test(plugins): a removed plugin setting gives way to a later mem0 init key

test(plugins): assert the generated DATA_DIR_NAME in the build tests
fix(plugins): give the MCP server the hooks' data dir, release 0.3.4
2026-09-25 11:54:58 +05:30 · 2026-09-25 11:20:52 +05:30 · 2026-09-25 11:11:37 +05:30 · 2026-09-25 10:24:04 +05:30 · 2026-09-25 09:58:06 +05:30 · 2026-09-24 22:14:28 +05:30
286 changed files with 15693 additions and 3807 deletions
@@ -12,7 +12,7 @@
      "name": "mem0",
      "source": "./integrations/claude-code-plugin",
      "description": "Cross-session memory and token savings for coding agents.",
-      "version": "0.3.1"
+      "version": "0.3.4"
    }
  ]
 }
@@ -12,7 +12,7 @@
      "name": "mem0",
      "source": "./integrations/cursor-plugin",
      "description": "Cross-session memory and token savings for coding agents.",
-      "version": "0.3.1"
+      "version": "0.3.4"
    }
  ]
 }
@@ -32,6 +32,9 @@ jobs:
      - name: Type check
        run: bun run type-check

+      - name: Test
+        run: bun test
+
      - name: Build
        run: bun run build

@@ -5,7 +5,7 @@
    {
      "id": "mem0",
      "displayName": "Mem0",
-      "version": "0.3.1",
+      "version": "0.3.4",
      "description": "Cross-session memory and token savings for coding agents.",
      "homepage": "https://mem0.ai",
      "keywords": ["memory", "personalization", "mcp", "semantic-search"],
@@ -1,6 +1,6 @@
 {
  "name": "@mem0/cli",
-  "version": "0.2.13",
+  "version": "0.2.14",
  "description": "The official CLI for mem0 — the memory layer for AI agents",
  "type": "module",
  "bin": {
@@ -41,7 +41,7 @@
    "tsup": "^8.0.0",
    "tsx": "^4.7.0",
    "vite": "^6.0.0",
-    "vitest": "^4.1.0",
+    "vitest": "^4.1.11",
    "@biomejs/biome": "^1.7.0",
    "@types/node": "^20.0.0"
  },
@@ -51,8 +51,8 @@ importers:
        specifier: ^6.0.0
        version: 6.4.3(@types/node@20.19.37)(tsx@4.21.0)
      vitest:
-        specifier: ^4.1.0
-        version: 4.1.8(@types/node@20.19.37)(vite@6.4.3(@types/node@20.19.37)(tsx@4.21.0))
+        specifier: ^4.1.11
+        version: 4.1.11(@types/node@20.19.37)(vite@6.4.3(@types/node@20.19.37)(tsx@4.21.0))

 packages:

@@ -439,11 +439,11 @@ packages:
  '@types/node@20.19.37':
    resolution: {integrity: sha512-8kzdPJ3FsNsVIurqBs7oodNnCEVbni9yUEkaHbgptDACOPW04jimGagZ51E6+lXUwJjgnBw+hyko/lkFWCldqw==}

-  '@vitest/expect@4.1.8':
-    resolution: {integrity: sha512-h3nDO677RDLEGlBxyQ5CW8RlMThSKSRLUePLOx09gNIWRL40edgA1GCZSZgf1W55MFAG6/Sw14KeaAnqv0NKdQ==}
+  '@vitest/expect@4.1.11':
+    resolution: {integrity: sha512-VX2x5vNJXET47KAFzwERI+KRMtTTCSWTfSMKsW7JsUsXV4psq++e3DvZpuTDOpHcxytiDs6p2nhVb2tVDiiUYw==}

-  '@vitest/mocker@4.1.8':
-    resolution: {integrity: sha512-LEiN/xe4OSIbKe9HQIp5OC24agGD9J5CnmMgsLohVVoOPWL9a2sBoR6VBx43jQZb7Kr1l4RCuyCJzcAa0+dojw==}
+  '@vitest/mocker@4.1.11':
+    resolution: {integrity: sha512-2XJVD55d1o5AZous5CCGKS74g/riOj9odEt2bQpCVZeblHyHdnMeFl4jl0XjU21stf4mbjUkew2eXQZt65g5CQ==}
    peerDependencies:
      msw: ^2.4.9
      vite: ^6.0.0 || ^7.0.0 || ^8.0.0
@@ -453,20 +453,20 @@ packages:
      vite:
        optional: true

-  '@vitest/pretty-format@4.1.8':
-    resolution: {integrity: sha512-9GasEBxpZ1VYIpqHf/0+YGg121uSNwCKOJqIrTwWP/TB7DmFCiaBpNl3aPZzoLWfWkuqhbH8vJIVobZkvdo2cA==}
+  '@vitest/pretty-format@4.1.11':
+    resolution: {integrity: sha512-yiZzPbGTS9Sr/JpFl8zHrcIkAofNbFV6k21vIgQN/cY/oxZeXhJv5sc/MBJ5jFKWmWs+oJHw0UXLZjmf931+Vw==}

-  '@vitest/runner@4.1.8':
-    resolution: {integrity: sha512-EmVxeBAfMJvycdjd6Hm+RbFBbA9fKvo0Kx37hNpBYoYeavH3RNsBXWDooR1mgD52dCrxIIuP7UotpfiwOikvcg==}
+  '@vitest/runner@4.1.11':
+    resolution: {integrity: sha512-LztvUgdwMNJMIkj3hQnnxiC2Xy1zNxq928W/xhjCLaNCzqTZOudjwbQf6v9IntZGPw132i2Lq2rgTRZHD3JHNw==}

-  '@vitest/snapshot@4.1.8':
-    resolution: {integrity: sha512-acfZboRmAIf05DEKcBQy33VXojFJjtUdLyo7oOmV9kebb2xdU01UknNiPuPZoJZQyO7DF0gZdTGTpeAzET9QPQ==}
+  '@vitest/snapshot@4.1.11':
+    resolution: {integrity: sha512-pN7ikn1ON7h8ee4gIAp4AzyK+zBtJPzVbqOgu5LCEh4VaJVbPQcgYQYJIMGQPXVeJJq1fnfazis7a5pFNPahog==}

-  '@vitest/spy@4.1.8':
-    resolution: {integrity: sha512-6EevtBp6OZOPF7bmz36HrGMeP3txgVSrgebWxHOafDXGkhIzfXK14f8KF6MuFfgXXUeHxmpD3BQxkV00/3s5mA==}
+  '@vitest/spy@4.1.11':
+    resolution: {integrity: sha512-apNa/prQy2qCeywhnixOHPRCgGNhvg7T4Dapfl1GahLp/R+uhBm5cPyFoNVyqsNd2h1nJxL6BqqdIjiABL60YA==}

-  '@vitest/utils@4.1.8':
-    resolution: {integrity: sha512-uOJamYALNhfJ6iolExyQM40yIQwDqYnkKtQ5VCiSe17E33H0aQ/u+1GlRuz4LZBk6Mm3sg90G9hEbmEt37C1Zg==}
+  '@vitest/utils@4.1.11':
+    resolution: {integrity: sha512-zTCVGpyFsGWBhllOyKlTw/vnr6D9qxsfSDyfbyZmTyjHw5N/VuvzHpHoQjm2ZJzn4RJgx5w4r7V0er69CmLgPQ==}

  acorn@8.16.0:
    resolution: {integrity: sha512-UVJyE9MttOsBQIDKw1skb9nAwQuR5wuGD3+82K6JgJlm/Y+KI92oNsMNGZCYdDsVtRHSak0pcV5Dno5+4jh9sw==}
@@ -910,20 +910,20 @@ packages:
      yaml:
        optional: true

-  vitest@4.1.8:
-    resolution: {integrity: sha512-flY6ScbCIt9HThs+C5HS7jvGOB560DJtk/Z15IQROTA6zEy49Nh8T/dofWTQL+n3vswqn87sbJNiuqw1SDp5Ig==}
+  vitest@4.1.11:
+    resolution: {integrity: sha512-fhACrNXUidIbGSBr5FlbuBkO7VWC1ZyLl0DO4CU2DrQoAPxX84Ysxs+HeGQpii5lZWV1Q4gBZTTu49mF+A6Edw==}
    engines: {node: ^20.0.0 || ^22.0.0 || >=24.0.0}
    hasBin: true
    peerDependencies:
      '@edge-runtime/vm': '*'
      '@opentelemetry/api': ^1.9.0
      '@types/node': ^20.0.0 || ^22.0.0 || >=24.0.0
-      '@vitest/browser-playwright': 4.1.8
-      '@vitest/browser-preview': 4.1.8
-      '@vitest/browser-webdriverio': 4.1.8
-      '@vitest/coverage-istanbul': 4.1.8
-      '@vitest/coverage-v8': 4.1.8
-      '@vitest/ui': 4.1.8
+      '@vitest/browser-playwright': 4.1.11
+      '@vitest/browser-preview': 4.1.11
+      '@vitest/browser-webdriverio': 4.1.11
+      '@vitest/coverage-istanbul': 4.1.11
+      '@vitest/coverage-v8': 4.1.11
+      '@vitest/ui': 4.1.11
      happy-dom: '*'
      jsdom: '*'
      vite: ^6.0.0 || ^7.0.0 || ^8.0.0
@@ -1186,44 +1186,44 @@ snapshots:
    dependencies:
      undici-types: 6.21.0

-  '@vitest/expect@4.1.8':
+  '@vitest/expect@4.1.11':
    dependencies:
      '@standard-schema/spec': 1.1.0
      '@types/chai': 5.2.3
-      '@vitest/spy': 4.1.8
-      '@vitest/utils': 4.1.8
+      '@vitest/spy': 4.1.11
+      '@vitest/utils': 4.1.11
      chai: 6.2.2
      tinyrainbow: 3.1.0

-  '@vitest/mocker@4.1.8(vite@6.4.3(@types/node@20.19.37)(tsx@4.21.0))':
+  '@vitest/mocker@4.1.11(vite@6.4.3(@types/node@20.19.37)(tsx@4.21.0))':
    dependencies:
-      '@vitest/spy': 4.1.8
+      '@vitest/spy': 4.1.11
      estree-walker: 3.0.3
      magic-string: 0.30.21
    optionalDependencies:
      vite: 6.4.3(@types/node@20.19.37)(tsx@4.21.0)

-  '@vitest/pretty-format@4.1.8':
+  '@vitest/pretty-format@4.1.11':
    dependencies:
      tinyrainbow: 3.1.0

-  '@vitest/runner@4.1.8':
+  '@vitest/runner@4.1.11':
    dependencies:
-      '@vitest/utils': 4.1.8
+      '@vitest/utils': 4.1.11
      pathe: 2.0.3

-  '@vitest/snapshot@4.1.8':
+  '@vitest/snapshot@4.1.11':
    dependencies:
-      '@vitest/pretty-format': 4.1.8
-      '@vitest/utils': 4.1.8
+      '@vitest/pretty-format': 4.1.11
+      '@vitest/utils': 4.1.11
      magic-string: 0.30.21
      pathe: 2.0.3

-  '@vitest/spy@4.1.8': {}
+  '@vitest/spy@4.1.11': {}

-  '@vitest/utils@4.1.8':
+  '@vitest/utils@4.1.11':
    dependencies:
-      '@vitest/pretty-format': 4.1.8
+      '@vitest/pretty-format': 4.1.11
      convert-source-map: 2.0.0
      tinyrainbow: 3.1.0

@@ -1627,15 +1627,15 @@ snapshots:
      fsevents: 2.3.3
      tsx: 4.21.0

-  vitest@4.1.8(@types/node@20.19.37)(vite@6.4.3(@types/node@20.19.37)(tsx@4.21.0)):
+  vitest@4.1.11(@types/node@20.19.37)(vite@6.4.3(@types/node@20.19.37)(tsx@4.21.0)):
    dependencies:
-      '@vitest/expect': 4.1.8
-      '@vitest/mocker': 4.1.8(vite@6.4.3(@types/node@20.19.37)(tsx@4.21.0))
-      '@vitest/pretty-format': 4.1.8
-      '@vitest/runner': 4.1.8
-      '@vitest/snapshot': 4.1.8
-      '@vitest/spy': 4.1.8
-      '@vitest/utils': 4.1.8
+      '@vitest/expect': 4.1.11
+      '@vitest/mocker': 4.1.11(vite@6.4.3(@types/node@20.19.37)(tsx@4.21.0))
+      '@vitest/pretty-format': 4.1.11
+      '@vitest/runner': 4.1.11
+      '@vitest/snapshot': 4.1.11
+      '@vitest/spy': 4.1.11
+      '@vitest/utils': 4.1.11
      es-module-lexer: 2.1.0
      expect-type: 1.3.0
      magic-string: 0.30.21
@@ -31,7 +31,8 @@ export class PlatformBackend implements Backend {
 		this.headers = {
 			Authorization: `Token ${config.apiKey}`,
 			"Content-Type": "application/json",
-			"X-Mem0-Source": "cli",
+			"X-Mem0-Source": "CLI",
+			"X-Mem0-Client": `mem0-cli-node/${CLI_VERSION}`,
 			"X-Mem0-Client-Language": "node",
 			"X-Mem0-Client-Version": CLI_VERSION,
 		};
@@ -4,7 +4,7 @@ build-backend = "hatchling.build"

 [project]
 name = "mem0-cli"
-version = "0.2.12"
+version = "0.2.13"
 description = "The official CLI for mem0 — the memory layer for AI agents"
 readme = "README.md"
 license = "Apache-2.0"
@@ -1,3 +1,3 @@
 """mem0 CLI — the command-line interface for the mem0 memory layer."""

-__version__ = "0.2.12"
+__version__ = "0.2.13"
@@ -27,7 +27,8 @@ class PlatformBackend(Backend):
            headers={
                "Authorization": f"Token {config.api_key}",
                "Content-Type": "application/json",
-                "X-Mem0-Source": "cli",
+                "X-Mem0-Source": "CLI",
+                "X-Mem0-Client": f"mem0-cli-python/{__version__}",
                "X-Mem0-Client-Language": "python",
                "X-Mem0-Client-Version": __version__,
            },
@@ -1,7 +1,6 @@
 ---
-title: "Overview"
-seo:
-  title: "API Reference Overview - Mem0"
+title: "API Reference Overview"
+sidebarTitle: "Overview"
 icon: "terminal"
 iconType: "solid"
 description: "REST APIs for memory management, search, and entity operations"
@@ -1,7 +1,6 @@
 ---
-title: 'Delete Memory'
-seo:
-  title: "Delete Memory API Endpoint - Mem0"
+title: "Delete Memory API Endpoint"
+sidebarTitle: "Delete Memory"
 description: "Delete a single memory by its unique memory ID from the Mem0 platform using the DELETE endpoint."
 openapi: delete /v1/memories/{memory_id}/
 ---
@@ -1,7 +1,6 @@
 ---
-title: 'Update Memory'
-seo:
-  title: "Update Memory API Endpoint - Mem0"
+title: "Update Memory API Endpoint"
+sidebarTitle: "Update Memory"
 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}/
 ---
@@ -1,7 +1,6 @@
 ---
-title: 'Add Member'
-seo:
-  title: "Add Organization Member API Endpoint - Mem0"
+title: "Add Organization Member API Endpoint"
+sidebarTitle: "Add Member"
 description: "Add a new member to an organization with a specified role such as READER or OWNER access level."
 openapi: post /api/v1/orgs/organizations/{org_id}/members/
 ---
@@ -1,7 +1,6 @@
 ---
-title: 'Get Members'
-seo:
-  title: "Get Organization Members API Endpoint - Mem0"
+title: "Get Organization Members API Endpoint"
+sidebarTitle: "Get Members"
 description: "Retrieve a list of all members belonging to a specific organization on the Mem0 platform."
 openapi: get /api/v1/orgs/organizations/{org_id}/members/
 ---
@@ -0,0 +1,5 @@
+---
+title: 'Generate Profiles'
+description: "Start one generation: sample a few entities, or build one for a single entity."
+openapi: post /v2/profiles/jobs/
+---
@@ -0,0 +1,5 @@
+---
+title: 'Get Generation Job'
+description: "Read the progress of a generation, and whether it finished."
+openapi: get /v2/profiles/jobs/{job_id}/
+---
@@ -0,0 +1,5 @@
+---
+title: 'Get Profile Settings'
+description: "Retrieve the profile schema, custom instructions, and enabled flag for the current project."
+openapi: get /v2/profiles/settings/
+---
@@ -0,0 +1,5 @@
+---
+title: 'Get Profile'
+description: "Retrieve the structured profile for a user, with a status describing whether generation has completed."
+openapi: get /v2/entities/{entity_type}/{entity_id}/profile/
+---
@@ -0,0 +1,5 @@
+---
+title: 'Update Profile Settings'
+description: "Set the JSON Schema, custom instructions, or enabled flag that control profile generation for the project."
+openapi: post /v2/profiles/settings/
+---
@@ -1,7 +1,6 @@
 ---
-title: 'Add Member'
-seo:
-  title: "Add Project Member API Endpoint - Mem0"
+title: "Add Project Member API Endpoint"
+sidebarTitle: "Add Member"
 description: "Add a new member to a project with a specified role such as READER or OWNER access level."
 openapi: post /api/v1/orgs/organizations/{org_id}/projects/{project_id}/members/
 ---
@@ -1,7 +1,6 @@
 ---
-title: 'Get Members'
-seo:
-  title: "Get Project Members API Endpoint - Mem0"
+title: "Get Project Members API Endpoint"
+sidebarTitle: "Get Members"
 description: "Retrieve a list of all members belonging to a specific project on the Mem0 platform."
 openapi: get /api/v1/orgs/organizations/{org_id}/projects/{project_id}/members/
 ---
@@ -7,6 +7,24 @@ mode: "wide"
 <Tabs>
 <Tab title="Python">

+<Update label="2026-09-23" description="v2.2.0">
+
+**New Features:**
+- **Client:** Add User Profiles to `MemoryClient` and `AsyncMemoryClient`: `get_profile()`, `generate_profile()`, `get_profile_settings()`, `update_profile_settings()`, `sample_profiles()`, and `get_profile_job()`. A profile is a structured, always-current JSON summary of one user, shaped by a JSON Schema you configure per project and filled by an LLM from that user's memories. Generation is asynchronous. Every job POST carries an `Idempotency-Key`; to retry a lost request without starting a second job, pass the same `idempotency_key` on each attempt ([#7340](https://github.com/mem0ai/mem0/pull/7340))
+
+**Bug Fixes:**
+- **Vector Stores:** Guard against `None` timestamps in the Valkey vector store's `insert()` and `update()` paths. `created_at` and `updated_at` fields that were present in the payload but set to `None` previously passed the `"created_at" not in payload` / `"updated_at" in payload` checks and raised `TypeError` when `datetime.fromisoformat()` received `None`. Both paths now use `.get()` with a truthiness check so `None` values fall through to the default, matching the Redis provider's behavior ([#6993](https://github.com/mem0ai/mem0/pull/6993))
+
+</Update>
+
+<Update label="2026-09-18" description="v2.1.0">
+
+**Improvements:**
+- **Client:** Requests now carry three surface-identity headers so the platform can tell which product made a call. `X-Mem0-Source` names the surface and `X-Application` the host app it runs inside, both set-once so a wrapper that already declared its identity keeps it. `X-Mem0-Client` is append-only and carries `name/version` per layer, outermost first, so a plugin calling this SDK reports the whole chain rather than only the last speaker. `MEM0_SOURCE`, `MEM0_APPLICATION` and `MEM0_CLIENT_STACK` set them from the environment for wrappers that cannot pass options ([#7326](https://github.com/mem0ai/mem0/pull/7326))
+- **Client:** The client stack is bounded by dropping whole entries rather than slicing characters, and this SDK's own entry is the reserved one. Truncating the joined string could sever an identifier mid-name and the platform parsed the fragment as a real client ([#7326](https://github.com/mem0ai/mem0/pull/7326))
+
+</Update>
+
 <Update label="2026-09-02" description="v2.0.20">

 **Improvements:**
@@ -174,7 +192,7 @@ mode: "wide"
 <Update label="2026-06-24" description="v2.0.8">

 **New Features:**
- **Embeddings:** Add native `embed_batch` to five embedders: LM Studio, Together, HuggingFace, Vertex AI, and Google GenAI: for batched embedding requests ([#5609](https://github.com/mem0ai/mem0/pull/5609))
+- **Embeddings:** Add native `embed_batch` to five embedders for batched embedding requests: LM Studio, Together, HuggingFace, Vertex AI, and Google GenAI ([#5609](https://github.com/mem0ai/mem0/pull/5609))

 **Bug Fixes:**
 - **Core:** Guard against malformed `image_url` entries in `parse_vision_messages` to prevent crashes ([#5631](https://github.com/mem0ai/mem0/pull/5631))
@@ -964,7 +982,7 @@ See the [OSS v2 to v3 migration guide](https://docs.mem0.ai/migration/oss-v2-to-
 **New Features:**
 - **OpenMemory:** Added OpenMemory support
 - **Neo4j:** Added weights to Neo4j model
- **AWS:** Added support for Opsearch Serverless
+- **AWS:** Added support for OpenSearch Serverless
 - **Examples:** Added ElizaOS Example

 **Improvements:**
@@ -1227,6 +1245,21 @@ See the [OSS v2 to v3 migration guide](https://docs.mem0.ai/migration/oss-v2-to-

 <Tab title="TypeScript">

+<Update label="2026-09-23" description="v3.3.0">
+
+**New Features:**
+- **Client:** Add User Profiles to `MemoryClient`: `getProfile()`, `generateProfile()`, `getProfileSettings()`, `updateProfileSettings()`, `sampleProfiles()`, and `getProfileJob()`. A profile is a structured, always-current JSON summary of one user, shaped by a JSON Schema you configure per project and filled by an LLM from that user's memories. Generation is asynchronous. Every job POST carries an `Idempotency-Key`; to retry a lost request without starting a second job, pass the same `idempotencyKey` on each attempt ([#7340](https://github.com/mem0ai/mem0/pull/7340))
+
+</Update>
+
+<Update label="2026-09-18" description="v3.2.0">
+
+**Improvements:**
+- **Client:** Requests now carry `X-Mem0-Source`, `X-Application` and `X-Mem0-Client`, matching the Python SDK. The first two are set-once so an outer wrapper keeps its identity; the third is append-only and reports the whole layer chain. Read from `MEM0_SOURCE`, `MEM0_APPLICATION` and `MEM0_CLIENT_STACK` when set ([#7326](https://github.com/mem0ai/mem0/pull/7326))
+- **Client:** The SDK version in `X-Mem0-Client` is injected at build time rather than hardcoded, so it cannot go stale at the next release ([#7326](https://github.com/mem0ai/mem0/pull/7326))
+
+</Update>
+
 <Update label="2026-09-02" description="v3.1.8">

 **Improvements:**
@@ -1864,6 +1897,13 @@ See the [OSS v2 to v3 migration guide](https://docs.mem0.ai/migration/oss-v2-to-

 <Tab title="CLI">

+<Update label="2026-09-18" description="Python v0.2.13 / Node v0.2.14">
+
+**Improvements:**
+- **Client:** Requests now carry the three surface-identity headers (`X-Mem0-Source`, `X-Application`, `X-Mem0-Client`) introduced in the Python and TypeScript SDKs, so the platform can attribute calls made through the CLI to the correct surface and version ([#7326](https://github.com/mem0ai/mem0/pull/7326))
+
+</Update>
+
 <Update label="2026-08-24" description="Python v0.2.12 / Node v0.2.13">

 **New Features:**
@@ -2060,6 +2100,16 @@ A full-featured command-line interface for Mem0, available in both Python and No
 <Tabs>
 <Tab title="Mem0 Plugin">

+<Update label="2026-09-25" description="Portable agent plugin v0.3.4">
+
+**Fixes:**
+- **Auth:** Falls back to the API key `mem0 init` saved in `~/.mem0/config.json` when no key is set in the plugin settings or `MEM0_API_KEY`, so search and the status check no longer report a missing key after `mem0 init` ([#7449](https://github.com/mem0ai/mem0/pull/7449))
+- **Auth:** A plugin setting that reaches the plugin as an unexpanded `${api_key}` or `${user_id}` placeholder is treated as unset. It is no longer sent as the API key, cached to disk, or used as the user ID ([#7449](https://github.com/mem0ai/mem0/pull/7449))
+- **State:** The `search_memories` MCP server now keeps its state in `~/.mem0/coding-agent-plugin`, the same directory the status, pause, resume and forget skills use, instead of `~/.mem0/mem0-plugin` ([#7449](https://github.com/mem0ai/mem0/pull/7449))
+- **Packaging:** `PLUGIN_VERSION` bumped to `0.3.4`, so the `mem0-plugin/<version>` wire header and `plugin_version` telemetry field identify builds with this fix ([#7449](https://github.com/mem0ai/mem0/pull/7449))
+
+</Update>
+
 <Update label="2026-09-08" description="Shared agent plugin runtime">

 **Changed:**
@@ -2076,7 +2126,7 @@ A full-featured command-line interface for Mem0, available in both Python and No
 - New Git repository writes use a hash of the remote identity in `agent_id`. Search and explicit shared-memory deletion include both current and legacy repository IDs within the repository's `app_id`. Existing memories are not rewritten. Legacy IDs retain their original ambiguity for matching owner/repository names on different Git hosts.

