content: "Got it! I'll avoid thrillers and suggest sci-fi movies instead.",
+  },
+];
+await memory.add(messages, { userId: "alice", metadata: { category: "movies" } });
+```
+
+</CodeGroup>
+
 ## Configuration Parameters
 
 | Parameter       | Description                       | Default                       | Environment Variable |