Cognee MCP Server

@topoteretes

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topoteretes

关于 Cognee MCP Server

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#cognee#mcp-server#ai-memory-engine

Cognee MCP Server 配置

暂无标准配置

该服务器的 README 中没有可解析的 MCP 配置块，请前往代码仓库查看安装说明。

代码仓库

Cognee MCP Server 工具

Builds knowledge graph from the input text and performs search in it.

概览

What is cognee-mcp-server?

An MCP server for cognee, an AI memory engine. It provides a tool that builds a knowledge graph from input text and performs search within that graph, returning retrieved edges.

How to use cognee-mcp-server?

Configure it in your Claude Desktop client (claude_desktop_config.json) using uvx. Set the required environment variables (e.g., LLM_API_KEY, GRAPH_DATABASE_PROVIDER, VECTOR_DB_PROVIDER, DB_PROVIDER, DB_NAME). Invoke the Cognify_and_search tool with the text and search query as inputs.

Key features of cognee-mcp-server

Builds a knowledge graph from input text
Performs search in the constructed graph
Returns retrieved edges of the knowledge graph
Supports optional custom Pydantic graph models

Use cases of cognee-mcp-server

Ingesting unstructured text and answering queries over it
Building a searchable memory layer for AI applications

常见问题

What does the Cognify_and_search tool do?

It constructs a knowledge graph from the provided text and then performs a search using the given query, returning the matching edges of the graph.

Does cognee-mcp-server support custom graph models?

Yes. You can optionally provide a `graph_model_file` (filename of a custom Pydantic graph model implementation) and `graph_model_name` (the class name) to customize the graph structure.

What environment configuration is required?

You must set `LLM_API_KEY`, `GRAPH_DATABASE_PROVIDER`, `VECTOR_DB_PROVIDER`, `DB_PROVIDER`, and `DB_NAME`. Example values: networkx, lancedb, sqlite.

What runtime dependencies does it have?

It requires Python and uv (for running via uvx). The optional custom graph model feature depends on a Pydantic implementation.

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