docs: remove deprecated Graph Memory references
Graph Memory was deprecated on April 16, 2026. This removes remaining mentions across docs that could mislead readers into thinking it is still a supported feature. - Platform pages (overview, quickstart, faqs, platform-vs-oss, vibecoding): remove graph memory from feature lists, comparison table, and intro copy - Platform features (platform-overview, mcp-integration, advanced-memory-operations): rephrase "graph-powered retrieval" to "advanced retrieval"; drop "Enable graph memories" tip; remove graph-edge verification step from the metadata example - Core concepts (add, search, memory-types, memory-evaluation): remove "optional graph storage" / "graph features" / "graph writes" / "graph toggles"; drop "graph" from Entity Search description; remove outdated add/search architecture diagrams (replacement pending) - Open source features (overview, rest-api): remove "graph relationships" and "graph backend(s)" from REST server config narrative - API reference (organizations-projects): drop "graph settings" from Update Project Settings description - Cookbooks: remove "Graph Memory on Neptune" card (page removed) and Neptune mention from AWS Bedrock card; remove "Graph Capabilities" bullet from Gemini cookbook; remove graph-memory conditional bullet from controlling-memory-ingestion - CLI: remove --graph / --no-graph flags from mem0 add / mem0 search flag tables and MEM0_ENABLE_GRAPH env var - Images: delete orphan add_architecture.png and search_architecture.png
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rudrajmehta-mem0
@@ -64,7 +64,7 @@ const memory = new Memory({ apiKey: process.env.MEM0_API_KEY!, async: true });
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</Tab>
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</Tabs>
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## Add memories with metadata and graph context
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## Add memories with metadata
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<Tabs>
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<Tab title="Python">
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@@ -109,7 +109,7 @@ const result = await memory.add(conversation, {
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</Tabs>
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<Info icon="check">
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Successful calls return memories tagged with the metadata you passed. In the dashboard, confirm a graph edge between “Morgan” and “Tokyo” and verify the `trip=japan-2025` tag exists.
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Successful calls return memories tagged with the metadata you passed. In the dashboard, verify the `trip=japan-2025` tag exists on the new memory.
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</Info>
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## Retrieve and refine
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@@ -201,7 +201,7 @@ await memory.deleteAll({ userId: "traveler-42", runId: "planning-call-1" });
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/>
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<Card
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title="Explore Reranker Search"
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description="See how rerankers boost accuracy after vector + graph retrieval."
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description="See how rerankers boost accuracy after advanced retrieval."
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icon="sparkles"
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href="/open-source/features/reranker-search"
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/>
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@@ -121,7 +121,6 @@ echo "Loves hiking on weekends" | mem0 add --user-id alice
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| `-f, --file` | Read messages from a JSON file |
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| `-m, --metadata` | Custom metadata as JSON |
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| `--categories` | Categories (JSON array or comma-separated) |
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| `--graph / --no-graph` | Enable or disable graph memory extraction |
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| `-o, --output` | Output format: `text`, `json`, `quiet` |
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### `mem0 search`
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@@ -141,7 +140,6 @@ mem0 search "preferred tools" --user-id alice --output json --top-k 5
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| `--rerank` | Enable reranking |
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| `--keyword` | Use keyword search instead of semantic |
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| `--filter` | Advanced filter expression (JSON) |
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| `--graph / --no-graph` | Enable or disable graph in search |
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| `-o, --output` | Output format: `text`, `json`, `table` |
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### `mem0 list`
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@@ -436,7 +434,6 @@ For non-interactive environments (CI, agent runtimes), set credentials via `mem0
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| `MEM0_AGENT_ID` | Default agent ID |
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| `MEM0_APP_ID` | Default app ID |
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| `MEM0_RUN_ID` | Default run ID |
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| `MEM0_ENABLE_GRAPH` | Enable graph memory (`true` / `false`) |
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Environment variables take precedence over values in the config file, which take precedence over defaults.
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@@ -9,7 +9,7 @@ iconType: "solid"
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<Accordion title="How does Mem0 work?">
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Mem0 utilizes a sophisticated hybrid database system to efficiently manage and retrieve memories for AI agents and assistants. Each memory is linked to a unique identifier, such as a user ID or agent ID, enabling Mem0 to organize and access memories tailored to specific individuals or contexts.