 **Packaging:**
- Claude Code, Cursor, Codex, Kimi, Antigravity, and the portable Python bundle are versioned at `0.3.1`. OpenCode, Pi Agent, and DeepSeek Harness are `0.3.0`; OpenClaw is `1.1.0`. Each host's changes and upgrade considerations are listed in its tab.
+- Claude Code, Cursor, Codex, Kimi, Antigravity, and the portable Python bundle are versioned at `0.3.1`. OpenCode and DeepSeek Harness are `0.3.0`; Pi Agent is `0.3.0`; OpenClaw is `1.1.0`. Each host's changes and upgrade considerations are listed in its tab.
 - Python and TypeScript CI run their respective runtime suites. Package checks build the installable artifacts, check generated-file consistency, and reject TypeScript output that still imports monorepo source.

 [#7203](https://github.com/mem0ai/mem0/pull/7203)
@@ -2371,6 +2421,37 @@ Initial release of the Mem0 plugin for Claude Code and Cursor, followed by Codex

 <Tab title="Claude Code">

+<Update label="2026-09-25" description="Claude Code plugin v0.3.4">
+
+**Fixes:**
+- **Auth:** Falls back to the API key `mem0 init` saved in `~/.mem0/config.json` when no key is set in the plugin settings or `MEM0_API_KEY`, so search and the status check no longer report a missing key after `mem0 init` ([#7449](https://github.com/mem0ai/mem0/pull/7449))
+- **Auth:** A plugin setting that reaches the plugin as an unexpanded `${api_key}` or `${user_id}` placeholder is treated as unset. It is no longer sent as the API key, cached to disk, or used as the user ID ([#7449](https://github.com/mem0ai/mem0/pull/7449))
+- **Packaging:** `PLUGIN_VERSION` bumped to `0.3.4`, so the `mem0-plugin/<version>` wire header and `plugin_version` telemetry field identify builds with this fix ([#7449](https://github.com/mem0ai/mem0/pull/7449))
+
+</Update>
+
+<Update label="2026-09-23" description="Claude Code plugin v0.3.3">
+
+**Improvements:**
+- **Search:** The `search_memories` tool description no longer tells the agent to call it before answering anything that could depend on prior context. It now asks for a search before repeating investigation or when earlier decisions, fixes, commands, or results may help, which reduces unnecessary searches ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+- **Sidekick:** Sidekick searches memories when earlier sessions could help, instead of before every answer ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+- **Extraction:** Repository memory instructions are shorter. They no longer ask for a dedicated memory for each command that failed and was then fixed, and no longer carry separate rules against saving personal preferences or memories that only name the repository, branch, or directory ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+- **Search skill:** `/search` no longer describes categories as best-effort labels or asks for a retry without the category ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+- **Packaging:** `PLUGIN_VERSION` bumped to `0.3.3`, so the `mem0-plugin/<version>` wire header and `plugin_version` telemetry field identify builds with these prompts ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+
+</Update>
+
+<Update label="2026-09-18" description="Claude Code plugin v0.3.2">
+
+**Improvements:**
+- **Telemetry:** `PLUGIN_VERSION` bumped to `0.3.2`. The `mem0-plugin/<version>` wire header and `plugin_version` telemetry field now reflect the fixes from #7322 through #7358 ([#7373](https://github.com/mem0ai/mem0/pull/7373))
+- **Telemetry:** Events are no longer delivered twice, no longer lose parked events on flush, and now attribute each event to the plugin that produced it ([#7323](https://github.com/mem0ai/mem0/pull/7323), [#7324](https://github.com/mem0ai/mem0/pull/7324), [#7358](https://github.com/mem0ai/mem0/pull/7358))
+
+**Changes:**
+- **Sidekick:** Sidekick is now available only in Claude Code, with Sonnet, worktree isolation, and parent memories.
+
+</Update>
+
 <Update label="2026-09-08" description="Claude Code plugin v0.3.1">

 **Changed:**
@@ -2390,6 +2471,37 @@ Initial release of the Mem0 plugin for Claude Code and Cursor, followed by Codex

 <Tab title="Cursor">

+<Update label="2026-09-25" description="Cursor plugin v0.3.4">
+
+**Fixes:**
+- **Auth:** An API key set in the Cursor plugin settings now reaches the `search_memories` MCP server. The server looked for the cached key in `~/.mem0/mem0-plugin` while the hooks cached it in `~/.mem0/cursor-plugin`, so search asked for auth whenever Cursor did not pass the setting to the MCP server directly ([#7449](https://github.com/mem0ai/mem0/pull/7449))
+- **Auth:** Falls back to the API key `mem0 init` saved in `~/.mem0/config.json` when no key is set in the plugin settings or `MEM0_API_KEY`, so search and the status check no longer report a missing key after `mem0 init` ([#7449](https://github.com/mem0ai/mem0/pull/7449))
+- **Auth:** A plugin setting that reaches the plugin as an unexpanded `${api_key}` or `${user_id}` placeholder is treated as unset. It is no longer sent as the API key, cached to disk, or used as the user ID ([#7449](https://github.com/mem0ai/mem0/pull/7449))
+- **Packaging:** `PLUGIN_VERSION` bumped to `0.3.4`, so the `mem0-plugin/<version>` wire header and `plugin_version` telemetry field identify builds with this fix ([#7449](https://github.com/mem0ai/mem0/pull/7449))
+
+</Update>
+
+<Update label="2026-09-23" description="Cursor plugin v0.3.3">
+
+**Improvements:**
+- **Search:** The `search_memories` tool description no longer tells the agent to call it before answering anything that could depend on prior context. It now asks for a search before repeating investigation or when earlier decisions, fixes, commands, or results may help, which reduces unnecessary searches ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+- **Extraction:** Repository memory instructions are shorter. They no longer ask for a dedicated memory for each command that failed and was then fixed, and no longer carry separate rules against saving personal preferences or memories that only name the repository, branch, or directory ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+- **Search skill:** `/search` no longer describes categories as best-effort labels or asks for a retry without the category ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+- **Packaging:** `PLUGIN_VERSION` bumped to `0.3.3`, so the `mem0-plugin/<version>` wire header and `plugin_version` telemetry field identify builds with these prompts ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+
+</Update>
+
+<Update label="2026-09-18" description="Cursor plugin v0.3.2">
+
+**Improvements:**
+- **Telemetry:** `PLUGIN_VERSION` bumped to `0.3.2`. The `mem0-plugin/<version>` wire header and `plugin_version` telemetry field now reflect the fixes from #7322 through #7358 ([#7373](https://github.com/mem0ai/mem0/pull/7373))
+- **Telemetry:** Events are no longer delivered twice, no longer lose parked events on flush, and now attribute each event to the plugin that produced it ([#7323](https://github.com/mem0ai/mem0/pull/7323), [#7324](https://github.com/mem0ai/mem0/pull/7324), [#7358](https://github.com/mem0ai/mem0/pull/7358))
+
+**Changes:**
+- **Sidekick:** Removes Sidekick and its start/stop hooks. Memory capture, search, and six skills remain available.
+
+</Update>
+
 <Update label="2026-09-08" description="Cursor plugin v0.3.1">

 **Changed:**
@@ -2409,6 +2521,35 @@ Initial release of the Mem0 plugin for Claude Code and Cursor, followed by Codex

 <Tab title="Codex">

+<Update label="2026-09-25" description="Codex plugin v0.3.4">
+
+**Fixes:**
+- **Auth:** Falls back to the API key `mem0 init` saved in `~/.mem0/config.json` when `MEM0_API_KEY` is not set, so search and the status check no longer report a missing key after `mem0 init` ([#7449](https://github.com/mem0ai/mem0/pull/7449))
+- **Packaging:** `PLUGIN_VERSION` bumped to `0.3.4`, so the `mem0-plugin/<version>` wire header and `plugin_version` telemetry field identify builds with this fix ([#7449](https://github.com/mem0ai/mem0/pull/7449))
+
+</Update>
+
+<Update label="2026-09-23" description="Codex plugin v0.3.3">
+
+**Improvements:**
+- **Search:** The `search_memories` tool description no longer tells the agent to call it before answering anything that could depend on prior context. It now asks for a search before repeating investigation or when earlier decisions, fixes, commands, or results may help, which reduces unnecessary searches ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+- **Extraction:** Repository memory instructions are shorter. They no longer ask for a dedicated memory for each command that failed and was then fixed, and no longer carry separate rules against saving personal preferences or memories that only name the repository, branch, or directory ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+- **Search skill:** `/search` no longer describes categories as best-effort labels or asks for a retry without the category ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+- **Packaging:** `PLUGIN_VERSION` bumped to `0.3.3`, so the `mem0-plugin/<version>` wire header and `plugin_version` telemetry field identify builds with these prompts ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+
+</Update>
+
+<Update label="2026-09-18" description="Codex plugin v0.3.2">
+
+**Improvements:**
+- **Telemetry:** `PLUGIN_VERSION` bumped to `0.3.2`. The `mem0-plugin/<version>` wire header and `plugin_version` telemetry field now reflect the fixes from #7322 through #7358 ([#7373](https://github.com/mem0ai/mem0/pull/7373))
+- **Telemetry:** Events are no longer delivered twice, no longer lose parked events on flush, and now attribute each event to the plugin that produced it ([#7323](https://github.com/mem0ai/mem0/pull/7323), [#7324](https://github.com/mem0ai/mem0/pull/7324), [#7358](https://github.com/mem0ai/mem0/pull/7358))
+
+**Changes:**
+- **Sidekick:** Renames shared tracking to use subagent terminology. Native subagent memory support remains available.
+
+</Update>
+
 <Update label="2026-09-08" description="Codex plugin v0.3.1">

 **Changed:**
@@ -2425,25 +2566,31 @@ Initial release of the Mem0 plugin for Claude Code and Cursor, followed by Codex

 </Tab>

-<Tab title="Agent Plugins v1">
+<Tab title="OpenCode">

-<Update label="2026-09-08" description="Portable Mem0 plugin v0.3.1">
+<Update label="2026-09-25" description="OpenCode plugin v0.4.2">

-**Added:**
- One portable package at `integrations/mem0-agent-plugin/`, using the Agent Plugins 1.0.0 root `plugin.json`, `mcp.json`, and fixed `skills/` locations.
- Ships a local, read-only `search_memories` server and the six shared memory skills. Uses `PLUGIN_ROOT` for bundled files and `PLUGIN_DATA` for persistent plugin state; all package files remain inside the installable directory.
-
-**Packaging:**
- Generated from the shared Python runtime and skill templates. Builds validate the manifest, MCP configuration, skills, and generated-file consistency.
- Host lifecycle hooks and native Sidekick declarations remain in the native plugin packages; the portable package does not provide automatic lifecycle capture or host-specific subagent isolation. Its bundled remember skill cannot persist a new memory on its own because the portable package has no capture hooks or write tool.
-
-[#7203](https://github.com/mem0ai/mem0/pull/7203)
+**Fixes:**
+- **Auth:** Falls back to the API key `mem0 init` saved in `~/.mem0/config.json` when neither `MEM0_API_KEY` nor a shell profile sets one, so search and the status check no longer report a missing key after `mem0 init` ([#7449](https://github.com/mem0ai/mem0/pull/7449))

 </Update>

-</Tab>
+<Update label="2026-09-23" description="OpenCode plugin v0.4.1">

-<Tab title="OpenCode">
+**Improvements:**
+- **Search:** The `search_memories` tool description no longer asks the agent to search proactively or to run several searches for multi-part questions. It now asks for a search before repeating investigation or when earlier decisions, fixes, commands, or results may help, the same wording as the other coding-agent plugins ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+- **Session context:** Removed two system-context lines that told the agent to run 2 parallel searches before responding and 2-4 parallel searches for non-trivial tasks ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+- **Skills:** `/mem0-search` and `/mem0-context-loader` make one `search_memories` call instead of 2 and 2-4 parallel calls. `/mem0-context-loader` now uses the search skill description from the other coding-agent plugins instead of asking to load at every new task or context switch ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+
+</Update>
+
+<Update label="2026-09-18" description="OpenCode plugin v0.4.0">
+
+**Changes:**
+- **Telemetry:** The PostHog `source` tag changed from the literal `"plugin"` to `OPENCODE_PLUGIN`, and `project_hash` is now salted. Saved PostHog insights filtering on `source = "plugin"` will stop matching new events; historical data is unaffected ([#7322](https://github.com/mem0ai/mem0/pull/7322))
+- **Config:** A new `keyFingerprint` key appears in the install-count deduplication logic; installs are now counted once per key rather than on every activation ([#7325](https://github.com/mem0ai/mem0/pull/7325))
+
+</Update>

 <Update label="2026-09-08" description="OpenCode plugin v0.3.0">

@@ -2543,6 +2690,36 @@ Initial release of the Mem0 plugin for Claude Code and Cursor, followed by Codex

 <Tab title="Antigravity">

+<Update label="2026-09-25" description="Antigravity plugin v0.3.4">
+
+**Fixes:**
+- **Auth:** Falls back to the API key `mem0 init` saved in `~/.mem0/config.json` when `MEM0_API_KEY` is not set, so search and the status check no longer report a missing key after `mem0 init` ([#7449](https://github.com/mem0ai/mem0/pull/7449))
+- **Data directory:** The `search_memories` MCP server uses `~/.mem0/antigravity-plugin`, the data directory the hooks use, instead of `~/.mem0/mem0-plugin` ([#7449](https://github.com/mem0ai/mem0/pull/7449))
+- **Packaging:** `PLUGIN_VERSION` bumped to `0.3.4`, so the `mem0-plugin/<version>` wire header and `plugin_version` telemetry field identify builds with this fix ([#7449](https://github.com/mem0ai/mem0/pull/7449))
+
+</Update>
+
+<Update label="2026-09-23" description="Antigravity plugin v0.3.3">
+
+**Improvements:**
+- **Search:** The `search_memories` tool description no longer tells the agent to call it before answering anything that could depend on prior context. It now asks for a search before repeating investigation or when earlier decisions, fixes, commands, or results may help, which reduces unnecessary searches ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+- **Extraction:** Repository memory instructions are shorter. They no longer ask for a dedicated memory for each command that failed and was then fixed, and no longer carry separate rules against saving personal preferences or memories that only name the repository, branch, or directory ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+- **Search skill:** `/search` no longer describes categories as best-effort labels or asks for a retry without the category ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+- **Packaging:** `PLUGIN_VERSION` bumped to `0.3.3`, so the `mem0-plugin/<version>` wire header and `plugin_version` telemetry field identify builds with these prompts ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+
+</Update>
+
+<Update label="2026-09-18" description="Antigravity plugin v0.3.2">
+
+**Improvements:**
+- **Telemetry:** `PLUGIN_VERSION` bumped to `0.3.2`. The `mem0-plugin/<version>` wire header and `plugin_version` telemetry field now reflect the fixes from #7322 through #7358 ([#7373](https://github.com/mem0ai/mem0/pull/7373))
+- **Telemetry:** Events are no longer delivered twice, no longer lose parked events on flush, and now attribute each event to the plugin that produced it ([#7323](https://github.com/mem0ai/mem0/pull/7323), [#7324](https://github.com/mem0ai/mem0/pull/7324), [#7358](https://github.com/mem0ai/mem0/pull/7358))
+
+**Changes:**
+- **Sidekick:** Removes Sidekick. Memory capture, search, and six skills remain available.
+
+</Update>
+
 <Update label="2026-09-08" description="Antigravity plugin v0.3.1">

 **Changed:**
@@ -2635,6 +2812,36 @@ Existing memories written by the previous versions are not rewritten. If your me

 <Tab title="Kimi">

+<Update label="2026-09-25" description="Kimi Code plugin v0.3.4">
+
+**Fixes:**
+- **Auth:** Falls back to the API key `mem0 init` saved in `~/.mem0/config.json` when `MEM0_API_KEY` is not set, so search and the status check no longer report a missing key after `mem0 init` ([#7449](https://github.com/mem0ai/mem0/pull/7449))
+- **Data directory:** The `search_memories` MCP server uses `~/.mem0/kimi-plugin`, the data directory the hooks use, instead of `~/.mem0/mem0-plugin` ([#7449](https://github.com/mem0ai/mem0/pull/7449))
+- **Packaging:** `PLUGIN_VERSION` bumped to `0.3.4`, so the `mem0-plugin/<version>` wire header and `plugin_version` telemetry field identify builds with this fix ([#7449](https://github.com/mem0ai/mem0/pull/7449))
+
+</Update>
+
+<Update label="2026-09-23" description="Kimi Code plugin v0.3.3">
+
+**Improvements:**
+- **Search:** The `search_memories` tool description no longer tells the agent to call it before answering anything that could depend on prior context. It now asks for a search before repeating investigation or when earlier decisions, fixes, commands, or results may help, which reduces unnecessary searches ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+- **Extraction:** Repository memory instructions are shorter. They no longer ask for a dedicated memory for each command that failed and was then fixed, and no longer carry separate rules against saving personal preferences or memories that only name the repository, branch, or directory ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+- **Search skill:** `/search` no longer describes categories as best-effort labels or asks for a retry without the category ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+- **Packaging:** `PLUGIN_VERSION` bumped to `0.3.3`, so the `mem0-plugin/<version>` wire header and `plugin_version` telemetry field identify builds with these prompts ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+
+</Update>
+
+<Update label="2026-09-18" description="Kimi Code plugin v0.3.2">
+
+**Improvements:**
+- **Telemetry:** `PLUGIN_VERSION` bumped to `0.3.2`. The `mem0-plugin/<version>` wire header and `plugin_version` telemetry field now reflect the fixes from #7322 through #7358 ([#7373](https://github.com/mem0ai/mem0/pull/7373))
+- **Telemetry:** Events are no longer delivered twice, no longer lose parked events on flush, and now attribute each event to the plugin that produced it ([#7323](https://github.com/mem0ai/mem0/pull/7323), [#7324](https://github.com/mem0ai/mem0/pull/7324), [#7358](https://github.com/mem0ai/mem0/pull/7358))
+
+**Changes:**
+- **Sidekick:** Removes Sidekick and its start/stop hooks. Memory capture, recall, and six skills remain available.
+
+</Update>
+
 <Update label="2026-09-08" description="Kimi Code plugin v0.3.1">

 **Changed:**
@@ -2669,6 +2876,21 @@ Existing memories written by the previous versions are not rewritten. If your me

 <Tab title="OpenClaw">

+<Update label="2026-09-23" description="openclaw-mem0 v1.2.1">
+
+**Improvements:**
+- **Search:** The `memory_search` tool description no longer asks the agent to search proactively or to run several searches for multi-part questions. It now asks for a search before repeating investigation or when earlier decisions, fixes, commands, or results may help. Recall strategies (`smart`, `always`, `manual`) are unchanged ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+
+</Update>
+
+<Update label="2026-09-18" description="openclaw-mem0 v1.2.0">
+
+**Changes:**
+- **Config:** Added `keyFingerprint` to the config schema for install-count deduplication; installs are now counted once per key rather than on every activation ([#7325](https://github.com/mem0ai/mem0/pull/7325))
+- **Telemetry:** Events are no longer delivered twice, and the `plugin_version` field now reflects the plugin that produced the event ([#7323](https://github.com/mem0ai/mem0/pull/7323), [#7324](https://github.com/mem0ai/mem0/pull/7324), [#7358](https://github.com/mem0ai/mem0/pull/7358))
+
+</Update>
+
 <Update label="2026-09-08" description="openclaw-mem0 v1.1.0">

 **Changed:**
@@ -2957,6 +3179,29 @@ Existing memories written by the previous versions are not rewritten. If your me

 <Tab title="Pi Agent">

+<Update label="2026-09-25" description="Pi Agent plugin v0.3.3">
+
+**Fixes:**
+- **Auth:** Falls back to the API key `mem0 init` saved in `~/.mem0/config.json` when neither `MEM0_API_KEY` nor `~/.pi/agent/mem0-config.json` sets one, so search and the status check no longer report a missing key after `mem0 init` ([#7449](https://github.com/mem0ai/mem0/pull/7449))
+
+</Update>
+
+<Update label="2026-09-23" description="Pi Agent plugin v0.3.2">
+
+**Improvements:**
+- **Search:** The memory policy, `mem0_memory` tool description, and prompt guidelines no longer ask the agent to search before answering anything that may depend on earlier context or to run several searches per question. They now ask for a search before repeating investigation or when earlier decisions, fixes, commands, or results may help ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+- **Skills:** `context-loader` makes one search instead of 2-4 parallel searches, and uses the search skill description from the other coding-agent plugins ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+- **Automatic recall:** Injected memories are introduced as "Mem0 found these relevant memories from earlier work in this repository:", the same heading as the Python plugins. The old heading called them a shallow first pass and told the agent to search again ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+
+</Update>
+
+<Update label="2026-09-18" description="Pi Agent plugin v0.3.1">
+
+**Improvements:**
+- **Telemetry:** Events are no longer delivered twice, no longer lose parked events, and now attribute each event to the plugin that produced it. The `plugin_version` wire field reflects the fixed release ([#7323](https://github.com/mem0ai/mem0/pull/7323), [#7324](https://github.com/mem0ai/mem0/pull/7324), [#7358](https://github.com/mem0ai/mem0/pull/7358))
+
+</Update>
+
 <Update label="2026-09-08" description="Pi Agent plugin v0.3.0">

 **Changed:**
@@ -3070,6 +3315,29 @@ Existing memories written by the previous versions are not rewritten. If your me

 <Tab title="DeepSeek Harness">

+<Update label="2026-09-25" description="deepseek-plugin v0.3.3">
+
+**Fixes:**
+- **Auth:** Falls back to the API key `mem0 init` saved in `~/.mem0/config.json` when neither `config.apiKey` nor `MEM0_API_KEY` is set, so search and the status check no longer report a missing key after `mem0 init` ([#7449](https://github.com/mem0ai/mem0/pull/7449))
+- **Config:** An empty `apiKey` now counts as unset and falls through to `MEM0_API_KEY` and the `mem0 init` key, instead of failing validation ([#7449](https://github.com/mem0ai/mem0/pull/7449))
+
+</Update>
+
+<Update label="2026-09-23" description="deepseek-plugin v0.3.2">
+
+**Improvements:**
+- **Search:** The `search_memory` tool description no longer asks the agent to search proactively before answering anything that may depend on earlier context. It now asks for a search before repeating investigation or when earlier decisions, fixes, commands, or results may help ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+- **Automatic recall:** Injected memories are introduced as "Mem0 found these relevant memories from earlier work:". The old heading called them a shallow first pass and told the agent to search again with `mem0_memory`, a tool DeepSeek does not have ([#7420](https://github.com/mem0ai/mem0/pull/7420))
+
+</Update>
+
+<Update label="2026-09-18" description="deepseek-plugin v0.3.1">
+
+**Improvements:**
+- **Telemetry:** Rebuild with the fixed shared telemetry core from `agent-plugin-core`. Events are no longer delivered twice, no longer lose parked events on flush, and now attribute each event to the plugin that produced it ([#7323](https://github.com/mem0ai/mem0/pull/7323), [#7324](https://github.com/mem0ai/mem0/pull/7324), [#7358](https://github.com/mem0ai/mem0/pull/7358))
+
+</Update>
+
 <Update label="2026-09-08" description="deepseek-plugin v0.3.0">

 **Added:**
@@ -3114,6 +3382,13 @@ Existing memories written by the previous versions are not rewritten. If your me

 <Tab title="Vercel AI SDK">

+<Update label="2026-09-18" description="Vercel AI SDK v3.0.3">
+
+**Improvements:**
+- **Client:** Inherits the three surface-identity headers (`X-Mem0-Source`, `X-Application`, `X-Mem0-Client`) from the TypeScript SDK bump, so platform calls made through the Vercel AI SDK provider are now correctly attributed ([#7326](https://github.com/mem0ai/mem0/pull/7326))
+
+</Update>
+
 <Update label="2026-08-24" description="Vercel AI SDK v3.0.2">

