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Cognee MCP brings persistent AI memory to your workflow through the Model Context Protocol.

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What is MCP?

The Model Context Protocol (MCP) is a standard for adding specialized tools to AI assistants. It allows AI tools like Claude or Cursor to work with external systems such as databases, APIs, and AI platforms. Without MCP, each AI assistant needs custom integrations for every external system. This creates duplication and inconsistency across tools. MCP provides a single method for extending AI assistants with:
  • Standardized connections between AI tools and external systems
  • Secure data access with built-in authentication and permissions
  • Tool interoperability so you can switch between AI providers
  • Persistent memory that survives across conversations and sessions

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How Cognee MCP Works

Cognee MCP exposes 14 specialized tools through the MCP protocol. These tools handle memory management, code intelligence, and data operations. You access them through MCP-compatible AI assistants like Cursor, Claude Desktop, Continue, Cline, and Roo Code. The tools enable your AI assistant to:
  • Store and retrieve knowledge from previous conversations
  • Build persistent understanding of your codebase and projects
  • Access structured memories across different sessions
For new integrations, prefer the v1.0 memory tools (remember, recall, forget). The legacy tools remain available when you need lower-level control. See the Tools Reference for all available operations.

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Architecture Modes

Cognee MCP can run in two modes: Standalone Mode: The MCP server manages its own database and processing. Each MCP instance maintains separate data. Use this for personal development or when clients need isolated environments. API Mode: The MCP server connects to a centralized Cognee backend via API. Multiple MCP instances can share the same knowledge graph. Use this when you want team members to access shared memory or when running multiple AI clients that need consistent data.
Do I need to install Cognee separately? No. The cognee-mcp package bundles the full Cognee library, so following any setup guide (Docker or Local Setup) installs the complete Cognee stack together with the MCP tools — you get “everything plus MCP.” In Standalone Mode the server runs the entire Cognee pipeline (ingestion, graph building, and search) locally with its own database; no extra Cognee install or running backend is required. You only need a separate Cognee REST API when you switch to API Mode to share one knowledge graph across clients.

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Setup Options

Choose your deployment method:

Docker Quickstart

Recommended for most usersGet running in minutes with a pre-built container.

API Mode (Shared)

For teamsConnect multiple clients to a shared knowledge graph.

Local Setup

For developmentBuild from source for full control and latest features.
Using Cognee Cloud? Cognee MCP and Cognee Cloud are separate systems with different APIs and authentication schemes. See Cognee Cloud & MCP to understand how they relate and when to use each.

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Next Steps

Tools Reference

See all available MCP tools and operations

Client Integrations

Connect with Cursor, Claude, Continue, and more