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When a message is added to Mem0 via the `add` method, the system extracts pertinent facts and preferences, distributing them across various data stores: a vector database and a graph database. This hybrid strategy ensures that diverse types of information are stored optimally, facilitating swift and effective searches.
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When a message is added to Mem0 via the `add` method, the system extracts pertinent facts and preferences, distributing them in a managed vector store. This strategy ensures that diverse types of information are stored optimally, facilitating swift and effective searches.
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When an AI agent or LLM needs to access memories, it employs the `search` method. Mem0 conducts a comprehensive search across these data stores, retrieving relevant information from each.
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@@ -130,7 +130,6 @@ The Mem0 MCP server enables powerful memory capabilities for your AI application
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## Performance tips
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- Enable graph memories for relationship-aware recall
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- Use specific filters when searching large memory sets
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- Batch operations when adding multiple memories
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- Monitor memory usage in the Mem0 dashboard
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@@ -1,10 +1,10 @@
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---
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title: Overview
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description: "See how Mem0 Platform features evolve from baseline filters to graph-powered retrieval."
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description: "See how Mem0 Platform features evolve from baseline filters to advanced retrieval."
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icon: "list"
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---
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Mem0 Platform features help managed deployments scale from basic filtering to graph-powered retrieval and data governance. Use this page to pick the right feature lane for your team.
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Mem0 Platform features help managed deployments scale from basic filtering to advanced retrieval and data governance. Use this page to pick the right feature lane for your team.
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<Info>
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New to the platform? Start with the <Link href="/platform/quickstart">Platform quickstart</Link>,
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@@ -11,7 +11,7 @@ Mem0 is the memory engine that keeps conversations contextual so users never rep
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## Why it matters
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- **Personalized replies**: Memories persist across users and agents, cutting prompt bloat and repeat questions.
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- **Hosted stack**: Mem0 runs the vector store, graph services, and rerankers—no provisioning, tuning, or maintenance.
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- **Hosted stack**: Mem0 runs the vector store and rerankers—no provisioning, tuning, or maintenance.
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- **Enterprise controls**: Audit logs and workspace governance ship by default for production readiness.
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<AccordionGroup>
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@@ -21,7 +21,7 @@ Mem0 is the memory engine that keeps conversations contextual so users never rep
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| --- | --- |
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| Fast setup | Add a few lines of code and you’re production-ready—no vector database or LLM configuration required. |
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| Production scale | Automatic scaling, high availability, and managed infrastructure so you focus on product work. |
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| Advanced features | Graph memory, webhooks, multimodal support, and custom categories are ready to enable. |
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| Advanced features | webhooks, multimodal support, and custom categories are ready to enable. |
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| Enterprise ready | Audit logs, workspace governance, and dedicated support keep security and governance covered. |
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</Accordion>
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</AccordionGroup>
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@@ -49,7 +49,7 @@ Mem0 is the memory engine that keeps conversations contextual so users never rep
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Add, search, update, and delete workflows.
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</Card>
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<Card title="Explore Platform Features" icon="sparkles" href="/platform/features/platform-overview">
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Graph memory, async clients, and rerankers.
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async clients and rerankers.
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</Card>
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<Card title="Configure Advanced Operations" icon="bolt" href="/platform/advanced-memory-operations">
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Metadata filters and per-request toggles.
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@@ -57,7 +57,6 @@ Mem0 offers two powerful ways to add memory to your AI applications. Choose base
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<Accordion title="Advanced Capabilities" icon="sparkles">
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| Feature | Platform | Open Source |
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|---------|----------|-------------|
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| **Graph Memory** | ✅ (Managed) | ✅ (Self-configured) |
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| **Multimodal support** | ✅ | ✅ |
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| **Custom categories** | ✅ | Limited |
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| **Advanced retrieval** | ✅ | ✅ |
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@@ -155,7 +155,7 @@ Learn how to search, update, and delete memories with complete CRUD operations
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</Card>
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<Card title="Platform Features" icon="star" href="/platform/features/platform-overview">
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Explore advanced features like metadata filtering, graph memory, and webhooks
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Explore advanced features like metadata filtering and webhooks
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</Card>
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<Card title="API Reference" icon="code" href="/api-reference/memory/add-memories">
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