 **Security:**
@@ -1,7 +1,6 @@
 ---
-title: Configurations
-seo:
-  title: "Embedder Configuration Reference - Mem0"
+title: "Embedder Configuration Reference"
+sidebarTitle: "Configurations"
 description: "Reference for embedder configuration options in Mem0, including provider selection and model settings."
 ---

@@ -1,7 +1,6 @@
 ---
-title: AWS Bedrock
-seo:
-  title: "AWS Bedrock as Embedding Provider - Mem0"
+title: "AWS Bedrock as Embedding Provider"
+sidebarTitle: "AWS Bedrock"
 description: "Configure AWS Bedrock as an embedding provider in Mem0 with IAM credentials and boto3 authentication."
 ---

@@ -1,7 +1,6 @@
 ---
-title: Azure OpenAI
-seo:
-  title: "Azure OpenAI as Embedding Provider - Mem0"
+title: "Azure OpenAI as Embedding Provider"
+sidebarTitle: "Azure OpenAI"
 description: "Configure Azure OpenAI as an embedding provider in Mem0 with API key, deployment, and endpoint settings."
 ---

@@ -1,7 +1,6 @@
 ---
-title: Google AI
-seo:
-  title: "Google AI as Embedding Provider - Mem0"
+title: "Google AI as Embedding Provider"
+sidebarTitle: "Google AI"
 description: "Configure Google AI as an embedding provider in Mem0 using Gemini models and the GOOGLE_API_KEY variable."
 ---

@@ -1,7 +1,6 @@
 ---
-title: LangChain
-seo:
-  title: "LangChain as Embedding Provider - Mem0"
+title: "LangChain as Embedding Provider"
+sidebarTitle: "LangChain"
 description: "Use LangChain as an embedding provider in Mem0 to access a wide range of models through a unified interface."
 ---

@@ -1,7 +1,6 @@
 ---
-title: "LM Studio"
-seo:
-  title: "LM Studio as Embedding Provider - Mem0"
+title: "LM Studio as Embedding Provider"
+sidebarTitle: "LM Studio"
 description: "Configure LM Studio as an embedding provider in Mem0 for local embedding generation with models like nomic-embed-text."
 ---
 You can use embedding models from LM Studio to run Mem0 locally.
@@ -1,7 +1,6 @@
 ---
-title: "Ollama"
-seo:
-  title: "Ollama as Embedding Provider - Mem0"
+title: "Ollama as Embedding Provider"
+sidebarTitle: "Ollama"
 description: "Configure Ollama as an embedding provider in Mem0 to generate embeddings locally using open-source models."
 ---
 You can use embedding models from Ollama to run Mem0 locally.
@@ -1,7 +1,6 @@
 ---
-title: OpenAI
-seo:
-  title: "OpenAI as Embedding Provider - Mem0"
+title: "OpenAI as Embedding Provider"
+sidebarTitle: "OpenAI"
 description: "Configure OpenAI as an embedding provider in Mem0 using models like text-embedding-3-large for vector generation."
 ---

@@ -1,7 +1,6 @@
 ---
-title: Together
-seo:
-  title: "Together AI as Embedding Provider - Mem0"
+title: "Together AI as Embedding Provider"
+sidebarTitle: "Together"
 description: "Configure Together AI as an embedding provider in Mem0 with support for 1024-dimensional embedding models."
 ---

@@ -12,7 +11,7 @@ To use Together embedding models, set the `TOGETHER_API_KEY` environment variabl
 <Note> The `embedding_model_dims` parameter for `vector_store` should be set to `1024` for Together embedder. </Note>

 <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.
+**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>
@@ -1,7 +1,6 @@
 ---
-title: Overview
-seo:
-  title: "Embedding Providers Overview - Mem0"
+title: "Embedding Providers Overview"
+sidebarTitle: Overview
 description: "Overview of all supported embedding model providers in Mem0, including OpenAI, Azure, Ollama, and more."
 ---

@@ -1,7 +1,6 @@
 ---
-title: Configurations
-seo:
-  title: "LLM Configuration Reference - Mem0"
+title: "LLM Configuration Reference"
+sidebarTitle: "Configurations"
 description: "Reference for LLM configuration options in Mem0 for Python and TypeScript, including value precedence rules."
 ---

@@ -1,7 +1,6 @@
 ---
-title: AWS Bedrock
-seo:
-  title: "AWS Bedrock as LLM Provider - Mem0"
+title: "AWS Bedrock as LLM Provider"
+sidebarTitle: "AWS Bedrock"
 description: "Configure AWS Bedrock as an LLM provider in Mem0 with IAM authentication and Claude model support."
 ---

@@ -1,7 +1,6 @@
 ---
-title: Azure OpenAI
-seo:
-  title: "Azure OpenAI as LLM Provider - Mem0"
+title: "Azure OpenAI as LLM Provider"
+sidebarTitle: "Azure OpenAI"
 description: "Configure Azure OpenAI as an LLM provider in Mem0 with Azure Identity authentication and deployment settings."
 ---

@@ -3,7 +3,7 @@ title: DeepSeek
 description: "Configure DeepSeek as an LLM provider in Mem0 with API key setup and optional custom endpoint configuration."
 ---

-To use DeepSeek LLM models, you have to set the `DEEPSEEK_API_KEY` environment variable. You can also optionally set `DEEPSEEK_API_BASE` if you need to use a different API endpoint (defaults to "https://api.deepseek.com").
+To use DeepSeek LLM models, you have to set the `DEEPSEEK_API_KEY` environment variable. You can also optionally set `DEEPSEEK_API_BASE` if you need to use a different API endpoint (defaults to `https://api.deepseek.com`).

 ## Usage

@@ -1,7 +1,6 @@
 ---
-title: Google AI
-seo:
-  title: "Google AI as LLM Provider - Mem0"
+title: "Google AI as LLM Provider"
+sidebarTitle: "Google AI"
 description: "Configure Google Gemini as an LLM provider in Mem0 using the google.genai SDK and GOOGLE_API_KEY variable."
 ---

@@ -1,7 +1,6 @@
 ---
-title: LangChain
-seo:
-  title: "LangChain as LLM Provider - Mem0"
+title: "LangChain as LLM Provider"
+sidebarTitle: "LangChain"
 description: "Use LangChain as an LLM provider in Mem0 to integrate with various chat models through a unified interface."
 ---

@@ -1,7 +1,6 @@
 ---
-title: LM Studio
-seo:
-  title: "LM Studio as LLM Provider - Mem0"
+title: "LM Studio as LLM Provider"
+sidebarTitle: "LM Studio"
 description: "Configure LM Studio as an LLM provider in Mem0 for running local language models via an OpenAI-compatible API."
 ---

@@ -78,7 +77,7 @@ m.add(messages, user_id="alice123", metadata={"category": "movies"})
  To use LM Studio, you need to:
  1. Download and install [LM Studio](https://lmstudio.ai/)
  2. Start a local server from the "Server" tab
-  3. Set the appropriate `lmstudio_base_url` in your configuration (default is usually http://localhost:1234/v1)
+  3. Set the appropriate `lmstudio_base_url` in your configuration (default is usually `http://localhost:1234/v1`)
 </Note>

 ## Config
@@ -3,7 +3,7 @@ title: MiniMax
 description: "Configure MiniMax as an LLM provider in Mem0 with API key setup and optional custom endpoint configuration."
 ---

-To use MiniMax LLM models, you have to set the `MINIMAX_API_KEY` environment variable. You can also optionally set `MINIMAX_API_BASE` if you need to use a different API endpoint (defaults to "https://api.minimax.io/v1").
+To use MiniMax LLM models, you have to set the `MINIMAX_API_KEY` environment variable. You can also optionally set `MINIMAX_API_BASE` if you need to use a different API endpoint (defaults to `https://api.minimax.io/v1`).

 ## Usage

@@ -1,7 +1,6 @@
 ---
-title: Ollama
-seo:
-  title: "Ollama as LLM Provider - Mem0"
+title: "Ollama as LLM Provider"
+sidebarTitle: "Ollama"
 description: "Configure Ollama as an LLM provider in Mem0 for running local language models with tool-calling support."
 ---

@@ -1,7 +1,6 @@
 ---
-title: OpenAI
-seo:
-  title: "OpenAI as LLM Provider - Mem0"
+title: "OpenAI as LLM Provider"
+sidebarTitle: "OpenAI"
 description: "Configure OpenAI as an LLM provider in Mem0 with support for GPT models and Openrouter compatibility."
 ---

@@ -1,7 +1,6 @@
 ---
-title: Together
-seo:
-  title: "Together AI as LLM Provider - Mem0"
+title: "Together AI as LLM Provider"
+sidebarTitle: "Together"
 description: "Configure Together AI as an LLM provider in Mem0 with API key setup and optional custom endpoint configuration."
 ---

@@ -1,7 +1,6 @@
 ---
-title: xAI
-seo:
-  title: "xAI Grok as LLM Provider - Mem0"
+title: "xAI Grok as LLM Provider"
+sidebarTitle: "xAI"
 description: "Configure xAI Grok models as an LLM provider in Mem0 with API key setup and usage examples."
 ---

@@ -1,7 +1,6 @@
 ---
-title: Overview
-seo:
-  title: "LLM Providers Overview - Mem0"
+title: "LLM Providers Overview"
+sidebarTitle: Overview
 description: "Overview of all supported LLM providers in Mem0, including OpenAI, Anthropic, Groq, Ollama, and more."
 ---

@@ -1,7 +1,6 @@
 ---
-title: Overview
-seo:
-  title: "Reranker Providers Overview - Mem0"
+title: "Reranker Providers Overview"
+sidebarTitle: "Overview"
 description: 'Pick the right reranker path to boost Mem0 search relevance.'
 ---

@@ -1,7 +1,6 @@
 ---
-title: Configurations
-seo:
-  title: "Vector Store Configuration Reference - Mem0"
+title: "Vector Store Configuration Reference"
+sidebarTitle: "Configurations"
 description: "Reference for vector database configuration options in Mem0, including provider selection and connection settings."
 ---

@@ -95,7 +95,7 @@ Uses the identity from Azure PowerShell (`Connect-AzAccount`).
 7. **Azure Developer CLI Credential:**
 Uses the session from Azure Developer CLI (`azd auth login`).

-<Note> If an API is provided, it will be used for authentication over an Azure Identity </Note>
+<Note> If an API key is provided, it will be used for authentication over an Azure Identity </Note>
 To enable Role-Based Access Control (RBAC) for Azure AI Search, follow these steps:

 1. In the Azure Portal, navigate to your **Azure AI Search** service.
@@ -1,7 +1,6 @@
 ---
-title: LangChain
-seo:
-  title: "LangChain as Vector Store Provider - Mem0"
+title: "LangChain as Vector Store Provider"
+sidebarTitle: "LangChain"
 description: "Use LangChain as a unified vector store provider in Mem0 to access multiple vector databases through one interface."
 ---

@@ -94,6 +94,7 @@ Here are the parameters available for configuring Pinecone:
 | `hybrid_search` | Whether to enable hybrid search | `False` |
 | `metric` | Distance metric for vector similarity | `"cosine"` |
 | `batch_size` | Batch size for operations | `100` |
+| `extra_params` | Additional keyword arguments passed to the `Pinecone` client constructor. Ignored when `client` is supplied. | `None` |
 | `namespace` | Namespace for the collection, useful for multi-tenancy. | `None` |
 </Tab>
 <Tab title="TypeScript">
@@ -102,7 +102,7 @@ Here are the parameters available for configuring Upstash Vector:
 | `url`               | URL for the Upstash Vector index   | `None`        |
 | `token`             | Token for the Upstash Vector index | `None`        |
 | `client`            | An `upstash_vector.Index` instance | `None`        |
-| `collection_name`   | The default namespace used         | `""`          |
+| `collection_name`   | The default namespace used         | `"mem0"`      |
 | `enable_embeddings` | Whether to use Upstash embeddings  | `False`       |

 <Note>
@@ -1,7 +1,6 @@
 ---
-title: Overview
-seo:
-  title: "Vector Store Providers Overview - Mem0"
+title: "Vector Store Providers Overview"
+sidebarTitle: "Overview"
 description: "Overview of all supported vector databases in Mem0, including Qdrant, Chroma, PGVector, Pinecone, Oracle, and more."
 ---

@@ -30,7 +30,7 @@ pip install google-adk mem0ai python-dotenv

 ## Code Breakdown

-Let's get started and understand the different components required in building a healthcare assistant powered by memory
+Let's get started and understand the different components required in building a healthcare assistant powered by memory.

 ```python
 # Import dependencies
@@ -0,0 +1,388 @@
+---
+title: Build a Company Brain with Mem0 Platform and Supabase
+description: "Build a shared company brain using Mem0 Platform as the managed memory layer, Supabase as your system of record, and the Mem0 MCP server."
+---
+
+<Info icon="server">
+**Uses:** Mem0 **Platform** (`MemoryClient`) · **System of record:** Supabase (Postgres + Auth) · **Access layer:** the hosted Mem0 MCP server. **You'll build:** a company brain your whole org (and every agent) writes to and queries, ending with a new-hire onboarding demo.
+</Info>
+
+Companies lose knowledge constantly: why you picked Postgres over Mongo, who owns billing, the deploy rule only one engineer remembers. A **company brain** captures this and answers questions about it, for every employee and every agent, and keeps it after people leave.
+
+We'll build one on **Mem0 Platform** (the managed memory layer, so there's no vector DB to run) with **Supabase as the system of record** (where your employees, teams, and source documents actually live) and the **Mem0 MCP server** as the wire that lets Claude Code, Cursor, or a Slack bot all reach the same brain.
+
+<Note>
+**How Platform and Supabase divide the work.** Mem0 Platform manages storage and extraction server-side, you do **not** point it at your own database. Supabase is your app's source of truth and identity provider; we *ingest* knowledge from Supabase into the brain and use Supabase Auth to decide who's asking. (If you want to self-host the vector store instead, that's the OSS path, see the [Supabase vector store reference](/components/vectordbs/dbs/supabase).)
+</Note>
+
+## Architecture
+
+```mermaid
+flowchart LR
+  subgraph SB["Supabase: system of record"]
+    K[(knowledge / employees / teams)]
+    AU[Auth · who is asking]
+  end
+  subgraph M0["Mem0 Platform: the brain"]
+    B[(managed memory)]
+  end
+  K -->|ingest| B
+  AU -->|maps to scope| B
+  CC[Claude Code] --> MCP[Mem0 MCP server]
+  CU[Cursor] --> MCP
+  SL[Slack bot] --> MCP
+  MCP --> B
+```
+
+Memory splits by entity. An individual is a **`user_id`** (their Supabase Auth id). Shared knowledge lives on an **`agent_id`**: the company-wide brain is `org:acme`, and each team is its own agent, e.g. `team:payments`. A person's own facts route to their `user_id`; company and team facts route to the agent. This split is what lets one search return "my" context alongside the shared org knowledge.
+
+## Prerequisites
+
+- **Python 3.9+**
+- A **Mem0 Platform API key**, [app.mem0.ai/dashboard/api-keys](https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=cookbook-company-brain). (Platform runs extraction and embeddings for you, so there's no OpenAI key to manage.)
+- A **Supabase** project, [supabase.com](https://supabase.com)
+
+About 20 minutes.
+
+---
+
+## Step 1: Get your Mem0 Platform API key
+
+Sign in at [app.mem0.ai](https://app.mem0.ai) and copy a key from **Dashboard → API Keys**. The key is scoped to your org and project; Mem0 resolves both server-side, so you never pass IDs by hand.
+
+## Step 2: Create the Supabase system of record
+
+In the Supabase **SQL editor**, create the tables your company already thinks in: people, teams, and a `knowledge` table the brain will ingest from. Identity reuses Supabase Auth's built-in `auth.users`.
+
+```sql
+-- Employees extend Supabase Auth's users; identity is auth.users.id (uuid)
+create table public.employees (
+  id     uuid primary key references auth.users (id) on delete cascade,
+  name   text not null,
+  team   text not null
+);
+
+-- The company knowledge the brain ingests. `scope` decides who can recall it.
+create table public.knowledge (
+  id             bigint generated always as identity primary key,
+  scope          text not null,                    -- the shared agent this belongs to: 'org:acme' | 'team:payments'
+  content        text not null,
+  author         uuid references auth.users (id),   -- who recorded it (their user_id); null for org seed data
+  created_at     timestamptz default now(),
+  mem0_synced_at timestamptz                        -- null until ingested into the brain
+);
+create index on public.knowledge (mem0_synced_at, created_at);
+
+-- Seed a little company knowledge to ingest.
+insert into public.knowledge (scope, content) values
+  ('org:acme', 'We chose Postgres over MongoDB for the core product for strong transactional guarantees and relational joins.'),
+  ('org:acme', 'All production deploys go out Tuesday and Thursday; never on Fridays.'),
+  ('org:acme', 'Customer data must stay in the EU region for GDPR compliance.'),
+  ('org:acme', 'Billing is owned by the Payments team, and Alice is the Payments tech lead.'),
+  ('team:payments', 'Stripe is our processor; webhooks are verified with PAYMENTS_WEBHOOK_SECRET.');
+```
+
+Grab your project URL and **service-role** key from **Settings → API** (the ingestion job runs server-side and needs to read every scope).
+
+## Step 3: Project setup
+
+```bash
+mkdir company-brain && cd company-brain
+pip install "mem0ai>=2.0.17" supabase requests   # 2.0.17+ for agent_custom_instructions
+```
+
+```bash
+export MEM0_API_KEY="m0-..."
+export SUPABASE_URL="https://<project-ref>.supabase.co"
+export SUPABASE_SERVICE_KEY="<service-role-key>"
+```
+
+## Step 4: Configure the brain
+
+Create **`brain.py`**. This constructs the Platform client and teaches it what to remember. The key is the **two** instruction sets: `custom_instructions` governs a person's own (`user_id`) memories, and `agent_custom_instructions` governs shared (`agent_id`) memories, phrased in the third person so company facts read "The company…", not "The user's organization…". `custom_categories` files each memory under a useful label.
+
+```python
+# brain.py
+import os
+from mem0 import MemoryClient
+
+client = MemoryClient(api_key=os.environ["MEM0_API_KEY"])
+
+# Steer extraction (project-wide). Runs server-side; no LLM key needed here.
+client.project.update(
+    # Governs a person's OWN memories (user_id).
+    custom_instructions=(
+        "Extract the individual's own durable preferences, context, and how they work. "
+        "Ignore greetings and one-off chatter."
+    ),
+    # Governs SHARED memories (agent_id); write them in the third person.
+    agent_custom_instructions=(
+        "Extract durable company/team knowledge in the third person "
+        "(\"The company...\", \"The team...\"): decisions and their rationale, ownership "
+        "(who owns what), processes, policies, tooling choices, and gotchas. "
+        "Ignore greetings, scheduling, and one-off chatter."
+    ),
+    custom_categories=[
+        {"decision": "Architectural or product decisions and why they were made"},
+        {"ownership": "Who owns a system, service, or process"},
+        {"policy": "Compliance, security, and process rules"},
+        {"tooling": "Tools, services, and how they're configured"},
+    ],
+)
+
+# Scopes. A person is a user_id; shared brains are agent_ids.
+COMPANY = "org:acme"                       # agent_id: company-wide shared brain
+def team(name):   return f"team:{name}"    # agent_id: a team's shared brain
+def person(uid):  return uid               # user_id: an individual (Supabase auth id)
+```
+
+Run it once to apply the project settings:
+
+```bash
+python -c "import brain; print('brain configured')"
+```
+
+
+## Step 5: Ingest company knowledge from Supabase
+
+This is where Supabase and the brain connect. Create **`ingest.py`**: read un-synced rows from `knowledge`, add each to the Platform brain under its scope, then mark it synced. Platform `add()` is **asynchronous**, it returns an `event_id` you can poll, so we include a small `wait_for` helper.
+
+```python
+# ingest.py
+import os, time, requests
+from supabase import create_client
+from brain import client, person
+
+sb = create_client(os.environ["SUPABASE_URL"], os.environ["SUPABASE_SERVICE_KEY"])
+MEM0_HEADERS = {"Authorization": f"Token {os.environ['MEM0_API_KEY']}"}
+
+def wait_for(event_id, timeout=30):
+    """Platform extraction is async; poll the event until it settles."""
+    for _ in range(timeout):
+        r = requests.get(f"https://api.mem0.ai/v1/event/{event_id}/", headers=MEM0_HEADERS).json()
+        if r.get("status") in ("SUCCEEDED", "FAILED"):
+            return r["status"]
+        time.sleep(1)
+    return "TIMEOUT"
+
+# 1. Read knowledge that hasn't been ingested yet
+rows = sb.table("knowledge").select("*").is_("mem0_synced_at", "null").execute().data
+
+for row in rows:
+    # 2. Add it. agent_id = the shared scope (org/team); user_id = who recorded it.
+    #    Mem0 routes shared facts to the agent and personal facts to the individual,
+    #    so pass both when there's an author.
+    add_kwargs = {
+        "agent_id": row["scope"],
+        "metadata": {"source": "supabase", "knowledge_id": row["id"]},
+    }
+    if row["author"]:
+        add_kwargs["user_id"] = person(row["author"])
+    res = client.add([{"role": "user", "content": row["content"]}], **add_kwargs)
+    # 3. Platform returns an event_id; wait for extraction to finish
+    event_id = res.get("event_id") if isinstance(res, dict) else None
+    if event_id:
+        wait_for(event_id)
+    # 4. Mark the row synced so we never double-ingest
+    sb.table("knowledge").update({"mem0_synced_at": "now()"}).eq("id", row["id"]).execute()
+
+print(f"Ingested {len(rows)} knowledge items into the company brain.")
+```
+
+```bash
+python ingest.py
+```
+
+```text
+Ingested 5 knowledge items into the company brain.
+```
+
+Re-running is safe, `mem0_synced_at` gates it, so a nightly cron can keep the brain in step with Supabase.
+
+## Step 6: Ask the brain
+
+Create **`ask.py`**. It searches everything relevant to the asker: their own (`user_id`) memories **plus** the shared company and team (`agent_id`) memories. This has to be an **`OR`**, each memory row belongs to exactly one entity, so a flat filter or an `AND` of a `user_id` and an `agent_id` matches nothing.
+
+```python
+# ask.py
+import sys
+from brain import client, COMPANY, team, person
+
+def ask(question: str, uid: str | None = None, user_team: str | None = None) -> str:
+    scopes = [{"agent_id": COMPANY}]              # company-wide brain
+    if user_team:
+        scopes.append({"agent_id": team(user_team)})   # the asker's team
+    if uid:
+        scopes.append({"user_id": person(uid)})        # the asker's own memories
+    hits = client.search(
+        query=question,
+        filters={"OR": scopes},   # OR, never AND (one FK per memory row)
+        top_k=5,
+        rerank=True,
+    )
+    return "\n".join(f"- {h['memory']}" for h in hits.get("results", hits))
+
+if __name__ == "__main__":
+    print(ask(" ".join(sys.argv[1:]) or "When can we deploy?"))
+```
+
+```bash
+python ask.py "Why did we pick Postgres, and can I deploy on Friday?"
+```
+
+```text
+- The company chose Postgres over MongoDB for strong transactional guarantees and relational joins
+- The company's production deploys go out Tuesday and Thursday, never on Fridays
+```
+
+Search returns every relevant memory, so a question resolves across separate facts, here it pulls both the owning team and the person:
+
+```bash
+python ask.py "Who should I talk to about billing?"
+```
+
+```text
+- Billing is owned by the Payments team
+- Alice is the Payments tech lead
+```
+
+## Step 7: Sharper retrieval
+
+Platform search is hybrid (semantic + keyword) and filterable. Combine a keyword pass with a category filter to answer precise questions:
+
+```python
+client.search(
+    query="webhook signing secret",
+    filters={"agent_id": "team:payments", "categories": {"in": ["tooling"]}},
+    keyword_search=True,     # hybrid keyword + semantic
+    rerank=True,
+    threshold=0.3,
+)
+```
+
+Filters use keyword operators (`in`, `gte`, `contains`, …) and AND/OR/NOT, so you can scope by date, category, or metadata, for example the company's policies added this quarter:
+
+```python
+client.search(
+    query="compliance rules",
+    filters={"AND": [
+        {"agent_id": "org:acme"},
+        {"categories": {"in": ["policy"]}},
+        {"created_at": {"gte": "2026-01-01"}},
+    ]},
+)
+```
+
+## Step 8: Expose the brain to every agent (MCP)
+
+A brain only your script can reach isn't a company brain. Mem0's **hosted MCP server** lets any agent (Claude Code, Cursor, a Slack bot) query and contribute to the *same* brain. The endpoint is `https://mcp.mem0.ai/mcp`, and the supported way to connect is the `mcp-add` helper, which registers the server and runs Mem0's OAuth login so no key ever lands in a config file.
+
+<Tabs>
+<Tab title="Claude Code / Cursor">
+```bash
+npx mcp-add --url "https://mcp.mem0.ai/mcp" --clients "claude code,cursor"
+```
+Complete the browser login on first connect. Now the agent has the brain's memory tools (`add_memory`, `search_memories`, and more) available in-editor.
+</Tab>
+<Tab title="Manual (.mcp.json)">
+```json
+{
+  "mcpServers": {
+    "mem0": { "url": "https://mcp.mem0.ai/mcp" }
+  }
+}
+```
+Auth happens via Mem0's OAuth flow on first use, don't paste a static token into the file (the hosted gateway may reject a raw `Token` header).
+</Tab>
+<Tab title="Slack bot">
+```python
+# A Slack bot is just another MCP client. Point its MCP layer at the same URL,
+# authenticate via Mem0's OAuth flow, and pass the company scope on each call.
+await mcp.call_tool("search_memories", {
+    "query": user_message,
+    "agent_id": "org:acme",
+})
+```
+</Tab>
+</Tabs>
+
+With this, an engineer asks the brain from their editor and a teammate asks it from Slack, one shared memory behind both.
+
+## Step 9: Onboard a new hire (the payoff)
+
+This is what a company brain is *for*. Dana joins, and her identity comes from **Supabase Auth**, which maps straight to her Mem0 `user_id`. She asks the questions every new hire asks and gets real answers on day one, drawn from the shared company (and her team's) brain, plus anything she's told it herself.
+
+```python
+# onboarding.py
+from brain import client, person
+from ask import ask
+
+# In a real app these come from sb.auth.get_user(jwt) and the employees table.
+dana_uid, dana_team = "8f3c...-dana", "payments"
+
+# Dana also tells the brain how *she* works. This is personal, so it goes to her
+# user_id, not the shared agent, and stays scoped to her.
+client.add(
+    [{"role": "user", "content": "I prefer early returns over nested ifs, and I review PRs in the morning."}],
+    user_id=person(dana_uid),
+)
+
+for q in [
+    "Who owns billing and who do I talk to?",   # company (agent) knowledge
+    "When are deploys, and are there hard rules?",
+    "How do I like to write code?",             # Dana's own (user) knowledge
+]:
+    print(f"Q: {q}\nA: {ask(q, uid=dana_uid, user_team=dana_team)}\n")
+```
+
+```text
+Q: Who owns billing and who do I talk to?
+A: - Billing is owned by the Payments team; Alice is the Payments tech lead
+
+Q: When are deploys, and are there hard rules?
+A: - The company's production deploys go out Tuesday and Thursday, never on Fridays
+
+Q: How do I like to write code?
+A: - User prefers early returns over nested ifs
+```
+
+The same `ask()` blends the shared company facts with Dana's own preference, because the `OR` filter spans both her `user_id` and the org and team `agent_id`s.
+
+Dana onboarded herself by asking, drawing on the shared brain the rest of the team had been filling.
+
+## Production notes
+
+<Warning>
+**`user_id` vs `agent_id`.** An individual is a `user_id`; shared brains (company, team) are `agent_id`s. Keeping them separate is what gives you the third-person "The company…" framing and lets a person's own context sit alongside org knowledge. Put a secret like a webhook key on a **team** agent, never the company agent, or everyone can recall it, and mirror the boundary in Supabase with a Row Level Security policy on `knowledge`.
+</Warning>
+
+<Warning>
+**Search must `OR` the scopes.** A memory row belongs to exactly one entity, so `filters={"OR": [{"user_id": ...}, {"agent_id": "org:acme"}, {"agent_id": "team:..."}]}`. A flat filter, or an `AND` of a `user_id` and an `agent_id`, returns nothing.
+</Warning>
+
+<Warning>
+**`add()` is asynchronous.** It returns `{event_id, status: "PENDING"}` and extraction finishes a moment later, poll `GET /v1/event/{event_id}/` (as in Step 5) when you need to know a write has landed before searching for it.
+</Warning>
+
+<Note>
+**Where the entity ID goes differs by call.** `search()` and `get_all()` take the scope inside `filters={...}` (a top-level `user_id=`/`agent_id=` is rejected). `add()` and `delete_all()` are the opposite, they take it as a top-level keyword: `client.delete_all(agent_id="team:payments")`. Deletes are asynchronous too, so a `get_all` right after a `delete_all` can still show rows for a few seconds.
+</Note>
+
+## Where to take it next
+
+- **Auto-feed the brain** from PR descriptions, RFCs, and incident write-ups so it grows without anyone thinking about it, just insert into Supabase `knowledge` and let the cron ingest.
+- **Scope by real identity** end to end: verify the Supabase JWT, read `sb.auth.get_user(jwt).user.id` for the `user_id`, look up the person's team, and `OR` their `user_id` with the company and team `agent_id`s on every recall.
+- **Give teams a private view** with Supabase RLS so `team:` knowledge is only readable by that team.
+
+---
+
+<CardGroup cols={2}>
+  <Card title="Mem0 MCP Server" icon="plug" href="/platform/mem0-mcp">
+    Connect any agent or editor to the brain over MCP.
+  </Card>
+  <Card title="Custom Categories & Instructions" icon="sliders" href="/platform/features/custom-instructions">
+    Steer exactly what the brain extracts and how it's filed.
+  </Card>
+</CardGroup>
+
+<Snippet file="star-on-github.mdx" />
@@ -1,7 +1,6 @@
 ---
-title: Overview
-seo:
-  title: "Cookbooks and Tutorials - Mem0"
+title: "Cookbooks and Tutorials"
+sidebarTitle: "Overview"
 description: "Browse cookbook examples and tutorials for building AI applications with Mem0, from companion chatbots to AI agents."
 ---

@@ -89,8 +89,8 @@ On Mem0 Platform, these stores are managed for you. In OSS, you choose and opera
 ## Next steps

 <CardGroup cols={3}>
-  <Card title="Memory types" icon="brain" href="/core-concepts/memory-types">
-    Choose the right scope for user, agent, run, and session memory.
+  <Card title="Entity scoping" icon="brain" href="/platform/features/entity-scoped-memory">
+    Organize Platform memories by user, agent, app, and run.
  </Card>
  <Card title="Memory operations" icon="database" href="/core-concepts/memory-operations/add">
    Add, search, update, and delete memories from your app.
@@ -1,7 +1,6 @@
 ---
-title: Delete Memory
-seo:
-  title: "Delete Memory Operation - Mem0"
+title: "Delete Memory Operation"
+sidebarTitle: "Delete Memory"
 description: Remove memories from Mem0 either individually, in bulk, or via filters.
 icon: "trash"
 iconType: "solid"
@@ -1,7 +1,6 @@
 ---
-title: Update Memory
-seo:
-  title: "Update Memory Operation - Mem0"
+title: "Update Memory Operation"
+sidebarTitle: "Update Memory"
 description: Modify an existing memory by updating its content or metadata.
 icon: "pen-to-square"
 iconType: "solid"
@@ -1,118 +0,0 @@
---
-title: Memory Types
-description: "What memory_type actually does in Mem0: procedural memory is implemented, semantic and episodic are not."
-icon: "tag"
-iconType: "solid"
---
-
-# Memory Types
-
-Mem0's Python SDK exposes a `memory_type` parameter on `add()`. The underlying `MemoryType` enum defines three values, but only one of them is wired up. This page states plainly which is which so you don't build against a type that doesn't exist yet.
-
-## Status
-
-| Type | Enum value | Status | Notes |
-| --- | --- | --- | --- |
-| Procedural memory | `procedural_memory` | **Implemented** | Python OSS only (`Memory`/`AsyncMemory`). Pass `memory_type="procedural_memory"` and `agent_id` to `add()`. Not available on the Platform `MemoryClient`, and not available in the TypeScript SDK (OSS or Platform). |
-| Semantic memory | `semantic_memory` | **Not implemented** | Defined in the `MemoryType` enum but never read anywhere else in the codebase. Passing it to `add()` raises a validation error. There is no evidence in this repo of a roadmap date for this. |
-| Episodic memory | `episodic_memory` | **Not implemented** | Same as above: defined, never wired into the extraction pipeline, rejected by validation, no documented roadmap. |
-
-<Warning>
-  Only `procedural_memory` is a real, working value. Calling `memory.add(messages, memory_type="semantic_memory")` (or `episodic_memory`) is rejected and tells you to pass `procedural_memory` instead. Sync `Memory.add()` raises `Mem0ValidationError`; `AsyncMemory.add()` raises a plain `ValueError`.
-</Warning>
-
-## Procedural memory
-
-Procedural memory stores step-by-step task knowledge (how an agent performs a workflow) rather than facts about a user. It requires `agent_id`:
-
-```python
-from mem0 import Memory
-
-memory = Memory()
-
-memory.add(
-    [
-        {"role": "user", "content": "Book a flight from SFO to NYC"},
-        {"role": "assistant", "content": "1. Search flights. 2. Filter by price. 3. Confirm booking."},
-    ],
-    agent_id="travel-agent",
-    memory_type="procedural_memory",
-)
-```
-
-Omit `memory_type` entirely and Mem0 stores the messages as an ordinary memory: there is no semantic/episodic pathway for it to fall into. Any other explicit value is rejected by validation rather than quietly falling back to an ordinary memory.
-
-## How every other memory is scoped
-
-Outside of the `procedural_memory` special case, Mem0 does not sort memories into named types. Every memory is scoped by the identifiers you pass in, and the same identifiers are used to retrieve it later:
-
- **`user_id`**: ties a memory to a specific person or account.
- **`agent_id`**: ties a memory to a specific agent or assistant persona.
- **`run_id`**: ties a memory to a specific session, task, or conversation thread.
- **`app_id`** (Platform only): ties a memory to a specific application or tenant, in addition to the three above. See <Link href="/platform/features/entity-scoped-memory">Entity-Scoped Memory</Link>.
-
-At least one identifier is required on `add()`. Passing more than one narrows the scope further (for example, `user_id` + `run_id` together).
-
-```python
-from mem0 import Memory
-
-memory = Memory()
-
-memory.add(
-    "I'm Alex and I prefer boutique hotels.",
-    user_id="alex",
-    run_id="trip-planning-2025",
-)
-
-results = memory.search(
-    "Any hotel preferences?",
-    filters={"user_id": "alex", "run_id": "trip-planning-2025"},
-)
-```
-
-<Tip>
-  Use `run_id` when you want a set of memories to stay tied to one session or task; use `user_id` alone for anything that should persist across every session for that person.
-</Tip>
-
-## How memories are extracted and updated
-
-When `infer=True` (the default) on `add()`, Mem0 runs a single pipeline rather than routing through separate type-specific paths:
-
-1. **Context gathering**: pulls the most recent messages already stored for the same `user_id`/`agent_id`/`run_id` scope.
-2. **Existing memory retrieval**: embeds the new messages and runs a vector search against memories already in that same scope, to find candidates that might need to change.
-3. **Extraction**: a single LLM call compares the new messages against the retrieved candidates and decides, per fact, whether to `ADD`, `UPDATE`, `DELETE`, or leave a memory alone.
-
-Alongside this, both OSS and Platform extract named entities (people, places, organizations) from memory text and use shared entities between memories to boost related results at search time. On Platform, that entity graph is also queryable directly; see <Link href="/platform/features/graph-memory">Graph Memory</Link>. In OSS, entities only affect ranking, there is no separate graph to query.
-
-<Warning>
-  Avoid storing secrets or unredacted PII in memories: they are retrievable by design. Encrypt or hash sensitive values before calling `add()`.
-</Warning>
-
-## Put it into practice
-
-<CardGroup cols={2}>
-  <Card
-    title="Explore Memory Operations"
-    description="Dive into the add/search/update/delete operations next."
-    icon="circle-check"
-    href="/core-concepts/memory-operations/add"
-  />
-  <Card
-    title="Advanced Memory Operations"
-    description="Tune metadata, filters, and retrieval on Platform."
-    icon="sliders"
-    href="/platform/advanced-memory-operations"
-  />
-  <Card
-    title="AI Tutor Cookbook"
-    description="See user_id-scoped memory used in a real tutoring agent."
-    icon="rocket"
-    href="/cookbooks/companions/ai-tutor"
-  />
-  <Card
-    title="Support Inbox Cookbook"
-    description="See user_id-scoped memory used in a support workflow."
-    icon="inbox"
-    href="/cookbooks/operations/support-inbox"
-  />
-</CardGroup>
@@ -41,6 +41,7 @@
                    "pages": [
                      "platform/quickstart",
                      "platform/overview",
+                      "platform/copilot",
                      "platform/agent-signup",
                      "vibecoding",
                      "platform/cli",
@@ -53,7 +54,6 @@
                    "icon": "brain",
                    "pages": [
                      "core-concepts/how-it-works",
-                      "core-concepts/memory-types",
                      "core-concepts/memory-operations/add",
                      "core-concepts/memory-operations/search",
                      "core-concepts/memory-operations/update",
@@ -71,6 +71,7 @@
                        "pages": [
                          "platform/features/v2-memory-filters",
                          "platform/features/entity-scoped-memory",
+                          "platform/features/user-profiles",
                          "platform/features/graph-memory",
                          "platform/features/async-client",
                          "platform/features/multimodal-support",
@@ -443,7 +444,8 @@
                      "cookbooks/integrations/mastra-agent",
                      "cookbooks/integrations/healthcare-google-adk",
                      "cookbooks/integrations/aws-bedrock",
-                      "cookbooks/integrations/tavily-search"
+                      "cookbooks/integrations/tavily-search",
+                      "cookbooks/integrations/supabase"
                    ]
                  },
                  {
@@ -511,6 +513,17 @@
                      "api-reference/entities/delete-user"
                    ]
                  },
+                  {
+                    "group": "Profiles",
+                    "icon": "id-card",
+                    "pages": [
+                      "api-reference/profiles/get-profile",
+                      "api-reference/profiles/get-profile-settings",
+                      "api-reference/profiles/update-profile-settings",
+                      "api-reference/profiles/generate-profiles",
+                      "api-reference/profiles/get-profile-job"
+                    ]
+                  },
                  {
                    "group": "Organizations",
                    "icon": "building",
@@ -1019,7 +1032,11 @@
    },
    {
      "source": "/concepts/memory-scoring",
-      "destination": "/core-concepts/memory-types"
+      "destination": "/core-concepts/how-it-works"
+    },
+    {
+      "source": "/core-concepts/memory-types",
+      "destination": "/core-concepts/how-it-works"
    },
    {
      "source": "/cookbooks/research-copilot",
@@ -1,7 +1,6 @@
 ---
-title: Overview
-seo:
-  title: "Integrations Overview - Mem0"
+title: "Integrations Overview"
+sidebarTitle: "Overview"
 description: "Overview of Mem0 integrations with popular AI frameworks and tools for persistent memory and context management."
 ---

@@ -17,6 +16,8 @@ Mem0 seamlessly integrates with popular AI frameworks and tools to enhance your
  **Universal Integration**: Use <Link href="/platform/mem0-mcp">Mem0 MCP</Link> for a standardized protocol that works with ANY AI client.
 </Callout>

+Sidekick is available only in the [Claude Code plugin](/integrations/claude-code#sidekick-agent). Other plugins, including the portable package, provide memory without Sidekick.
+
 Here are the available integrations for Mem0:

 ## Integrations
@@ -7,6 +7,8 @@ Add persistent memory to [**Google Antigravity**](https://antigravity.google) (`

 <Info>Current plugin version: `0.3.1`.</Info>

+Sidekick is available only in the [Claude Code plugin](/integrations/claude-code#sidekick-agent).
+
 ## Prerequisites

 1. A Mem0 API key (starts with `m0-`):
@@ -26,6 +28,10 @@ echo 'export MEM0_API_KEY="m0-your-api-key"' >> ~/.bashrc && source ~/.bashrc
 ```
 </CodeGroup>

+<Tip>
+  Already set up the [Mem0 CLI](/platform/cli) with `mem0 init`? The Mem0 plugin also reads the key it saved in `~/.mem0/config.json`, so you can skip this step. `MEM0_API_KEY` takes precedence when set.
+</Tip>
+
 ## Installation

 **Option A: degit** (recommended):
@@ -48,11 +54,10 @@ This installs the generated Antigravity bundle with the Mem0 server, lifecycle h
 | Local MCP Server (`search_memories`) | Yes |
 | Lifecycle Hooks | Yes |
 | 6 Memory Skills | Yes |
-| Sidekick Agent | Yes |

 ## Memory tools and skills

-The full plugin exposes a focused `search_memories` tool and captures completed work through lifecycle hooks. Six skills provide search, status, remember, forget, pause, and resume workflows. A native sidekick can handle a bounded task in the workspace assigned by Antigravity; it does not claim Claude Code worktree isolation.
+The full plugin exposes a focused `search_memories` tool and captures completed work through lifecycle hooks. Six skills provide search, status, remember, forget, pause, and resume workflows.

 If you need the full set of direct CRUD tools, connect the [hosted Mem0 MCP server](/platform/mem0-mcp) separately instead of installing both configurations under the same server name.

@@ -1,7 +1,6 @@
 ---
-title: AWS Bedrock
-seo:
-  title: "AWS Bedrock Integration with Mem0"
+title: "AWS Bedrock Integration"
+sidebarTitle: "AWS Bedrock"
 description: "Use Mem0 with AWS Bedrock and OpenSearch Service for cloud-native persistent semantic memory storage."
 ---

@@ -130,10 +130,10 @@ print(response.msgs[0].content)

 <CardGroup cols={2}>
  <Card
-    title="Memory types in Mem0"
-    description="Choose between chat history and semantic search for your Camel agents."
+    title="How Mem0 works"
+    description="Understand how Mem0 extracts, stores, and retrieves memories for your Camel agents."
    icon="sparkles"
-    href="/core-concepts/memory-types"
+    href="/core-concepts/how-it-works"
  />
  <Card
    title="Try LangChain next"
@@ -64,6 +64,8 @@ After the automatic first-prompt search, Claude can also call `search_memories`

 ### Sidekick agent

+Sidekick is available only in Claude Code.
+
 `mem0:sidekick` is a Sonnet coding agent that runs in a separate Git worktree. Use it to offload investigation, implementation, testing, or review without burning main-session context.

 ```text
@@ -164,12 +166,42 @@ claude plugin update mem0@mem0-plugins --scope user

 | Problem | Fix |
 | --- | --- |
-| Missing key | Reinstall with `--config api_key="$MEM0_API_KEY"` while the var is set. |
+| Missing key | Reinstall with `--config api_key="$MEM0_API_KEY"` while the var is set, or run `mem0 init` with the [Mem0 CLI](/platform/cli). The plugin falls back to the key it saves. |
 | `401 Unauthorized` | API key is invalid or expired. Run `/mem0:status` to confirm. |
 | No memory after ending a session | Extraction runs in the background. Wait a moment, then search again. |
 | Sidekick won't start | Must be in a Git repo. Check that your Claude Code version supports plugin agents and worktrees. |
 | Remove the plugin | `claude plugin uninstall mem0@mem0-plugins` |

+## Telemetry
+
+The plugin sends usage events (which hook ran, timing, result counts, failure
+types) so Mem0 can see what's used and what's breaking.
+
+These events are **not anonymous**. When an API key is configured, which
+installing the plugin requires, they are sent under your Mem0 account email,
+the same way the Python SDK and the CLI attribute theirs. Without a key they
+are sent under a random per-machine id.
+
+Each event carries the event name, the plugin version, the harness it ran in,
+your OS and Python version, and per-event properties describing what happened:
+timings, counts, coarse outcome and failure labels, and which model was
+configured. Repository and session identifiers are hashed with a random salt
+generated on your machine, so they cannot be linked back to a repository name
+or path.
+
+The exact set is enforced in code rather than by this list: every property is
+filtered through a denylist of sensitive keys and credential-shaped values are
+redacted before anything is sent.
+
+Prompts, memory text, queries, file paths, repository names, and API keys are
+never sent.
+
+Turn it off:
+
+```bash
+export MEM0_TELEMETRY=false
+```
+
 <CardGroup cols={2}>
  <Card title="Mem0 MCP Setup" icon="puzzle-piece" href="/platform/mem0-mcp">
    Detailed MCP configuration for all clients
@@ -3,10 +3,12 @@ title: Codex
 description: "Add persistent memory to OpenAI Codex with automatic capture, automatic recall, a search tool, and six memory skills."
 ---

-Add persistent memory to [**OpenAI Codex**](https://openai.com/index/codex/) with the Mem0 plugin. Codex forgets everything between tasks. This plugin fixes that by connecting to Mem0's cloud memory layer via MCP, automatically capturing learnings at key lifecycle points, and retrieving relevant context on the first prompt of a session. Codex can use the search tool for recall later in the session.
+Add persistent memory to [**OpenAI Codex**](https://openai.com/codex/) with the Mem0 plugin. Codex forgets everything between tasks. This plugin fixes that by connecting to Mem0's cloud memory layer via MCP, automatically capturing learnings at key lifecycle points, and retrieving relevant context on the first prompt of a session. Codex can use the search tool for recall later in the session.

 <Info>Current plugin version: `0.3.1`.</Info>

+Sidekick is available only in the [Claude Code plugin](/integrations/claude-code#sidekick-agent).
+
 ## Prerequisites

 Before setting up Mem0 with Codex, ensure you have:
@@ -33,6 +35,10 @@ source ~/.bashrc
 ```
 </CodeGroup>

+<Tip>
+  Already set up the [Mem0 CLI](/platform/cli) with `mem0 init`? The plugin (Option A) also reads the key it saved in `~/.mem0/config.json`, so you can skip this step. `MEM0_API_KEY` takes precedence when set.
+</Tip>
+
 ## Installation

 ### Option A: Plugin Marketplace (Recommended)
@@ -7,6 +7,8 @@ Add persistent memory to [**Cursor**](https://cursor.com) with the Mem0 plugin.

 <Info>Current plugin version: `0.3.1`.</Info>

+Sidekick is available only in the [Claude Code plugin](/integrations/claude-code#sidekick-agent).
+
 ## Prerequisites

 Before setting up Mem0 with Cursor, ensure you have:
@@ -33,6 +35,10 @@ source ~/.bashrc
 ```
 </CodeGroup>

+<Tip>
+  Already set up the [Mem0 CLI](/platform/cli) with `mem0 init`? The full plugin (Option A) also reads the key it saved in `~/.mem0/config.json`, so you can skip this step. That includes Cursor opened from the Dock, which does not load your shell profile. A key from the plugin configuration or the environment takes precedence.
+</Tip>
+
 <Warning>
  Already have `mem0` configured as an MCP server in Cursor? Remove the existing entry from your Cursor MCP settings before installing to avoid duplicate tools.
 </Warning>
@@ -49,7 +55,7 @@ cursor-agent plugin marketplace add https://github.com/mem0ai/mem0

 Open Cursor's **Customize** page or run `/plugins`, select the **Mem0 Plugins** marketplace, and install **Mem0** at user or project scope. Enter your Mem0 API key when Cursor asks for the plugin configuration, then restart Cursor.

-The full plugin includes automatic capture, the `search_memories` recall tool, lifecycle hooks, a sidekick agent, and six memory skills.
+The full plugin includes automatic capture, the `search_memories` recall tool, lifecycle hooks, and six memory skills.

 ### Option B: One-Click Deeplink (MCP Only)

@@ -98,7 +104,6 @@ Add the following to your `.cursor/mcp.json`:
 | Recall | `search_memories` | MCP search tools |
 | Lifecycle hooks | Yes | No |
 | Memory skills | 6 | No |
-| Sidekick agent | Yes | No |

 ## MCP-only tools

@@ -125,15 +130,14 @@ The full plugin translates Cursor's native events into the shared Mem0 memory li
 | `sessionStart` | Initializes the project session and recovers pending capture |
 | `beforeSubmitPrompt` | Observes the submitted prompt; recall stays tool-driven because this event cannot inject context |
 | `postToolUse` / `postToolUseFailure` | Records useful tool results and failures |
-| `subagentStart` / `subagentStop` | Records the Mem0 Sidekick lifecycle and completed result |
 | `afterAgentResponse` / `stop` | Captures the completed exchange |
 | `preCompact` / `sessionEnd` | Flushes pending capture in the background |

 <Note>
-  Cursor's `beforeSubmitPrompt` hook can allow or block a prompt, but it cannot add context to that prompt. The plugin therefore gives the agent `search_memories` and a memory-aware sidekick for recall instead of claiming automatic per-prompt injection.
+  Cursor's `beforeSubmitPrompt` hook cannot add context to a prompt. Use `search_memories` to recall memories.
 </Note>

-Cursor's `subagentStart` hook also cannot inject parent context. The bundled Sidekick searches Mem0 itself, while the lifecycle hooks correlate its start and completion for later capture.
+The plugin does not register subagent start or stop hooks.

 ## Example Workflow

@@ -164,6 +168,7 @@ Captured prompts and responses retain their full redacted text without a per-mes
 ## Troubleshooting

 - **"Connection failed"**: Verify `MEM0_API_KEY` is set: `echo $MEM0_API_KEY`
+- **Still asked for an API key**: Run `mem0 init` with the [Mem0 CLI](/platform/cli). The full plugin falls back to the key it saves.
 - **Duplicate tools**: Do not combine the full plugin with an MCP-only option. Remove the standalone `mem0` MCP entry before installing the plugin.
 - **No tools appearing**: Go to Cursor Settings > MCP and verify the `mem0` server shows as connected

@@ -7,6 +7,8 @@ Add persistent memory to the [**DeepSeek Harness**](https://github.com/deepseek-

 <Info>Current package version: `0.3.0`.</Info>

+Sidekick is available only in the [Claude Code plugin](/integrations/claude-code#sidekick-agent).
+
 ## Overview

 The plugin provides automatic memory plus two agent-callable tools:
@@ -54,6 +56,10 @@ source ~/.bashrc
 ```
 </CodeGroup>

+<Tip>
+  Already set up the [Mem0 CLI](/platform/cli) with `mem0 init`? The plugin also reads the key it saved in `~/.mem0/config.json`, so you can skip this step. `config.apiKey` and `MEM0_API_KEY` take precedence.
+</Tip>
+
 ## Try it locally

 1. Build and pack the plugin:
@@ -101,7 +107,7 @@ For a Mem0 Platform on-prem or dedicated deployment, point `config.host` at that

 | Field | Required | Default | Notes |
 |---|---|---|---|
-| `apiKey` | no | `$MEM0_API_KEY` | Mem0 platform API key |
+| `apiKey` | no | `$MEM0_API_KEY` | Mem0 platform API key. Falls back to the key `mem0 init` saved. |
 | `userId` | yes | | Default entity that owns the memories |
 | `allowUserOverride` | no | `false` | Permit model-selected access to a different user only in a trusted multi-user deployment |
 | `host` | no | `api.mem0.ai` | Platform base URL (on-prem / dedicated) |
@@ -112,7 +118,7 @@ Both tools also accept optional per-call `userId`, `agentId`, and `runId` params

 ## Telemetry

-Writes are tagged `source="DEEPSEEK_HARNESS"` so Mem0 can attribute usage to this integration. Anonymous usage events include operation names, durations, result counts, and coarse failure kinds. Queries, memory text, entity IDs, and API keys are never included. Set `MEM0_TELEMETRY=false` to opt out.
+Writes are tagged `source="DEEPSEEK_HARNESS"` so Mem0 can attribute usage to this integration. Usage events include operation names, durations, result counts, and coarse failure kinds. They are **not anonymous**: when an API key is configured they are sent under your Mem0 account email, the same way the SDK attributes its own. Queries, memory text, entity IDs, and API keys are never included. Set `MEM0_TELEMETRY=false` to opt out.

 <Note>
  This plugin is a developer preview and tracks the evolving DeepSeek Harness plugin API.
@@ -23,7 +23,7 @@ npm install -g flowise
 npx flowise start
 ```

-2. Access to the Flowise UI at http://localhost:3000
+2. Access to the Flowise UI at `http://localhost:3000`
 3. Basic familiarity with [Flowise's LLM orchestration](https://flowiseai.com/#features) concepts

 ## Setup and Configuration
@@ -1,53 +1,65 @@
 ---
 title: Hermes Agent
-description: "Add long-term memory to Hermes agents with Mem0, on managed Mem0 Cloud or fully self-hosted (OSS), with automatic background sync and zero-latency prefetch."
+description: "Add persistent memory to Hermes Agent with Mem0 Cloud, a self-hosted server, or the in-process OSS SDK."
 ---

-Add long-term memory to [Hermes Agent](https://github.com/NousResearch/hermes-agent), a self-improving AI agent CLI by Nous Research. Hermes has a pluggable memory system, and Mem0 is one of the supported providers. Once enabled, Mem0 learns facts from your conversations and surfaces relevant ones before each turn, without slowing down the chat.
+Add long-term memory to [Hermes Agent](https://github.com/NousResearch/hermes-agent), a self-improving AI agent CLI by Nous Research. The [standalone Mem0 plugin](https://github.com/mem0ai/mem0/tree/main/integrations/hermes-plugin-mem0) learns facts from conversations and recalls relevant memories for the current question.

-You can run Mem0 in two ways:
+You can run Mem0 in three ways:

 - **Platform mode** (default): managed Mem0 Cloud. Add your API key and you are ready.
- **OSS mode**: fully self-hosted with your own LLM, embedder, and vector store. No data leaves your machine.
+- **Self-hosted server mode**: point the plugin at a Mem0 server you run yourself (the Docker-shipped server). The plugin only talks HTTP to your server.
+- **OSS mode**: run Mem0 in-process with your own LLM, embedder, and vector store. No Mem0 server required.

 ## How It Works

-Hermes runs a built-in memory system (file-based `MEMORY.md` and `USER.md`) alongside one external provider. When Mem0 is active, it works additively with the built-in system at three points in every conversation turn.
+Hermes runs a built-in memory system (file-based `MEMORY.md` and `USER.md`) alongside one external provider. When Mem0 is active, it works additively with the built-in system at two points in every conversation turn.

-### 1. Before the agent responds (prefetch)
+### 1. Current-turn recall (bounded wait)

-When you send a message, Hermes checks for cached Mem0 search results from the previous turn. If they exist, those memories are injected into the system prompt so the model can see them. This is zero-latency, with no waiting on an API call.
+When you send a message, Hermes searches your stored memories for the current question and waits up to 3 seconds for results. If they arrive in time, they are injected into the system prompt so the model can see them. If the backend is slower, Hermes skips the injection and the model can still call `mem0_search` itself after the bounded recall wait.

-### 2. After the agent responds (sync)
+### 2. Background fact extraction (sync)

-Once the model finishes, Hermes sends the `(user message, assistant response)` pair to Mem0 in a background thread. Mem0 extracts facts automatically (for example, "user prefers Python" or "user works at Acme Corp"), so you never have to tell it what to remember. Each write is tagged with the gateway channel it came from.
+Once the model finishes, the plugin sends the user message and assistant response to Mem0 in a background thread for fact extraction. Each write includes the agent identifier and gateway channel.

-### 3. Background prefetch for the next turn
-
-At the same time, Hermes runs a background search to pre-load relevant memories for your next message. By the time you type, the results are already cached.
+<Note>
+  Automatic capture truncates each message to **450 characters by default in every mode**, preferring a sentence boundary. Adjust `sync_max_chars` for your model's context limit. Capture is best effort: if the previous sync is still running after a five-second wait, the next turn is skipped. Use `mem0_add` to store specific text verbatim.
+</Note>

 ## Agent Tools

-When Mem0 is active, the model gets five tools it can call during a conversation:
+When Mem0 is active, the model gets four tools it can call during a conversation:

 | Tool | Description | Parameters |
 |------|-------------|------------|
-| `mem0_list` | List all stored memories, for a full overview | `page`, `page_size` (default 100, max 200) |
-| `mem0_search` | Semantic search by meaning, ranked by relevance | `query` (required), `top_k` (default 10, max 50), `rerank` (default `true`, Platform mode only) |
+| `mem0_search` | Semantic search by meaning, ranked by relevance | `query` (required), `top_k` (default 10, max 50), `rerank` (uses the configured default, Platform mode only) |
 | `mem0_add` | Store a fact verbatim, with no LLM extraction | `content` (required) |
 | `mem0_update` | Update a memory's text by ID | `memory_id`, `text` (both required) |
 | `mem0_delete` | Delete a memory by ID | `memory_id` (required) |

 ## Installation

-Install Hermes Agent:
+Install [Hermes Agent](https://github.com/NousResearch/hermes-agent) with memory-provider plugin support and Python 3.11 or later. Once the plugin directory is available on Mem0's main branch, install it from the repository subdirectory:

 ```bash
-curl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash
-source ~/.bashrc
+hermes plugins install mem0ai/mem0/integrations/hermes-plugin-mem0
+hermes plugins enable mem0
+hermes memory setup
+hermes memory status
 ```

-The `mem0ai` package is installed automatically when you enable the Mem0 provider, so there is no manual pip step. OSS providers may need extra packages (for example `qdrant-client`, `psycopg2-binary`, or `ollama`), which the setup flow installs for you when you pick them.
+Select **mem0** in setup and choose one of the modes below. Start a fresh Hermes conversation after setup.
+
+Hermes installers with plugin dependency support install `mem0ai>=2.0.10,<3` and `httpx>=0.27,<1` from the plugin's `pyproject.toml`. Older hosts such as Hermes v0.21.3 require those packages to be installed explicitly into the Hermes Python environment. The OSS setup flow installs additional provider packages as needed.
+
+<Note>
+  Hermes versions that still bundle Mem0 prefer the bundled provider. Use a Hermes release that has completed the standalone-provider migration; installing this plugin alone does not replace the bundled implementation. Existing users should keep their current configuration; see [Migration for existing users](#migration-for-existing-users).
+</Note>
+
+<Note>
+  Run the setup wizard in an interactive terminal. On Hermes hosts whose `hermes memory setup --help` lists only a provider argument, options such as `--mode`, `--host`, and `--oss-llm` are rejected by Hermes before the plugin runs. Use `hermes memory setup mem0` or the manual configuration below. Redirected input cannot select the mode picker and falls back to Platform.
+</Note>

 ## Platform Setup

@@ -56,10 +68,10 @@ Platform mode uses managed Mem0 Cloud and is the fastest way to start.
 ### Option 1: Interactive wizard (recommended)

 ```bash
-hermes memory setup
+hermes memory setup mem0
 ```

-Select **mem0**, choose **Platform**, and paste your API key when prompted. The wizard writes the non-secret settings to `~/.hermes/mem0.json` and keeps the key in `~/.hermes/.env`.
+Choose **Platform** and paste your API key when prompted. The wizard writes settings to `$HERMES_HOME/mem0.json` and keeps the key in that profile's `.env`. The default Hermes home is `~/.hermes`; named profiles use their own home directory.

 <Note>Get your API key from <a href="https://app.mem0.ai?utm_source=oss&utm_medium=integration-hermes">app.mem0.ai</a>.</Note>

@@ -67,37 +79,74 @@ Select **mem0**, choose **Platform**, and paste your API key when prompted. The

 ```bash
 hermes config set memory.provider mem0
-echo "MEM0_API_KEY=your-api-key" >> ~/.hermes/.env
 ```

-Then in your `config.yaml`:
+Add your key to the active Hermes profile's `.env`:

-```yaml
-memory:
-  provider: mem0
+```dotenv
+MEM0_API_KEY=your-api-key
 ```

-That's it. Mem0 runs automatically from here.
+Set these values in the active profile's `mem0.json`, choosing a stable user identity:

-## OSS (Self-Hosted) Setup
+```json
+{
+  "mode": "platform",
+  "host": "",
+  "user_id": "my-hermes-user"
+}
+```

-OSS mode runs Mem0 entirely on your own infrastructure: your LLM, your embedder, and your vector store. No data is sent to Mem0 Cloud, and no Mem0 API key is required.
+Remove any stale `MEM0_HOST` from the environment and profile `.env`, and remove an old inline `api_key` from `mem0.json` so the new `.env` key is used. The config command sets `memory.provider: mem0` in that profile's `config.yaml`. Restart Hermes and check `hermes memory status`.
+
+## Self-Hosted Server Setup
+
+Run the [Mem0 server](https://github.com/mem0ai/mem0/tree/main/server) (FastAPI + pgvector) from its Docker image and point the plugin at it. Unlike OSS mode, the plugin just talks HTTP to your server.

 ### Interactive

 ```bash
-hermes memory setup
-# Select "mem0", then "Open Source (self-hosted)"
+hermes memory setup mem0
+# Choose "Self-hosted server", then enter the server URL and API key
+```
+
+### Manual configuration
+
+Select `mem0` with `hermes config set memory.provider mem0`. Set these values in the active profile's `mem0.json`:
+
+```json
+{
+  "mode": "platform",
+  "host": "http://localhost:8888",
+  "user_id": "my-hermes-user"
+}
+```
+
+Add the server key to that profile's `.env`:
+
+```dotenv
+MEM0_API_KEY=your-admin-api-key
+```
+
+Remove an old inline `api_key` from `mem0.json` so the `.env` key is used. `MEM0_HOST` can also supply the server URL, but a non-empty `host` in `mem0.json` overrides it. Keep `mode` set to `platform` for the HTTP server backend.
+
+Then start a fresh Hermes session and call `mem0_search` — it connects to your server. The plugin authenticates with `X-API-Key` and uses the server's `/search` and `/memories` routes. The API key is optional only for servers running with `AUTH_DISABLED`.
+
+<Note>Setting `host` routes to the self-hosted server automatically. Don't combine it with `mode: oss` — OSS takes precedence and ignores `host`.</Note>
+
+## OSS (Self-Hosted) Setup
+
+OSS mode runs the Mem0 SDK in the Hermes process with your chosen LLM, embedder, and vector store. It does not use Mem0 Cloud or require a Mem0 API key. Data goes to the model services you configure; use local Ollama models and local storage for a fully local setup.
+
+### Interactive
+
+```bash
+hermes memory setup mem0
+# Choose "Open Source"
 # Follow the prompts for LLM, embedder, and vector store
 ```

-### With flags
-
-```bash
-hermes memory setup mem0 --mode oss \
-  --oss-llm openai --oss-llm-key sk-... \
-  --oss-vector qdrant
-```
+The wizard uses the listed default OpenAI models and local Qdrant storage. For custom OpenAI-compatible endpoints, deployment names, or a Qdrant server, use manual configuration below.

 ### Supported providers

@@ -107,79 +156,91 @@ hermes memory setup mem0 --mode oss \
 | Embedder | `openai` (default `text-embedding-3-small`), `ollama` (local, default `nomic-embed-text`) |
 | Vector store | `qdrant` (local path or server), `pgvector` |

-### Flag reference
-
-| Flag | Description |
-|------|-------------|
-| `--mode` | `platform` or `oss` |
-| `--oss-llm` | LLM provider (`openai` or `ollama`, default `openai`) |
-| `--oss-llm-key` | LLM API key (for `openai`) |
-| `--oss-llm-model` | Override the LLM model |
-| `--oss-llm-url` | LLM base URL (for `ollama` or a custom endpoint) |
-| `--oss-embedder` | Embedder provider (default `openai`) |
-| `--oss-embedder-key` | Embedder API key |
-| `--oss-vector` | Vector store (`qdrant` or `pgvector`, default `qdrant`) |
-| `--oss-vector-path` | Local Qdrant storage path |
-| `--oss-vector-host`, `--oss-vector-port` | PGVector or remote Qdrant host and port |
-| `--oss-vector-user`, `--oss-vector-password`, `--oss-vector-dbname` | PGVector connection details |
-| `--user-id` | Canonical user identifier |
-| `--dry-run` | Preview the resolved config without writing it |
-
-## Switching Modes
-
-You can move between Platform and OSS at any time. Run the setup command again, or edit `~/.hermes/mem0.json` directly.
+### Manual configuration

 ```bash
-# Platform to OSS
-hermes memory setup mem0 --mode oss --oss-llm-key sk-...
-
-# OSS to Platform
-hermes memory setup mem0 --mode platform --api-key sk-...
-
-# Preview without writing anything
-hermes memory setup mem0 --mode oss --oss-llm-key sk-... --dry-run
+hermes config set memory.provider mem0
 ```

-A self-hosted `~/.hermes/mem0.json` looks like this:
+Add the model key to the active profile's `.env`:
+
+```dotenv
+OPENAI_API_KEY=your-model-api-key
+```
+
+Set the following in that profile's `mem0.json`. Use your existing storage path when migrating; for a new named profile, choose a path inside that profile's home.

 ```json
 {
  "mode": "oss",
+  "user_id": "my-hermes-user",
  "oss": {
-    "llm": {"provider": "openai", "config": {"model": "gpt-5-mini"}},
+    "llm": {"provider": "openai", "config": {"model": "gpt-5-mini", "is_reasoning_model": true}},
    "embedder": {"provider": "openai", "config": {"model": "text-embedding-3-small"}},
    "vector_store": {"provider": "qdrant", "config": {"path": "~/.hermes/mem0_qdrant"}}
  }
 }
 ```

+For an OpenAI-compatible service such as Azure's `/openai/v1` endpoint, add `OPENAI_BASE_URL` to the profile's `.env` and set each `model` to its deployed name. Both the LLM and embedder use this endpoint unless their `config.openai_base_url` overrides it. The main Hermes chat model is configured separately; this JSON configures Mem0's extraction and embedding models.
+
+For a Qdrant server, replace `vector_store.config.path` with `url`, for example `"url": "http://localhost:6333"`. Manual setup does not install optional provider dependencies: install `qdrant-client`, `psycopg2-binary`, or `ollama` in the **Hermes Python environment** as needed for your selected providers. Start a fresh session and verify a memory write and search; `hermes memory status` reports configuration availability, not a full backend health check.
+
+Desktop sessions in the same process and profile share local Qdrant storage when their OSS settings match. Operations are serialized, and storage closes after the last session releases it. Conflicting settings are rejected without changing existing memories; close active sessions before changing models or credentials. For concurrent CLI and Desktop processes, use a Qdrant server or the self-hosted Mem0 HTTP API instead of sharing a local directory.
+
+## Switching Modes
+
+Run `hermes memory setup mem0` in an interactive terminal and choose the new mode, or edit the active profile's `mem0.json` using the examples above. Switching backends does not transfer memories between them. Preserve existing OSS storage paths when editing configuration. When returning to Platform, set `mode` to `platform`, clear `host`, and remove any stale `MEM0_HOST` setting from your environment and profile `.env`.
+
 ## Configuration

-Behavioral settings live in `~/.hermes/mem0.json` and are written for you by `hermes memory setup`. Only the secret `MEM0_API_KEY` belongs in `~/.hermes/.env`.
+Settings live in `$HERMES_HOME/mem0.json` and are written by `hermes memory setup`. API keys normally live in that profile's `.env`; distinct OpenAI LLM/embedder keys and database credentials are stored in the OSS configuration. Setup writes these files atomically with owner-only permissions.
+
+When editing these files manually, restrict both `.env` and `mem0.json` to their owner (`chmod 600` on Unix). Keep configuration and secrets in the same active Hermes profile.
+
+`MEM0_MODE`, `MEM0_HOST`, `MEM0_USER_ID`, and `MEM0_AGENT_ID` supply environment defaults. Non-empty values in `mem0.json` take precedence. `MEM0_API_KEY` supplies the Cloud or server key unless `api_key` is set in the file.

 | Key | Default | Description |
 |-----|---------|-------------|
-| `mode` | `platform` | `platform` (Mem0 Cloud) or `oss` (self-hosted) |
-| `api_key` | none | Mem0 Platform API key, required in Platform mode. Stored in `.env` as `MEM0_API_KEY` |
-| `user_id` | `hermes-user` | Identifier that scopes memories. See cross-channel behavior below |
+| `mode` | `platform` | `platform` (Mem0 Cloud) or `oss` (self-managed, in-process). Self-hosted server routing is set via `host` |
+| `host` | none | Self-hosted Mem0 server URL. When set, the plugin talks HTTP to your server instead of the cloud |
+| `api_key` | none | Mem0 Platform API key, or the admin key of a self-hosted server. Stored in `.env` as `MEM0_API_KEY` |
+| `user_id` | gateway user ID, then `hermes-user` | Identifier that scopes memories. See cross-channel behavior below |
 | `agent_id` | `hermes` | Agent identifier attached to writes |
-| `rerank` | `true` | Rerank search results for relevance (Platform mode only) |
+| `rerank` | `false` | Platform reranking for recall and tool searches that omit `rerank` |
+| `sync_max_chars` | `450` | Per-message character cap for automatic fact extraction in every mode |
+| `oss` | `{}` | OSS LLM, embedder, and vector-store configuration |

 ### Cross-channel memories

 Hermes can run from the CLI and from gateways like Telegram, Slack, and Discord. The `user_id` setting controls how memories are scoped across them:

- **Set a `user_id`** and it applies to every gateway, so one person gets a single merged memory store no matter where they talk to the agent.
- **Leave it unset** (or at the default `hermes-user`) and each gateway uses its own native id, keeping per-platform memories separate.
+- **Set a `user_id` other than `hermes-user`** and it applies to every gateway, so one person gets a single merged memory store no matter where they talk to the agent.
+- **Leave it unset** (or at the default `hermes-user`) and each gateway uses its own native ID when available, falling back to `hermes-user`.

-Either way, every write is tagged with `metadata.channel` (for example `telegram` or `cli`), so per-channel views are still possible at query time.
+Every write is tagged with `metadata.channel` (for example `telegram` or `cli`). Plugin searches filter by user identity across sessions; they do not restrict recall to the current channel or session.

+## Migration for Existing Users
+
+Keep `memory.provider: mem0`, `mem0.json`, `MEM0_*` settings, user identity, and OSS database paths unchanged. Moving from the bundled provider to this standalone plugin does not require rerunning setup or moving stored memories.
+
+Automatic migration depends on Hermes rollout as well as this repository:
+
+1. Users need a Hermes build containing [PR #114569](https://github.com/NousResearch/hermes-agent/pull/114569).
+2. Hermes maintainers must approve a catalog entry named `mem0` with `repo: https://github.com/mem0ai/mem0`, `subdir: integrations/hermes-plugin-mem0`, and a reviewed full commit SHA.
+3. The bundled Mem0 provider must be removed so the standalone provider can load.
+
+With these in place, Hermes installs a missing configured provider during `hermes update` across profiles or at agent startup. Startup installation respects `security.allow_lazy_installs`. Offline or disabled installation needs manual action; merging the plugin directory alone does not complete automatic migration.
+
+CLI setup and status are supported. This plugin does not ship a Desktop configuration panel or provider-specific CLI commands.

 ## Reliability

- **Circuit breaker**: if Mem0 fails five times in a row, Hermes pauses calls for two minutes, then retries. The agent keeps working without memory during that window. Expected client errors, like a 404 on a missing memory id, do not count toward tripping the breaker.
- **Non-blocking**: every Mem0 call runs in a background daemon thread, so a slow or failed call never blocks your conversation.
- **Thread-safe**: the client uses lazy initialization with locking, and the background sync and prefetch threads are guarded so concurrent gateway messages cannot produce duplicate memories.
+- **Circuit breaker**: five consecutive backend failures pause calls for two minutes. The agent can continue without memory during that window. Expected update/delete errors such as a missing memory do not trip the breaker.
+- **Bounded waits**: recall waits up to three seconds. Capture runs in the background, but an overlapping turn may wait up to five seconds for the previous sync before being skipped.
+- **Graceful shutdown**: shutdown and Python process exit wait for active recall and capture workers before closing the backend. Backend network timeouts still apply. Self-hosted HTTP capture uses a 120-second read timeout and a 30-second connection timeout; other self-hosted HTTP operations use 30 seconds.
+- **Best-effort capture**: there is no durable queue. Forced termination, including Hermes' 30-second exit watchdog, can interrupt pending writes even while graceful shutdown is waiting.
+- **OSS data protection**: an embedding dimension mismatch fails initialization without deleting the existing collection or table.

 ## Troubleshooting

@@ -188,6 +249,7 @@ Either way, every write is tagged with `metadata.channel` (for example `telegram
 The circuit breaker tripped after five consecutive failures and resets after two minutes.

 - **Platform mode**: check your API key and internet connection.
+- **Self-hosted server mode**: check that the server is running and reachable at the configured `host` URL.
 - **OSS mode**: make sure your vector store (Qdrant or PGVector) is running and reachable.

 ### OSS: vector store connection refused
@@ -213,15 +275,12 @@ curl http://localhost:11434/api/tags

 - `mem0_add` stores text verbatim with no extraction. Ordinary conversation turns are extracted automatically by the background sync.
 - Search is semantic, so try a broader query.
- Confirm `user_id` is the same across sessions (check `~/.hermes/mem0.json`).
+- Confirm `user_id` is the same across sessions (check `$HERMES_HOME/mem0.json`).
+- Check `sync_max_chars`: facts beyond the per-message limit are not sent for extraction.

-## Key Features
+### OSS: embedding dimension mismatch

-1. **Two ways to run**: managed Platform or fully self-hosted OSS, switchable at any time.
-2. **Zero-latency recall**: memories are prefetched in the background and cached before you type.
-3. **Automatic extraction**: Mem0 extracts and deduplicates facts from each exchange for you.
-4. **Non-blocking and fault tolerant**: background threads plus a circuit breaker keep the agent responsive even when Mem0 is unreachable.
-5. **Additive memory**: works alongside Hermes' built-in file memory (`MEMORY.md`, `USER.md`).
+Restore the embedding model and dimensions that created the existing collection, or choose a new collection and migrate data explicitly. The plugin leaves the original collection intact when dimensions differ.

 <CardGroup cols={2}>
  <Card title="OpenClaw Integration" icon="/images/provider-icons/openclaw.svg" href="/integrations/openclaw">
@@ -7,6 +7,8 @@ Kimi Code forgets project decisions between sessions. The Mem0 plugin captures c

 <Info>Current plugin version: `0.3.1`.</Info>

+Sidekick is available only in the [Claude Code plugin](/integrations/claude-code#sidekick-agent).
+
 ## Prerequisites

 1. A Mem0 Platform account and API key:
@@ -33,7 +35,7 @@ Inside Kimi Code, install the native plugin bundle and reload the session:
 /reload
 ```

-Run `/plugins info mem0` to confirm that the plugin, MCP server, skills, hooks, and sidekick agent loaded.
+Run `/plugins info mem0` to confirm that the plugin, MCP server, skills, and hooks loaded.

 ## What you get

@@ -42,7 +44,6 @@ Run `/plugins info mem0` to confirm that the plugin, MCP server, skills, hooks,
 - **Explicit search:** Kimi can call `search_memories` when it needs a more specific answer.
 - **Six memory skills:** Search, status, remember, forget, pause, and resume use the same memory behavior as the other Mem0 coding-agent plugins.
 - **Project scoping:** Memories stay attached to the repository, with separate personal and shared project lanes.
- **Kimi sidekick:** A focused subagent can investigate or implement a bounded task in a separate context. Filesystem isolation depends on the environment Kimi provides.

 Credentials are redacted before memory capture. If Mem0 is unavailable, hooks fail open so Kimi can continue its normal work.

@@ -57,7 +58,8 @@ Kimi's native lifecycle events are translated into the shared Mem0 memory lifecy
 | `PostToolUse` / `PostToolUseFailure` | Records useful tool results and failures |
 | `Stop` | Captures the completed exchange |
 | `PreCompact` / `SessionEnd` | Flushes pending capture in the background |
-| `SubagentStart` / `SubagentStop` | Passes parent context to the Mem0 sidekick and records its lifecycle |
+
+The plugin does not register subagent start or stop hooks or supply parent memories to child agents.

 ## Verify the plugin

@@ -97,7 +99,7 @@ Captured prompts and responses retain their full redacted text without a per-mes

 | Problem | Fix |
 | --- | --- |
-| Missing API key | Start Kimi from a shell where `MEM0_API_KEY` is exported. |
+| Missing API key | Start Kimi from a shell where `MEM0_API_KEY` is exported, or run `mem0 init` with the [Mem0 CLI](/platform/cli). The plugin falls back to the key it saves. |
 | Plugin changes do not appear | Run `/plugins reload`, then `/reload` or `/new`. |
 | MCP server is disabled | Run `/plugins mcp enable mem0 mem0`, then `/reload`. |
 | No memory in a later session | Wait a moment for the background flush, then ask Kimi to search memory explicitly. |
@@ -1,7 +1,6 @@
 ---
-title: Langchain
-seo:
-  title: "LangChain Integration with Mem0"
+title: "LangChain Integration"
+sidebarTitle: "Langchain"
 description: "Build personalized AI agents using LangChain for conversation flow and Mem0 for long-term memory retention."
 ---

@@ -45,7 +45,7 @@ memory_from_client = Mem0Memory.from_client(
 )
 ```

-Context is used to identify the user, agent or the conversation in the Mem0. It is required to be passed in the at least one of the fields in the `Mem0Memory` constructor. It can be any of the following:
+Context is used to identify the user, agent or the conversation in the Mem0. It is required to be passed in at least one of the fields in the `Mem0Memory` constructor. It can be any of the following:

 ```python
 context = {
@@ -1,7 +1,6 @@
 ---
-title: n8n
-seo:
-  title: "n8n Integration with Mem0"
+title: "n8n Integration"
+sidebarTitle: "n8n"
 description: "Add long-term memory to n8n workflows and AI Agents with the Mem0 community node, no code required."
 ---

@@ -7,6 +7,8 @@ Add long-term memory to [OpenClaw](https://github.com/openclaw/openclaw) agents

 <Info>Current package version: `1.1.0`.</Info>

+Sidekick is available only in the [Claude Code plugin](/integrations/claude-code#sidekick-agent). OpenClaw subagents can recall parent memories. Mem0 does not capture their sessions.
+
 ## Overview

 <Frame>
@@ -479,7 +481,9 @@ Plugin config is stored in `~/.openclaw/openclaw.json` with file permissions `0o

 ### Telemetry

-Anonymous usage telemetry (PostHog) is enabled by default to help improve the plugin. No conversation content or memory values are included, only event counts (recall, capture, tool usage, CLI commands).
+Usage telemetry (PostHog) is enabled by default to help improve the plugin. No conversation content or memory values are included, only event counts (recall, capture, tool usage, CLI commands).
+
+These events are **not anonymous**. OpenClaw does not send your account email the way the SDK does, but it does send an unsalted SHA-256 hash of it, falling back to a hash of the API key and then to a random per-machine id. Mem0 holds the email the hash is derived from, so the hash identifies your account rather than concealing it. The first run that resolves an account also emits a PostHog `$identify`, which permanently merges any earlier random id into that identity.

 To opt out, set the environment variable:

@@ -7,6 +7,8 @@ Add persistent memory to [**OpenCode**](https://opencode.ai) with the Mem0 plugi

 <Info>Current package version: `0.3.0`.</Info>

+Sidekick is available only in the [Claude Code plugin](/integrations/claude-code#sidekick-agent).
+
 ## Prerequisites

 1. A Mem0 API key (starts with `m0-`):
@@ -24,6 +26,10 @@ echo 'export MEM0_API_KEY="m0-your-api-key"' >> ~/.bashrc && source ~/.bashrc
 ```
 </CodeGroup>

+<Tip>
+  Already set up the [Mem0 CLI](/platform/cli) with `mem0 init`? The OpenCode plugin also reads the key it saved in `~/.mem0/config.json`, so you can skip this step. `MEM0_API_KEY` and your shell profile take precedence.
+</Tip>
+
 ## Installation

 ### Option A: Plugin Install (Recommended)
@@ -7,6 +7,8 @@ Add persistent memory to [**Pi Agent**](https://pi.dev) with `@mem0/pi-agent-plu

 <Info>Current package version: `0.3.0`.</Info>

+Sidekick is available only in the [Claude Code plugin](/integrations/claude-code#sidekick-agent).
+
 ## Overview

 The plugin provides:
@@ -38,6 +40,10 @@ source ~/.bashrc
 ```
 </CodeGroup>

+<Tip>
+  Already set up the [Mem0 CLI](/platform/cli) with `mem0 init`? The extension also reads the key it saved in `~/.mem0/config.json`, so you can skip this step. `MEM0_API_KEY` and `apiKey` in `mem0-config.json` take precedence.
+</Tip>
+
 ## Installation

 ```bash
@@ -66,7 +72,7 @@ For advanced settings, create `~/.pi/agent/mem0-config.json`:

 | Key | Type | Default | Description |
 |-----|------|---------|-------------|
-| `apiKey` | `string` | `$MEM0_API_KEY` | Mem0 API key. Environment variable takes precedence. |
+| `apiKey` | `string` | `$MEM0_API_KEY` | Mem0 API key. Environment variable takes precedence. Falls back to the key `mem0 init` saved. |
 | `userId` | `string` | `$MEM0_USER_ID` or `"default"` | User identity for memory scoping |
 | `autoCapture` | `boolean` | `true` | Store facts from conversations automatically |
 | `defaultScope` | `string` | `"project"` | Default memory scope: `project`, `session`, or `global` |
@@ -145,7 +151,7 @@ You: What do you know about my preferences?

 ## Troubleshooting

- **"No API key found"**: Verify `MEM0_API_KEY` is set: `echo $MEM0_API_KEY`. If empty, add it to your shell profile (see Prerequisites)
+- **"No API key found"**: Verify `MEM0_API_KEY` is set: `echo $MEM0_API_KEY`. If empty, add it to your shell profile (see Prerequisites) or run `mem0 init`
 - **Extension not loading**: Check Pi startup output for errors. For a source checkout, run `pnpm build`, then `pi -e ./dist/entry.js` from the plugin directory
 - **Memories not capturing**: Verify `autoCapture` is `true` (default). Check `/mem0-status` for connection health
 - **Wrong project detected**: The plugin uses the git repository root as `app_id`. If not in a git repo, it falls back to the working directory name. Run `/mem0-status` to see the detected project
@@ -171,6 +171,7 @@ If the user is on a pre-current major (Python < 2, TS < 3, or a Platform call st
 - [Introduction](https://docs.mem0.ai/introduction) [Both]: Use when the user wants a one-page overview of how memory fits between the LLM and the app.
 - [Vibe Code with Mem0](https://docs.mem0.ai/vibecoding) [Both]: Use when the user is in Claude Code, Cursor, or Windsurf and wants memory wired into their editor.
 - [Platform Overview](https://docs.mem0.ai/platform/overview) [Platform]: Use when the user picks the managed product - 4-line integration, hosted API, dashboard.
+- [Mem0 Copilot](https://docs.mem0.ai/platform/copilot) [Platform]: Use when inspecting project memories, reviewing configuration changes, or testing extraction in the dashboard.
 - [Sign up as an agent](https://docs.mem0.ai/platform/agent-signup) [Platform]: Use when an AI agent needs to mint a Mem0 API key autonomously - four commands, no email or dashboard, human claims ownership later.
 - [Platform vs Open Source](https://docs.mem0.ai/platform/platform-vs-oss) [Both]: Use when the user is deciding between managed and self-hosted.
 - [Platform Quickstart](https://docs.mem0.ai/platform/quickstart) [Platform]: Use for the first Platform integration - API key plus `MemoryClient.add/search`.
@@ -185,7 +186,6 @@ If the user is on a pre-current major (Python < 2, TS < 3, or a Platform call st
 ## Core Concepts

 - [How Mem0 Works](https://docs.mem0.ai/core-concepts/how-it-works) [Both]: Use when explaining the end-to-end pipeline: extraction (ADD-only distillation), storage across vector/entity/history stores, and multi-signal retrieval.
- [Memory Types](https://docs.mem0.ai/core-concepts/memory-types) [Both]: Use when checking which `memory_type` values actually work: `procedural_memory` is implemented, `semantic_memory` and `episodic_memory` are defined in the enum but rejected by validation.
 - [Memory Operations - Add](https://docs.mem0.ai/core-concepts/memory-operations/add) [Both]: Use when explaining how `add()` extracts facts, resolves conflicts, and writes to both stores.
 - [Memory Operations - Search](https://docs.mem0.ai/core-concepts/memory-operations/search) [Both]: Use when explaining how queries are processed and ranked.
 - [Memory Operations - Update](https://docs.mem0.ai/core-concepts/memory-operations/update) [Both]: Use when memories need to be edited in place or reconciled against new info.
@@ -197,6 +197,7 @@ If the user is on a pre-current major (Python < 2, TS < 3, or a Platform call st
 ### Features - Essential
 - [V2 Memory Filters](https://docs.mem0.ai/platform/features/v2-memory-filters) [Platform]: Use when compound filters (AND/OR on metadata, entity, time) are needed at search.
 - [Entity-Scoped Memory](https://docs.mem0.ai/platform/features/entity-scoped-memory) [Platform]: Use when partitioning memories by user, agent, app, or run.
+- [Profiles](https://docs.mem0.ai/platform/features/user-profiles) [Platform]: Use when a structured always-current summary of a user is needed in one read, instead of searching their memories.
 - [Graph Memory](https://docs.mem0.ai/platform/features/graph-memory) [Platform]: Use when connecting facts across memories through shared entities for entity-centric or multi-hop questions.
 - [Async Client](https://docs.mem0.ai/platform/features/async-client) [Platform]: Use when the app issues many concurrent Mem0 calls and needs non-blocking I/O.
 - [Multimodal Support](https://docs.mem0.ai/platform/features/multimodal-support) [Platform]: Use when storing images or PDFs as memory input.
@@ -255,7 +256,7 @@ If the user is on a pre-current major (Python < 2, TS < 3, or a Platform call st
 - [Agno](https://docs.mem0.ai/integrations/agno) [Platform]: Use when the user is on Agno.
 - [Camel AI](https://docs.mem0.ai/integrations/camel-ai) [Both]: Use when the user is on Camel AI.
 - [ChatDev](https://docs.mem0.ai/integrations/chatdev) [Platform]: Use when the user is on ChatDev.
- [Hermes](https://docs.mem0.ai/integrations/hermes) [Both]: Use when the user is on Hermes.
+- [Hermes](https://docs.mem0.ai/integrations/hermes) [Both]: Use when installing or configuring the standalone Hermes memory plugin, or migrating from the bundled Mem0 provider.
 - [Pi Agent](https://docs.mem0.ai/integrations/pi-agent) [Platform]: Use when adding automatic capture, prompt recall, scoped memory, and six memory commands to Pi Agent.
 - [DeepSeek Harness](https://docs.mem0.ai/integrations/deepseek-plugin) [Platform]: Use when adding automatic recall, completed-turn capture, and native search/add tools to DeepSeek Harness.
 - [OpenAI Agents SDK](https://docs.mem0.ai/integrations/openai-agents-sdk) [Platform]: Use when the user is on the OpenAI Agents SDK.
@@ -269,11 +270,11 @@ If the user is on a pre-current major (Python < 2, TS < 3, or a Platform call st
 ### AI Coding Tools
 - [Claude Code](https://docs.mem0.ai/integrations/claude-code) [Platform]: Use when wiring memory into Claude Code.
 - [Claude.ai](https://docs.mem0.ai/integrations/claude-ai) [Platform]: Use when connecting Mem0 to Claude.ai (the hosted web app) via a custom remote MCP connector, or when Claude's native memory seems to be crowding out mem0 tool calls.
- [Cursor](https://docs.mem0.ai/integrations/cursor) [Platform]: Use when adding lifecycle capture, explicit memory recall, six skills, and a sidekick to Cursor.
+- [Cursor](https://docs.mem0.ai/integrations/cursor) [Platform]: Use when adding lifecycle capture, explicit memory recall, and six memory skills to Cursor.
 - [Codex](https://docs.mem0.ai/integrations/codex) [Platform]: Use when adding automatic capture and recall, six memory skills, and a search tool to OpenAI Codex.
 - [Kimi Code](https://docs.mem0.ai/integrations/kimi) [Platform]: Use when adding persistent project memory to Kimi Code through its native plugin lifecycle.
 - [OpenCode](https://docs.mem0.ai/integrations/opencode) [Platform]: Use when adding ten native SDK memory tools, automatic context, seven skills, and project scoping to OpenCode.
- [Antigravity](https://docs.mem0.ai/integrations/antigravity) [Platform]: Use when adding lifecycle capture, explicit recall, six memory skills, and a native sidekick to Google Antigravity.
+- [Antigravity](https://docs.mem0.ai/integrations/antigravity) [Platform]: Use when adding lifecycle capture, explicit recall, and six memory skills to Google Antigravity.

 ### Voice & Real-time
 - [LiveKit](https://docs.mem0.ai/integrations/livekit) [Platform]: Use when building real-time voice/video with memory.
@@ -325,6 +326,7 @@ If the user is on a pre-current major (Python < 2, TS < 3, or a Platform call st
 - [Healthcare Google ADK](https://docs.mem0.ai/cookbooks/integrations/healthcare-google-adk) [Platform]: Use when the domain is medical and the framework is Google ADK.
 - [AWS Bedrock](https://docs.mem0.ai/cookbooks/integrations/aws-bedrock) [OSS]: Use when deploying with AWS managed model services.
 - [Tavily Search](https://docs.mem0.ai/cookbooks/integrations/tavily-search) [Platform]: Use when the agent layers web search on memory.
+- [Company Brain (Mem0 Platform + Supabase)](https://docs.mem0.ai/cookbooks/integrations/supabase) [Platform]: Use to build a shared org brain on Mem0 Platform with Supabase as system of record and the MCP server as the access layer (with a new-hire onboarding demo).

 ### Framework Examples
 - [LlamaIndex React](https://docs.mem0.ai/cookbooks/frameworks/llamaindex-react) [Both]: Use when building a React UI with LlamaIndex and memory.
@@ -362,6 +364,11 @@ All API Reference docs describe Mem0 Platform REST endpoints (requires API key).
 ### Entities
 - [Get Users](https://docs.mem0.ai/api-reference/entities/get-users) [Platform]: Use when listing users, agents, or apps known to a project.
 - [Delete User](https://docs.mem0.ai/api-reference/entities/delete-user) [Platform]: Use when removing an entity and all its memories.
+- [Get Profile](https://docs.mem0.ai/api-reference/profiles/get-profile) [Platform]: Use when reading a user's structured profile and branching on its generation status.
+- [Get Profile Settings](https://docs.mem0.ai/api-reference/profiles/get-profile-settings) [Platform]: Use when checking the project's profile schema, instructions, or enabled flag.
+- [Update Profile Settings](https://docs.mem0.ai/api-reference/profiles/update-profile-settings) [Platform]: Use when defining or changing the JSON Schema that shapes profiles for a project.
+- [Generate Profiles](https://docs.mem0.ai/api-reference/profiles/generate-profiles) [Platform]: Use when building profiles now: a sample of ten, or one entity.
+- [Get Generation Job](https://docs.mem0.ai/api-reference/profiles/get-profile-job) [Platform]: Use when checking how far a generation has got, and whether it finished.

 ### Organizations
 - [Create Organization](https://docs.mem0.ai/api-reference/organization/create-org) [Platform]: Use when setting up a new org.
@@ -418,13 +425,13 @@ Each subdirectory is a Claude Code Skill (`SKILL.md` + supporting assets). Load

 Source: https://github.com/mem0ai/mem0/tree/main/integrations/claude-code-plugin

-The self-contained Claude Code plugin lives in `integrations/claude-code-plugin/` (v0.3.1, installs as `mem0@mem0-plugins`). It captures evidence locally through lifecycle hooks, extracts memories in a detached background worker, and exposes a single local MCP tool, `search_memories`, plus six `/mem0:*` skills and the unchanged `mem0:sidekick` agent. Pure-stdlib Python, nothing to install.
+The self-contained Claude Code plugin lives in `integrations/claude-code-plugin/` (v0.3.1, installs as `mem0@mem0-plugins`). It captures evidence locally through lifecycle hooks, extracts memories in a detached background worker, and exposes a single local MCP tool, `search_memories`, plus six `/mem0:*` skills and `mem0:sidekick`, available only in Claude Code. Pure-stdlib Python, nothing to install.

 ### Coding-Agent Plugin Sources

 Source: https://github.com/mem0ai/mem0/tree/main/integrations/agent-plugin-core

-The `integrations/agent-plugin-core/` directory is the single source for shared Python and TypeScript memory behavior. Native plugins live in their own sibling directories, while `integrations/mem0-agent-plugin/` is the single portable Agent Plugins v1 package. The portable package provides search and skills but no automatic capture; its remember skill cannot save a new memory on its own. Shared Python search accepts optional `run_id` for session-specific recall in every scope. TypeScript integrations reuse the core's lifecycle, formatting, identity, scoping, and telemetry utilities while keeping their public packages and native host APIs unchanged.
+The `integrations/agent-plugin-core/` directory is the single source for shared Python and TypeScript memory behavior. Native plugins live in their own sibling directories, while `integrations/mem0-agent-plugin/` is the single portable Agent Plugins v1 package. Sidekick is available only in Claude Code. The portable package provides search and skills but no automatic capture; its remember skill cannot save a new memory on its own. Shared Python search accepts optional `run_id` for session-specific recall in every scope. TypeScript integrations reuse the core's lifecycle, formatting, identity, scoping, and telemetry utilities while keeping their public packages and native host APIs unchanged.

 Editor-specific setup docs (already listed above under `## Integrations > AI Coding Tools`):

@@ -1,7 +1,6 @@
 ---
-title: Custom Instructions
-seo:
-  title: "Open Source Custom Instructions - Mem0"
+title: "Open Source Custom Instructions"
+sidebarTitle: "Custom Instructions"
 description: Tailor fact extraction so Mem0 stores only the details you care about.
 icon: "wand-magic-sparkles"
 ---
@@ -1,7 +1,6 @@
 ---
-title: Multimodal Support
-seo:
-  title: "Open Source Multimodal Support - Mem0"
+title: "Open Source Multimodal Support"
+sidebarTitle: "Multimodal Support"
 description: Capture and recall memories from both text and images.
 icon: "image"
 ---
@@ -1,7 +1,6 @@
 ---
-title: "Overview"
-seo:
-  title: "Open Source Features Overview - Mem0"
+title: "Open Source Features Overview"
+sidebarTitle: "Overview"
 description: "Self-hosting features that extend Mem0 beyond basic memory storage"
 icon: "list"
 ---
@@ -56,7 +56,7 @@ The Mem0 REST API server exposes every OSS memory operation over HTTP. Run it al
    make bootstrap    # starts Compose, creates an admin, issues the first API key
    ```

-    Or to start the stack only and finish setup via the browser wizard at http://localhost:3000:
+    Or to start the stack only and finish setup via the browser wizard at `http://localhost:3000`:

    ```bash
    cd server
@@ -1,7 +1,6 @@
 ---
-title: "Overview"
-seo:
-  title: "Mem0 Open Source Overview"
+title: "Open Source Overview"
+sidebarTitle: "Overview"
 description: "Self-host Mem0 with full control over your infrastructure and data"
 icon: "house"
 ---
@@ -8070,6 +8070,480 @@
 					}
 				}
 			}
+		},
+		"/v2/entities/{entity_type}/{entity_id}/profile/": {
+			"get": {
+				"tags": [
+					"profiles"
+				],
+				"operationId": "profiles_read",
+				"summary": "Get an entity's profile",
+				"description": "Return the memory profile for one user.\n\nGeneration is asynchronous, so a known entity that has no profile yet is a normal 200 carrying a `status`. A 404 means only that no such entity exists.",
+				"parameters": [
+					{
+						"name": "entity_type",
+						"in": "path",
+						"required": true,
+						"schema": {
+							"type": "string",
+							"enum": [
+								"user"
+							]
+						},
+						"description": "The kind of entity that carries the profile."
+					},
+					{
+						"name": "entity_id",
+						"in": "path",
+						"required": true,
+						"schema": {
+							"type": "string"
+						},
+						"description": "The entity's id, as supplied when the memory was added."
+					}
+				],
+				"responses": {
+					"200": {
+						"description": "The profile envelope.",
+						"content": {
+							"application/json": {
+								"schema": {
+									"type": "object",
+									"properties": {
+										"profile": {
+											"type": "object",
+											"additionalProperties": true,
+											"description": "The generated profile, shaped by the project's schema. Empty unless status is succeeded."
+										},
+										"status": {
+											"type": "string",
+											"enum": [
+												"succeeded",
+												"pending",
+												"failed",
+												"not_enabled",
+												"insufficient_data"
+											],
+											"description": "Generation state. Branch on this rather than on an empty profile."
+										},
+										"entity_type": {
+											"type": "string",
+											"enum": [
+												"user"
+											]
+										},
+										"entity_id": {
+											"type": "string"
+										},
+										"updated_at": {
+											"type": "string",
+											"format": "date-time",
+											"nullable": true
+										},
+										"generation_count": {
+											"type": "integer"
+										}
+									}
+								}
+							}
+						}
+					},
+					"400": {
+						"description": "Unsupported entity type."
+					},
+					"404": {
+						"description": "No such entity in this project."
+					}
+				}
+			}
+		},
+		"/v2/profiles/settings/": {
+			"get": {
+				"tags": [
+					"profiles"
+				],
+				"operationId": "profiles_settings_read",
+				"summary": "Get profile settings",
+				"description": "Return the profile settings for the project the API key is scoped to.",
+				"responses": {
+					"200": {
+						"description": "Current settings.",
+						"content": {
+							"application/json": {
+								"schema": {
+									"type": "object",
+									"properties": {
+										"enabled": {
+											"type": "boolean",
+											"description": "Whether profile generation runs for this project. Project-wide."
+										},
+										"entities": {
+											"type": "object",
+											"description": "Settings for user profiles, under `user`.",
+											"properties": {
+												"user": {
+													"type": "object",
+													"properties": {
+														"schema": {
+															"type": "object",
+															"additionalProperties": true,
+															"nullable": true,
+															"description": "JSON Schema describing the profile. Every property needs a description."
+														},
+														"custom_instructions": {
+															"type": "string",
+															"nullable": true,
+															"description": "Extra guidance for the extraction step."
+														}
+													}
+												}
+											}
+										},
+										"capabilities": {
+											"type": "object",
+											"properties": {
+												"jobs": {
+													"type": "boolean"
+												},
+												"estimates": {
+													"type": "boolean"
+												},
+												"samples": {
+													"type": "boolean"
+												},
+												"full_rebuild": {
+													"type": "boolean",
+													"description": "Whether a project-wide rebuild (regenerate/backfill) is available. Currently false."
+												}
+											}
+										}
+									}
+								}
+							}
+						}
+					}
+				}
+			},
+			"post": {
+				"tags": [
+					"profiles"
+				],
+				"operationId": "profiles_settings_update",
+				"summary": "Update profile settings",
+				"description": "Update the project's profile settings. Only the fields present in the body are written, so one setting can change without re-sending the others.",
+				"requestBody": {
+					"required": true,
+					"content": {
+						"application/json": {
+							"schema": {
+								"type": "object",
+								"description": "Only the fields present are written. `schema` and `custom_instructions` nest under `entities.user`; a flat body is rejected.",
+								"properties": {
+									"enabled": {
+										"type": "boolean",
+										"description": "Whether profile generation runs for this project. Project-wide."
+									},
+									"entities": {
+										"type": "object",
+										"description": "Settings for user profiles, under `user`.",
+										"properties": {
+											"user": {
+												"type": "object",
+												"properties": {
+													"schema": {
+														"type": "object",
+														"additionalProperties": true,
+														"nullable": true,
+														"description": "JSON Schema describing the profile. Every property needs a description. Send null to clear it."
+													},
+													"custom_instructions": {
+														"type": "string",
+														"nullable": true,
+														"description": "Extra guidance for the extraction step. Send null to clear it."
+													}
+												}
+											}
+										}
+									}
+								}
+							}
+						}
+					}
+				},
+				"responses": {
+					"200": {
+						"description": "Settings as stored after the update.",
+						"content": {
+							"application/json": {
+								"schema": {
+									"type": "object",
+									"properties": {
+										"enabled": {
+											"type": "boolean",
+											"description": "Whether profile generation runs for this project. Project-wide."
+										},
+										"entities": {
+											"type": "object",
+											"description": "Settings for user profiles, under `user`.",
+											"properties": {
+												"user": {
+													"type": "object",
+													"properties": {
+														"schema": {
+															"type": "object",
+															"additionalProperties": true,
+															"nullable": true,
+															"description": "JSON Schema describing the profile. Every property needs a description."
+														},
+														"custom_instructions": {
+															"type": "string",
+															"nullable": true,
+															"description": "Extra guidance for the extraction step."
+														}
+													}
+												}
+											}
+										},
+										"capabilities": {
+											"type": "object",
+											"properties": {
+												"jobs": {
+													"type": "boolean"
+												},
+												"estimates": {
+													"type": "boolean"
+												},
+												"samples": {
+													"type": "boolean"
+												},
+												"full_rebuild": {
+													"type": "boolean",
+													"description": "Whether a project-wide rebuild (regenerate/backfill) is available. Currently false."
+												}
+											}
+										}
+									}
+								}
+							}
+						}
+					},
+					"400": {
+						"description": "The schema is not a valid profile schema."
+					}
+				}
+			}
+		},
+		"/v2/profiles/jobs/": {
+			"post": {
+				"tags": [
+					"profiles"
+				],
+				"operationId": "profiles_create_job",
+				"summary": "Generate profiles",
+				"description": "Start one generation. `operation` says what to build:\n\n- `sample` — up to 10 real entities, so a schema can be judged before it is used widely. These are real profiles: they are saved to those entities and count toward usage.\n- `trigger` — one entity, named by `entity_id`.\n\nSend an `Idempotency-Key` header. Replaying the same key returns the same job instead of charging twice. Poll `status_url` from the response until the status is terminal.",
+				"parameters": [
+					{
+						"in": "header",
+						"name": "Idempotency-Key",
+						"required": true,
+						"schema": {
+							"type": "string",
+							"minLength": 8,
+							"maxLength": 128
+						},
+						"description": "Makes a retry safe: the same key returns the same job."
+					}
+				],
+				"requestBody": {
+					"required": true,
+					"content": {
+						"application/json": {
+							"schema": {
+								"type": "object",
+								"required": [
+									"operation",
+									"entity_type"
+								],
+								"properties": {
+									"operation": {
+										"type": "string",
+										"enum": [
+											"sample",
+											"trigger"
+										],
+										"description": "What to generate. Optional only when `entity_id` is set, which means `trigger`."
+									},
+									"entity_type": {
+										"type": "string",
+										"enum": [
+											"user"
+										]
+									},
+									"entity_id": {
+										"type": "string",
+										"description": "One entity, for `trigger`."
+									},
+									"limit": {
+										"type": "integer",
+										"minimum": 1,
+										"maximum": 10,
+										"description": "How many entities to sample."
+									}
+								}
+							}
+						}
+					}
+				},
+				"responses": {
+					"202": {
+						"description": "Job accepted.",
+						"content": {
+							"application/json": {
+								"schema": {
+									"type": "object",
+									"properties": {
+										"job_id": {
+											"type": "string"
+										},
+										"status": {
+											"type": "string"
+										},
+										"status_url": {
+											"type": "string",
+											"description": "Poll this. Building the path yourself breaks on a route change."
+										},
+										"operation": {
+											"type": "string"
+										},
+										"entity_type": {
+											"type": "string"
+										},
+										"entity_count_reserved": {
+											"type": "integer",
+											"description": "Entities reserved against usage for this job."
+										},
+										"event_id": {
+											"type": "string",
+											"nullable": true
+										},
+										"replayed": {
+											"type": "boolean",
+											"description": "True when an Idempotency-Key returned an existing job."
+										},
+										"sampled": {
+											"type": "integer",
+											"description": "`sample` only."
+										},
+										"entity_ids": {
+											"type": "array",
+											"items": {
+												"type": "string"
+											},
+											"description": "`sample` only: the entity ids picked. Read each with `GET /v2/entities/user/{entity_id}/profile/`."
+										}
+									}
+								}
+							}
+						}
+					},
+					"400": {
+						"description": "Unknown or missing `operation`, or profiles are not configured."
+					},
+					"402": {
+						"description": "Payment required."
+					},
+					"409": {
+						"description": "A job is already running, or the Idempotency-Key was used for a different request. Branch on `error.code`."
+					},
+					"429": {
+						"description": "Cooldown. `retry_after_seconds` sits inside `error`."
+					},
+					"503": {
+						"description": "`jobs_unavailable` — generation is switched off for this project."
+					}
+				}
+			}
+		},
+		"/v2/profiles/jobs/{job_id}/": {
+			"get": {
+				"tags": [
+					"profiles"
+				],
+				"operationId": "profiles_get_job",
+				"summary": "Read a generation job",
+				"description": "The job nests under `job`. `total` is null until `enumeration_complete`, and `completed` is `succeeded + failed + skipped`.",
+				"parameters": [
+					{
+						"in": "path",
+						"name": "job_id",
+						"required": true,
+						"schema": {
+							"type": "string"
+						}
+					}
+				],
+				"responses": {
+					"200": {
+						"description": "The job.",
+						"content": {
+							"application/json": {
+								"schema": {
+									"type": "object",
+									"properties": {
+										"job": {
+											"type": "object",
+											"properties": {
+												"id": {
+													"type": "string"
+												},
+												"operation": {
+													"type": "string"
+												},
+												"entity_type": {
+													"type": "string"
+												},
+												"status": {
+													"type": "string",
+													"enum": [
+														"QUEUED",
+														"RUNNING",
+														"SUCCEEDED",
+														"PARTIALLY_SUCCEEDED",
+														"FAILED",
+														"CANCELLED"
+													]
+												},
+												"total": {
+													"type": "integer",
+													"nullable": true
+												},
+												"enumeration_complete": {
+													"type": "boolean"
+												},
+												"completed": {
+													"type": "integer"
+												},
+												"succeeded": {
+													"type": "integer"
+												},
+												"failed": {
+													"type": "integer"
+												},
+												"skipped": {
+													"type": "integer"
+												}
+											}
+										}
+									}
+								}
+							}
+						}
+					},
+					"404": {
+						"description": "No such job in this project."
+					}
+				}
+			}
 		}
 	},
 	"components": {
@@ -8988,4 +9462,4 @@
 		}
 	},
 	"x-original-swagger-version": "2.0"
-}
+}
@@ -1,7 +1,6 @@
 ---
-title: CLI
-seo:
-  title: "Mem0 CLI for Terminal Memory Management"
+title: "CLI for Terminal Memory Management"
+sidebarTitle: "CLI"
 description: "Manage memories from your terminal, for both humans and AI agents."
 icon: "terminal"
 iconType: "solid"
@@ -0,0 +1,194 @@
+---
+title: "Mem0 Copilot"
+description: "Inspect project memories, review configuration changes, and test extraction from the Mem0 dashboard."
+icon: "message"
+---
+
+Copilot is an AI assistant in the [Mem0 dashboard](https://app.mem0.ai/dashboard/copilot). Ask it to inspect stored memories, suggest extraction rules and categories, change project settings, or explain the platform SDKs and APIs.
+
+You describe the task in chat. Copilot uses tools to read project data or propose changes. In **Review changes** mode, you approve each change before it runs.
+
+## Start with your project
+
+1. Sign in to the dashboard and select the organization and project you want to work on.
+2. Open **Copilot** in the sidebar.
+3. Select **Review changes** below the message box.
+4. Ask: “Show my current project settings and explain what each one does.”
+5. Expand an activity card, such as **Read project config**, to see its **Input** and **Result**. Check these results when reviewing an answer or confirming a change.
+
+You can ask about settings or SDK usage with an empty project. Suggestions based on stored data need enough project history to analyze.
+
+## Inspect stored memories
+
+Start with a project overview, then narrow the question:
+
+| Prompt | What to inspect |
+| --- | --- |
+| “Summarize what this project has stored and how it is categorized.” | The memories and category patterns Copilot reads. Check which records support its summary. |
+| “Analyze the memories for user alice.” | Facts stored for `alice`, their categories, and unwanted information. To investigate a missing fact, also provide the original input. |
+| “Search alice's memories for dietary preferences.” | Memories relevant to the query within that user's scope. |
+
+Copilot can list memories across the project. Searching by meaning needs a specific User, Agent, App, or Run ID. Select one in **Scope** or name it in your prompt.
+
+Memory lists are paginated, and suggestions use samples. Check the activity results to see which records were read. Ask for more pages when you need to inspect the rest.
+
+### Choose the memory scope
+
+Open **Scope** below the message box. Select an existing ID or type one and choose it.
+
+| Control | Identifies |
+| --- | --- |
+| **User** | The end user whose memories you want to inspect, such as `alice`. |
+| **Agent** | An AI agent associated with the memories. |
+| **App** | An application associated with the memories. |
+| **Run** | A particular execution or session associated with the memories. |
+
+A field set to **any** adds no filter for that entity type. **Clear scope** removes the selections. Scope gives Copilot default IDs to use; you can request a different entity in a message. Check the activity's **Input** to confirm which IDs it used. Adding a test memory requires a **User** ID, even when another entity is selected.
+
+<Note>
+  Scope selects memories, not separate settings. Categories, extraction instructions, memory depth, and multilingual settings apply to the selected project. Category and extraction suggestions also analyze project data, regardless of the selected entity.
+</Note>
+
+See [Entity-scoped memory](/platform/features/entity-scoped-memory) for how these IDs organize memories in your application.
+
+## Review and apply changes
+
+The mode control below the message box determines when changes run:
+
+- **Review changes**: Copilot pauses before changing project configuration or adding a test memory. Read the proposal and choose whether to apply it.
+- **Auto-apply**: Copilot can change settings and add test memories without asking for approval. Check the selected project and scope before using it.
+
+Ask Copilot to show the current settings before requesting an update. In the approval card, review every listed field. Approving the card applies the whole proposal, including fields you did not edit.
+
+| Action | Effect |
+| --- | --- |
+| **Apply change** | Approve the proposed write. Inspect the subsequent result to confirm it succeeded. |
+| **Edit** | When offered, edit extraction instructions or category names and descriptions. Choose **Apply with edits** to submit your revision. |
+| **Discard edits** | Return to the original proposal without applying it. |
+| **Decline** | Reject this proposal without applying it. |
+| **Ask for something else** | Enter feedback and choose **Send**. This declines the current proposal and sends your feedback as a new message. Review the next proposal before applying it. |
+
+Not every field has an inline editor. If a proposal includes both extraction instructions and categories, only the instructions get an editor. The editor cannot apply blank instructions or an empty category list. Use **Ask for something else** to change other fields or request separate proposals.
+
+<Warning>
+  A generated prompt profile contains separate prompts for extraction and summaries. If your project uses one, saving extraction instructions through Copilot deactivates it. Review the replacement rules and test the affected behavior before using them in production.
+</Warning>
+
+## What Copilot cannot do
+
+Copilot cannot perform these actions, even in **Auto-apply** mode:
+
+- Create or delete API keys.
+- Directly edit or delete existing memories.
+- Export project data.
+- Invite or remove organization or project members, or change their roles and permissions.
+- Create or delete organizations or projects.
+- Change billing details or subscription plans.
+
+Use the dashboard or the relevant platform API for these tasks. Copilot can explain the steps or point you to documentation, but it cannot carry out the actions.
+
+Copilot supports the managed Mem0 platform. It does not help configure or use the [self-hosted open-source library](/open-source/overview).
+
+## Example 1: Stop storing small talk, then test extraction
+
+This walkthrough uses a project where you have noticed greetings or small talk in stored memories. Use a development project when trying configuration changes, since a test user does not isolate project settings.
+
+<Steps>
+  <Step title="Inspect the problem">
+    Select the project, set **User** to `alice`, and ask:
+
+    > Analyze the memories for user alice.
+
+    Inspect the returned memories. Identify examples of small talk you want to exclude and useful facts you still want to keep.
+  </Step>
+  <Step title="Request a targeted change">
+    With **Review changes** selected, ask:
+
+    > Update my extraction instructions to ignore greetings and small talk. Keep the existing rules for durable user preferences.
+
+    Check for a **Read project config** activity before reviewing the update. If it is missing, ask Copilot to read the current instructions first. If analysis reports insufficient data, ask it to use the rule you provided. You can also set the rule directly through [Custom instructions](/platform/features/custom-instructions).
+  </Step>
+  <Step title="Review the proposal">
+    Review the full replacement text. Keep existing rules your application needs. For this test, the relevant rules could look like:
+
+    ```text
+    Remember the following:
+
+    * The user's dietary preferences and food restrictions.
+
+    Don't remember the following:
+
+    * Greetings and small talk.
+    ```
+
+    Use **Edit** to adjust the wording, or **Ask for something else** to request a revision.
+
+    Choose **Apply change** or **Apply with edits**, then inspect the result to confirm the instructions were saved.
+  </Step>
+  <Step title="Add a test conversation">
+    Choose a new **User** ID for this test, such as `copilot-extraction-test-01`, and clear any other entity selections. Ask:
+
+    > Add this as a user message for copilot-extraction-test-01: “Hi! How's your day? I prefer vegetarian meals and avoid peanuts.”
+
+    Review the test-memory proposal and choose **Apply change**.
+
+    <Warning>
+      Adding a test memory writes to the selected project. It is not a dry run. Use a dedicated test user so you can find and remove the test data afterward.
+    </Warning>
+  </Step>
+  <Step title="Wait for extraction, then check the result">
+    Expand **Add test memory** and inspect **Result**. A `PENDING` status means extraction is still running. Use the returned `event_id` with the [Get Event API](/api-reference/events/get-event) to check progress. Wait for `SUCCEEDED` before evaluating the output. If the event is `FAILED`, inspect its details before retrying.
+
+    Then ask:
+
+    > List all memories for user copilot-extraction-test-01. Then search that user's memories for dietary preferences.
+
+    Check that the memories retain the vegetarian preference and peanut restriction, and exclude the greeting. Inspect the full list as well as search results: a relevant search can hide unwanted small-talk records.
+
+    If the output is wrong, describe the mismatch and review another instruction change. Use a new test user for the next attempt so earlier memories do not affect the result. Remove test data afterward through the dashboard or [memory deletion API](/api-reference/memory/delete-memories).
+  </Step>
+</Steps>
+
+Test with new inputs after changing settings. Updating configuration is not a cleanup operation for existing memories. See [Custom instructions](/platform/features/custom-instructions) for guidance on writing extraction rules.
+
+## Example 2: Suggest categories and extraction instructions
+
+These workflows sample the selected project's data. Generating a suggestion does not update settings by itself. Copilot can then propose applying it, which follows the selected review mode. Use **Review changes** to inspect suggestions before they are saved.
+
+| Workflow | Data used | Example prompt |
+| --- | --- | --- |
+| Custom categories | Stored memories, excluding deleted memories. | “Suggest custom categories from this project's memories.” |
+| Extraction instructions | Successful requests to add conversation data, including requests that produced no memories. | “Compare recent add requests with the extracted memories and suggest better extraction instructions.” |
+
+Category suggestions identify recurring themes. Review the names, descriptions, and examples. Applying a category list replaces the project's previous list; it does not add to it or re-tag existing memories. See [Custom categories](/platform/features/custom-categories) for project and per-call behavior.
+
+Extraction suggestions compare conversation inputs with what was extracted. One add request can produce several memories or none, so the number of add requests is different from the number of stored memories. Keep your application's existing requirements when reviewing the proposal.
+
+Both workflows require enough project data. If a suggestion fails because there is too little data, check the activity's **Result** for the current and required counts. You can still inspect memories, ask SDK/API questions, or provide your own rules instead of requesting a data-based suggestion.
+
+## Example 3: Adjust detail and language
+
+Ask Copilot to read the current settings, then request the change you need:
+
+- **Memory depth** controls the level of detail: **Less**, **Medium**, or **More detailed**. Try “Show my current memory depth, then propose More detailed memories.” For deciding *which facts* to retain, use extraction instructions.
+- **Multilingual** behavior preserves the user's original language. Try “Enable multilingual behavior so memories preserve the language of the input.” Test it with a new conversation in the language your application uses.
+
+Both are project settings. Review the proposed values and test a fresh input after applying them. See [Organization and project settings](/api-reference/organizations-projects) for configuration through the API.
+
+## Example 4: Ask SDK and API questions
+
+Include your language and the task, for example:
+
+> Show me how to search memories for user alice with the managed Mem0 Python SDK. Link the documentation you used.
+
+Copilot can look up the official platform documentation. Check the **Browse mem0 docs** and **Read docs page** activities and open the cited pages. If an answer has no sources, ask for them before using the example. The [Platform quickstart](/platform/quickstart) covers adding and searching memories in code.
+
+## Resume a conversation and check message limits
+
+Use **History** to reopen your 50 most recently active chats for the selected project. Chats belong to the person who created them; other project members cannot open them. Use **New chat** to start a separate conversation, or **Delete chat** in history to remove one. Deleting a chat does not undo settings changes or remove test memories.
+
+Message allowances depend on the organization's plan and are shared across its projects and members. They reset at the start of each calendar month in UTC.
+
+For plans with a limit, a usage notice appears once 80% of the allowance is used. Below that point, no counter is shown. At the limit, new messages are disabled until the allowance resets or the plan is upgraded. Follow the notice's upgrade link to review plan options.
+
+Sending feedback through **Ask for something else** counts as a new message. Approving or declining a saved proposal without feedback does not use another message. Test additions and searches also use the platform APIs and remain subject to their normal quotas.
@@ -1,7 +1,6 @@
 ---
-title: Custom Instructions
-seo:
-  title: "Platform Custom Instructions - Mem0"
+title: "Platform Custom Instructions"
+sidebarTitle: "Custom Instructions"
 description: 'Control how Mem0 extracts and stores memories using natural language guidelines'
 ---

@@ -1,7 +1,6 @@
 ---
-title: Multimodal Support
-seo:
-  title: "Platform Multimodal Support - Mem0"
+title: "Platform Multimodal Support"
+sidebarTitle: "Multimodal Support"
 description: Integrate images and documents into your interactions with Mem0
 ---

@@ -0,0 +1,359 @@
+---
+title: Profiles
+description: "Build a structured, always-current summary of each user from their memories, shaped by a JSON Schema you define."
+---
+
+# Profiles
+
+Memories are individual facts. A profile is the summary of all of them for one entity: a single structured object, shaped by a JSON Schema you define, that Mem0 keeps current as new memories arrive.
+
+Search answers "what did this user say about X". A profile answers "who is this user", in one read, with no query to write.
+
+<Info>
+  **Use profiles when…**
+  - You want to personalize a first response, before the user says anything in this session.
+  - You need a compact object to drop into a prompt instead of a list of memories.
+  - You want the same fields for every user, so your code can rely on their shape.
+</Info>
+
+<Note>
+  User Profiles are in **beta** and available on request. To enable them for your
+  organization, contact [support@mem0.ai](mailto:support@mem0.ai).
+</Note>
+
+## How it works
+
+1. You define a **schema**: the fields a profile should contain, each with a description.
+2. Mem0 builds each entity's profile from their memories, and rebuilds it as new memories arrive.
+3. You read the profile whenever you need it.
+
+Generation is **asynchronous**. A profile is not ready the instant an entity's first memory lands, so a read tells you where it is with a `status` rather than failing.
+
+## Define the schema
+
+The schema is JSON Schema. Every property needs a `description` — that is what tells the model how to fill the field, so a vague description gives a vague profile.
+
+<CodeGroup>
+```python Python
+from mem0 import MemoryClient
+
+client = MemoryClient()
+
+client.update_profile_settings(
+    enabled=True,
+    schema={
+        "type": "object",
+        "properties": {
+            "communication_style": {
+                "type": "string",
+                "description": "How the user prefers to be addressed: terse, detailed, formal, casual",
+            },
+            "expertise_areas": {
+                "type": "array",
+                "items": {"type": "string"},
+                "description": "Subjects the user demonstrates working knowledge of",
+            },
+            "current_goals": {
+                "type": "array",
+                "items": {"type": "string"},
+                "description": "What the user is actively trying to accomplish",
+            },
+        },
+    },
+    custom_instructions="Prefer durable traits over one-off remarks.",
+)
+```
+
+```typescript TypeScript
+import MemoryClient from "mem0ai";
+
+const client = new MemoryClient({ apiKey: "your-api-key" });
+
+await client.updateProfileSettings({
+  enabled: true,
+  schema: {
+    type: "object",
+    properties: {
+      communication_style: {
+        type: "string",
+        description:
+          "How the user prefers to be addressed: terse, detailed, formal, casual",
+      },
+      expertise_areas: {
+        type: "array",
+        items: { type: "string" },
+        description: "Subjects the user demonstrates working knowledge of",
+      },
+      current_goals: {
+        type: "array",
+        items: { type: "string" },
+        description: "What the user is actively trying to accomplish",
+      },
+    },
+  },
+  customInstructions: "Prefer durable traits over one-off remarks.",
+});
+```
+</CodeGroup>
+
+<Note>
+  Your schema's property names reach the API exactly as you write them. The SDKs do not rewrite them, so a profile always comes back with the field names you chose.
+</Note>
+
+Only the fields you pass are written. To turn the feature off without touching your schema, send `enabled` alone.
+
+## Read a profile
+
+<CodeGroup>
+```python Python
+result = client.get_profile("alice")
+
+if result["status"] == "succeeded":
+    print(result["profile"])
+else:
+    print("not ready:", result["status"])
+```
+
+```typescript TypeScript
+const result = await client.getProfile({ entityId: "alice" });
+
+if (result.status === "succeeded") {
+  console.log(result.profile);
+} else {
+  console.log("not ready:", result.status);
+}
+```
+</CodeGroup>
+
+A response looks like this:
+
+```json
+{
+  "profile": {
+    "communication_style": "terse",
+    "expertise_areas": ["distributed systems", "postgres"],
+    "current_goals": ["cut p99 latency", "migrate off the legacy queue"]
+  },
+  "status": "succeeded",
+  "entity_type": "user",
+  "entity_id": "alice",
+  "updated_at": "2026-02-08T10:30:00Z",
+  "generation_count": 3
+}
+```
+
+`generation_count` is how many times this profile has been (re)generated — `0` before the first generation completes.
+
+### Always branch on `status`
+
+`profile` is empty unless `status` is `succeeded`. Check the status rather than the emptiness of the object, so a profile that is merely still building is not mistaken for a user you know nothing about.
+
+| `status` | Meaning | What to do |
+|---|---|---|
+| `succeeded` | Profile is built and current | Use it |
+| `pending` | Generation is queued or running | Read again shortly |
+| `insufficient_data` | Not enough memories to say anything yet | Fall back to defaults |
+| `not_enabled` | Profiles are off for this project | Enable them in settings |
+| `failed` | The last generation did not complete | Retry, or trigger a new one |
+
+A `404` means only that no such entity exists in your project.
+
+## Generate a profile on demand
+
+Profiles are built once an entity has accumulated enough messages, so a brand-new user has none during their first few interactions. Trigger one directly to close that gap:
+
+<CodeGroup>
+```python Python
+client.generate_profile("alice")
+```
+
+```typescript TypeScript
+await client.generateProfile({ entityId: "alice" });
+```
+</CodeGroup>
+
+The call returns as soon as the work is queued. Poll the read endpoint and branch on `status`.
+
+## Test a schema before applying it
+
+A schema that reads well can still produce disappointing profiles. Sample a few real entities and inspect the output before committing to it.
+
+Sampling is asynchronous: the call returns a job as soon as it is queued. Poll `status_url` until the job is terminal, then read each sampled entity's profile:
+
+<CodeGroup>
+```python Python
+import time
+
+job = client.sample_profiles(limit=5)
+
+# Poll until the sample job reaches a terminal state (job status is UPPERCASE).
+TERMINAL = {"SUCCEEDED", "PARTIALLY_SUCCEEDED", "FAILED", "CANCELLED"}
+deadline = time.time() + 120
+while True:
+    status = client.get_profile_job(job["status_url"])["job"]
+    if status["status"] in TERMINAL:
+        break
+    if time.time() > deadline:
+        raise TimeoutError("Sample job did not finish in time")
+    time.sleep(3)
+
+print(status["status"], status["succeeded"], "of", status["total"])
+
+# The create response lists the sampled entities; read each one's saved profile.
+for entity_id in job.get("entity_ids", []):
+    print(client.get_profile(entity_id))
+```
+
+```typescript TypeScript
+const job = await client.sampleProfiles({ limit: 5 });
+
+// Poll until the sample job reaches a terminal state (job status is UPPERCASE).
+const TERMINAL = ["SUCCEEDED", "PARTIALLY_SUCCEEDED", "FAILED", "CANCELLED"];
+const deadline = Date.now() + 120_000;
+let status;
+while (true) {
+  status = (await client.getProfileJob(job.statusUrl)).job;
+  if (TERMINAL.includes(status.status)) break;
+  if (Date.now() > deadline)
+    throw new Error("Sample job did not finish in time");
+  await new Promise((resolve) => setTimeout(resolve, 3000));
+}
+
+console.log(status.status, status.succeeded, "of", status.total);
+
+// The create response lists the sampled entities; read each one's saved profile.
+for (const entityId of job.entityIds ?? []) {
+  console.log(await client.getProfile({ entityId }));
+}
+```
+</CodeGroup>
+
+These are real generations. The profiles are saved to those entities and count toward your usage, so sampling is not wasted work and not a free dry run. A sample covers up to 10 entities and cannot be repeated immediately.
+
+## Apply a new schema to existing entities
+
+A new schema shapes the next generation. Profiles that already exist keep their values until their entity is generated again.
+
+Each entity picks the new schema up as it sends more memories, and you can generate one now with `generate_profile`.
+
+<Note>
+Rebuilding every profile in a project at once is not available yet. Refresh profiles one entity at a time with `generate_profile`, or let each one update on its own as its entity sends more memories.
+</Note>
+
+## When profiles update
+
+You never call an "update profile" endpoint — Mem0 keeps each profile current for you. Two things drive it:
+
+- **Automatically, as memories accumulate.** Mem0 refreshes an entity's profile after roughly every **10 messages** it receives, folding the new memories into the existing profile. There is no schedule to wait for and no extra call to make: the same `add` you already do keeps the profile moving.
+- **On demand.** Call `generate_profile` to build or refresh a profile immediately — useful for a brand-new entity that has not yet crossed the automatic threshold.
+
+Generation is **asynchronous and incremental**. A refresh runs in the background a short while after its trigger, so a read taken immediately after an `add` may still show the previous profile (or `pending`). Branch on `status` rather than assuming the latest memory is already reflected.
+
+<Note>
+  Updates are **incremental**, not a full rebuild each time — Mem0 merges what it newly learns into the stored profile and keeps the fields your schema still defines. After a schema change, existing profiles pick it up as their entities send more memories, or when you call `generate_profile` — see [Apply a new schema to existing entities](#apply-a-new-schema-to-existing-entities).
+</Note>
+
+## Use a profile in a prompt
+
+The point of the structure is that it drops straight into a prompt:
+
+```python
+result = client.get_profile(user_id)
+
+if result["status"] == "succeeded":
+    profile = result["profile"]
+    system_prompt = f"""You are helping {user_id}.
+Communication style: {profile.get("communication_style", "unknown")}
+Areas of expertise: {", ".join(profile.get("expertise_areas", []))}
+Current goals: {", ".join(profile.get("current_goals", []))}
+
+Match their style and do not explain what they already know."""
+else:
+    system_prompt = "You are a helpful assistant."
+```
+
+## Writing a schema that works
+
+- **Describe every field.** The description is the instruction; without it the model guesses.
+- **Prefer durable traits.** "Prefers dark mode" ages well; "is annoyed today" does not.
+- **Keep it small.** Ten focused fields beat forty speculative ones, and cost less to generate.
+- **Say what the field is not.** A description that rules out the near-miss interpretation is worth more than one that only states the obvious.
+- **Sample before you commit.** It is the only way to see what your descriptions actually produce.
+
+<Note>
+  A schema has a size budget of roughly **10,000 tokens** of serialized JSON — the whole schema is sent to the model on every generation, so a handful of verbose fields can cost more than many terse ones. Oversized schemas are rejected on save.
+</Note>
+
+## Availability
+
+The feature is in beta and enabled per organization on request — see the note at the top of this page.
+
+Once it is on, an entity gets a profile when two more things hold:
+
+- profiles are **enabled** with a schema for the project (see [Define the schema](#define-the-schema)), and
+- the memory is scoped to an entity — a `user_id`.
+
+On a project where profiles are turned off, a read returns `status: not_enabled` rather than an error, so you can call it unconditionally and branch on the status.
+
+## Settings reference
+
+| Argument | Type | Description |
+|---|---|---|
+| `enabled` | boolean | Whether profile generation runs for the project |
+| `schema` | object | JSON Schema describing the profile. Every property needs a `description` |
+| `custom_instructions` | string | Extra guidance applied during extraction |
+
+`enabled` is project-wide. `schema` and `custom_instructions` apply to user
+profiles, so the stored settings nest them under `entities`:
+
+```json
+{
+  "enabled": true,
+  "entities": {
+    "user": {
+      "schema": { "type": "object", "properties": { "...": {} } },
+      "custom_instructions": "Prefer durable traits over one-off remarks."
+    }
+  },
+  "capabilities": { "full_rebuild": false }
+}
+```
+
+That is what a read returns and what a write accepts. The SDKs take the fields
+flat and nest them for you, so a schema you write with
+`update_profile_settings` comes back unchanged from `get_profile_settings`.
+
+<Note>
+  Profile settings are per project. An API key is scoped to one project, so profiles never cross a project boundary.
+</Note>
+
+## FAQ
+
+**Do I need to change my `add` or `search` calls to use profiles?**
+No. Profiles are built from the memories you already add. You define a schema once and read the profile when you need it — your ingestion and retrieval code is unchanged.
+
+**Why is `profile` empty even though the entity has memories?**
+Generation is asynchronous and needs enough to work with. Branch on `status`: `pending` means it is still building, and `insufficient_data` means there are not yet enough memories to fill the schema. Read again shortly, or call `generate_profile` to build one now.
+
+**Is sampling free?**
+No. `sample_profiles` runs real generations against real memories and **keeps** the profiles it produces, so it counts toward your usage like any other generation. It exists to check a schema on a few entities before you commit to it — not as a zero-cost dry run.
+
+**Does changing the schema rewrite existing profiles?**
+No. A schema change applies to the next generation. An existing profile keeps its values until its entity is generated again, which happens as that entity sends more memories, or when you call `generate_profile` for it.
+
+**What happens to a field I remove from the schema?**
+It stops being maintained. On an entity's next generation, fields your schema no longer defines are pruned from the stored profile — so keep a field in the schema for as long as you want its value kept.
+
+**How current is a profile?**
+It refreshes automatically as memories accumulate (about every 10 messages for an entity), plus any on-demand `generate_profile` calls. Because refreshes run in the background, expect a short delay after the triggering `add` rather than an instant update.
+
+## Related
+
+<CardGroup cols={2}>
+  <Card title="Entity-Scoped Memory" icon="users" href="/platform/features/entity-scoped-memory">
+    How users, agents, apps and runs partition memories.
+  </Card>
+  <Card title="Custom Instructions" icon="pen" href="/platform/features/custom-instructions">
+    Steer what Mem0 extracts in the first place.
+  </Card>
+</CardGroup>
@@ -1,7 +1,6 @@
 ---
-title: "Overview"
-seo:
-  title: "Mem0 Platform Overview"
+title: "Platform Overview"
+sidebarTitle: "Overview"
 description: "Managed memory layer for AI agents, production-ready in minutes"
 icon: "cloud"
 ---
@@ -51,8 +50,8 @@ For the full pipeline, see [How Mem0 works](/core-concepts/how-it-works).
  <Card title="Run the quickstart" icon="rocket" href="/platform/quickstart">
    Get an API key and save your first memory.
  </Card>
-  <Card title="Understand memory types" icon="brain" href="/core-concepts/memory-types">
-    How user, agent, app, and run memory differ.
+  <Card title="Scope your memories" icon="brain" href="/platform/features/entity-scoped-memory">
+    Organize memories by user, agent, app, and run.
  </Card>
  <Card title="Add, search, and update" icon="layer-group" href="/core-concepts/memory-operations/add">
    The core memory operations, end to end.
@@ -39,7 +39,7 @@ The core memory loop is identical on both: `add`, `search`, `get`, `get_all`, `u
 - **Entity scoping** by `user_id`, `agent_id`, and `run_id`
 - **Filter grouping**: both accept `AND`/`OR`/`NOT` wrappers, both implicitly AND a flat multi-key filter like `{"user_id": "alice", "agent_id": "a1"}`, and both accept `*` as a wildcard value. Which fields you may filter on, and which operators each field accepts, differ (see below)
 - **Entity-aware ranking**: both extract entities from memory text and use shared entities to boost related results at search time
- **Multimodal input**, **memory expiration** (`expiration_date`), **reranking**, **procedural memory** (Python), and **custom extraction instructions** (`custom_instructions`)
+- **Multimodal input**, **memory expiration** (`expiration_date`), **reranking**, and **custom extraction instructions** (`custom_instructions`)
 - Python and JavaScript SDKs, plus a REST API (self-hosted via `server/`, or hosted)

 ## What's actually different
@@ -4,7 +4,7 @@ description: "Standard layout for documenting Mem0 API endpoints."
 icon: "code"
 ---

-# Api Reference Template
+# API Reference Template

 API reference pages document a single endpoint contract. Present metadata, request/response examples, and recovery guidance without narrative detours.

@@ -124,7 +124,7 @@ Walk through a real request/response. Include sample payloads and highlight nota
 {/* DEBUG: verify CTA targets */}

 <CardGroup cols={2}>
-  <Card title="Dive Into Memory Scoring" icon="scale-balanced" href="/core-concepts/memory-types">
+  <Card title="Dive Into Memory Scoring" icon="scale-balanced" href="/core-concepts/how-it-works">
    Understand how Mem0 ranks memories under the hood.
  </Card>
  <Card title="Build a Research Copilot" icon="book-open" href="/cookbooks/operations/deep-research">
@@ -38,7 +38,6 @@ client.memories.add(
    user_id: str,
    memory: str,
    metadata: Optional[dict] = None,
-    memory_type: Literal["session", "long_term"] = "session",
 )
 ```

@@ -47,13 +46,13 @@ await mem0.memories.add({
  userId: string;
  memory: string;
  metadata?: Record<string, string>;
-  memoryType?: "session" | "long_term";
 });
 ```
 </CodeGroup>

 <Info>
-  Defaults to session memories. Override `memory_type` for long-term storage.
+  [Describe defaults supported by this operation and SDK. Do not infer a
+  memory type or retention policy from a scoping identifier.]
 </Info>

 <Warning>
@@ -67,7 +66,6 @@ await mem0.memories.add({
 | `user_id` | string | Yes | Unique identifier for the end user. | Must match follow-up operations. |
 | `memory` | string | Yes | Content to persist. | Managed & OSS. Markdown allowed. |
 | `metadata` | object | No | Key-value pairs for filters. | OSS stores as JSONB; limit to 2KB. |
-| `memory_type` | string | No | Retention bucket | Platform supports `shared`. |

 <Tip>
  Set `ttl_seconds` when you need memories to expire automatically (OSS only).
@@ -96,8 +96,8 @@ time. Storage: vector embeddings.
 **Architecture Overview:**
 - Memory is scoped by user_id, agent_id, or run_id
 - Core operations: add, search, update, delete
- Memory types: factual (preferences, facts), episodic (past interactions),
-  semantic (concept relationships), working (session state)
+- Store preferences, facts, and past interactions; use run_id to scope a
+  session. Platform does not expose a memory_type selector.
 - Integration pattern: retrieve relevant memories → generate response → store
  new memories

@@ -28,7 +28,7 @@
    "clsx": "^2.1.1",
    "js-cookie": "^3.0.6",
    "lucide-react": "^0.477.0",
-    "next": "15.5.21",
+    "next": "15.5.24",
    "react": "^19.0.0",
    "react-dom": "^19.0.0",
    "react-markdown": "^10.0.1",
@@ -45,11 +45,11 @@ grok_client = OpenAI(

 def recommend_movie_with_memory(user_id: str, user_query: str):
    # Retrieve prior memory about movies
-    past_memories = memory.search("movie preferences", user_id=user_id)
+    past_memories = memory.search("movie preferences", filters={"user_id": user_id})

    prompt = user_query
-    if past_memories:
-        prompt += f"\nPreviously, the user mentioned: {past_memories}"
+    if past_memories["results"]:
+        prompt += f"\nPreviously, the user mentioned: {[m['memory'] for m in past_memories['results']]}"

    # Generate movie recommendation using Grok 3
    response = grok_client.chat.completions.create(model="grok-3-beta", messages=[{"role": "user", "content": prompt}])
@@ -198,7 +198,7 @@ def search_memory_tool(query: str, user_id: str = "user") -> str:
        Relevant vector memories found or message if none found
    """
    try:
-        results = m.search(query, user_id=user_id)
+        results = m.search(query, filters={"user_id": user_id})

        if isinstance(results, dict) and 'results' in results:
            memory_list = results['results']
@@ -245,7 +245,7 @@ def search_graph_memory_tool(query: str, user_id: str = "user") -> str:
    """
    try:
        graph_query = f"relationships connections {query}"
-        results = m.search(graph_query, user_id=user_id)
+        results = m.search(graph_query, filters={"user_id": user_id})

        if isinstance(results, dict) and 'results' in results:
            memory_list = results['results']
@@ -290,7 +290,7 @@ def get_all_memories_tool(user_id: str = "user") -> str:
        All memories for the user or message if none found
    """
    try:
-        all_memories = m.get_all(user_id=user_id)
+        all_memories = m.get_all(filters={"user_id": user_id})

        if isinstance(all_memories, dict) and 'results' in all_memories:
            memory_list = all_memories['results']
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
kartik-mem0	9a5497469d	test(plugins): a removed plugin setting gives way to a later mem0 init key	2026-09-25 11:54:58 +05:30
kartik-mem0	12617b6d8d	test(plugins): assert the generated DATA_DIR_NAME in the build tests	2026-09-25 11:20:52 +05:30
kartik-mem0	cbfb37c623	fix(plugins): give the MCP server the hooks' data dir, release 0.3.4 mcp_server.py never calls configure_harness, so it resolved ~/.mem0/mem0-plugin while the Cursor, Kimi and Antigravity hooks use ~/.mem0/<host>-plugin. A key set in Cursor's plugin settings and cached by the sessionStart hook was invisible to search_memories. build.py now writes DATA_DIR_NAME into each bundle's _harness_id.py and memory_core seeds its default from it, like the PLATFORM_* values. An end-to-end test launches the real session-start hook and MCP server for Claude Code, Cursor and Codex the way each host does, with the key in plugin settings and in the mem0 init config, and checks the search reaches the API with that key. Bumps the Python plugins to 0.3.4, OpenCode to 0.4.2, Pi and DeepSeek to 0.3.3, with changelog entries for each. Fixes #7346	2026-09-25 11:11:37 +05:30
kartik-mem0	71dc0cae07	fix(plugins): read the mem0 CLI key and ignore unexpanded host placeholders The Python plugin core and the opencode, pi and deepseek plugins now fall back to the key `mem0 init` saves in ~/.mem0/config.json, so a configured CLI is enough to authenticate. The Python core also stops using or caching a literal ${api_key} left behind when a host (Cursor) does not expand its plugin variables, which is what kept asking for auth after the key was set. Fixes #7346	2026-09-25 10:24:04 +05:30
mintlify[bot]	8d6c001966	Fix grammar & typos: correct OpenSearch spelling in changelog (#7442 ) Co-authored-by: mintlify[bot] <109931778+mintlify[bot]@users.noreply.github.com>	2026-09-25 09:58:06 +05:30
Varun S G	989c7da0fc	fix(oss): stop ConfigManager from injecting OpenAI's baseURL and model into other providers (#7350 )	2026-09-24 22:14:28 +05:30
Mohd Quamar Tyagi	d675cf68ad	fix(memory): restore Memory and AsyncMemory context-manager protocol (#7354 )	2026-09-24 22:04:57 +05:30
Diwakar Ray Yadav	2c6ff619d1	fix(memory): exclude vector-store-rejected records from ADD results (#7066 )	2026-09-24 22:01:31 +05:30
Kartik	f4acc89a29	docs: remove memory types page and preserve redirects (#7437 )	2026-09-24 18:00:54 +05:30
Kartik	43849c6e9d	feat(integrations): migrate and validate standalone Hermes Mem0 plugin (#7372 )	2026-09-24 17:53:29 +05:30
Kartik	47a69e1e72	docs(changelog): add v2.2.1 entry for Valkey None-timestamps fix (#7425 )	2026-09-24 00:30:19 +05:30
Karthik	ea9bbcabed	feat(profiles): User Profiles v1 — SDK methods + docs (#7340 ) Co-authored-by: Pratik <10096516+pratikgajjar@users.noreply.github.com> Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>	2026-09-24 00:11:22 +05:30
Brennan	0cddc36d52	Protect against None timestamps in Valkey layer (#6993 ) Signed-off-by: Brennan Cathcart <brennancathcart@gmail.com>	2026-09-23 22:32:04 +05:30
mintlify[bot]	83b07b1537	Fix grammar & typos: minor fixes across docs (#7423 ) Co-authored-by: mintlify[bot] <109931778+mintlify[bot]@users.noreply.github.com>	2026-09-23 19:53:11 +05:30
Kartik	8c02c425a5	fix(agent-plugins): match memo prompts and tool descriptions, release 0.3.3 (#7420 ) Co-authored-by: Claude <noreply@anthropic.com>	2026-09-23 19:35:25 +05:30
mintlify[bot]	f8082a7345	Fix grammar & typos: API casing in template heading (#7410 ) Co-authored-by: mintlify[bot] <109931778+mintlify[bot]@users.noreply.github.com>	2026-09-22 20:06:21 +05:30
Deshraj Yadav	5d38e3703a	chore: remove CLI_SPECIFICATION.md (#4578 ) Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> Co-authored-by: kartik-mem0 <kartik.labhshetwar@mem0.ai>	2026-09-22 19:52:54 +05:30
88lin	fd8fd087ea	docs(vectordbs/pinecone): document extra_params on the Python config table (#7222 )	2026-09-22 19:25:51 +05:30
Shahil kadia	a214ec37bc	fix(examples): migrate OSS Memory search/get_all calls to v3 filters API (#7300 ) Co-authored-by: Shahil Kadia <nexiouscaliver@users.noreply.github.com>	2026-09-22 19:01:33 +05:30
mintlify[bot]	8b38da9ab8	Fix grammar & typos: SDK changelog v2.0.8 entry (#6716 ) Co-authored-by: mintlify[bot] <109931778+mintlify[bot]@users.noreply.github.com>	2026-09-22 18:51:03 +05:30
mintlify[bot]	17852dc648	SEO & metadata audit: shorten supabase cookbook description (#7380 ) Co-authored-by: mintlify[bot] <109931778+mintlify[bot]@users.noreply.github.com>	2026-09-22 18:50:39 +05:30
Himanshu	a39a802bbc	docs(cookbooks): Company Brain with Mem0 Platform + Supabase (#7309 )	2026-09-18 23:19:15 +05:30
Saket Aryan	19f7134082	chore(release): bump every package the telemetry attribution work changed (#7373 ) Co-authored-by: kartik-mem0 <kartik.labhshetwar@mem0.ai>	2026-09-18 16:28:55 +05:30
Saket Aryan	a8d3634312	fix(plugins): stop the TypeScript telemetry losing events and misattributing accounts (#7358 )	2026-09-18 14:13:22 +05:30
Saket Aryan	1a5c7ad28c	feat(integrations): declare which surface each client is, and its version (#7326 )	2026-09-18 14:13:11 +05:30
Saket Aryan	4e38b057fd	fix(plugins): count installs once, and re-resolve the email when the key changes (#7325 )	2026-09-18 13:46:25 +05:30
Saket Aryan	3362999095	fix(plugins): stop delivering telemetry events twice, and stop losing parked ones (#7324 )	2026-09-18 13:43:33 +05:30
Saket Aryan	012cd32c3a	fix(plugins): report the plugin that produced the event, not the one that sent it (#7323 )	2026-09-18 13:42:34 +05:30
Saket Aryan	e4e0307ae6	fix(plugins): say what telemetry actually sends, and salt the hashes (#7322 )	2026-09-18 13:23:05 +05:30
Kartik	84bf468176	docs: add practical Mem0 Copilot guide (MEM-6344) (#7337 )	2026-09-18 06:54:04 +05:30
mintlify[bot]	f135cb9949	SEO & metadata audit: shorten hermes description (#7359 ) Co-authored-by: mintlify[bot] <109931778+mintlify[bot]@users.noreply.github.com>	2026-09-17 19:32:03 +05:30
ANIRUDDHA ADAK	f5220ff8d4	fix(security): bump next to 15.5.24, patches GHSA-p293-qw3h-jr36 (#7320 )	2026-09-17 19:23:45 +05:30
Paurush Mittal	0df3e4b87d	fix(docs): correct rendered titles and remaining SEO links (#7344 )	2026-09-16 17:14:33 +05:30
PowderXu	b51f7692f0	docs(upstash): correct the default collection namespace (#7287 )	2026-09-15 19:41:46 +05:30
jianyx1	dc7f88363f	docs: fix Hermes integration page to match the current plugin (#7244 )	2026-09-15 19:23:17 +05:30
Harsh Vardhan Gupta	c7ee362aff	fix(security): resolve 12 Vanta/Dependabot vulnerabilities across 6 pnpm workspaces + poetry.lock (#7280 ) Co-authored-by: kartik-mem0 <kartik.labhshetwar@mem0.ai>	2026-09-11 16:07:57 +05:30
Kartik	d873892dad	feat(plugins)!: make Sidekick exclusive to Claude Code (#7278 )	2026-09-10 20:51:50 +05:30