cognee-mcp-server

by topoteretes

392 downloads
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GitHub

Description

# cognee-mcp-server An MCP server for [cognee](https://www.cognee.ai/), an AI memory engine. ## Tools - `Cognify_and_search` : Builds knowledge graph from the input text and performs search in it. - Inputs: - `text` (String): Context for knowledge graph contstruction -…

About

# cognee-mcp-server An MCP server for [cognee](https://www.cognee.ai/), an AI memory engine. ## Tools - `Cognify_and_search` : Builds knowledge graph from the input text and performs search in it. - Inputs: - `text` (String): Context for knowledge graph contstruction - `search_query` (String): Query for retrieval -…

Details

Author
topoteretes
Downloads
392
Categories
Other

- 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

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.

cognee-mcp-server

An MCP server for cognee, an AI memory engine.

Tools

- Cognify_and_search : Builds knowledge graph from the input text and performs search in it.
- Inputs:
- text (String): Context for knowledge graph contstruction
- search_query (String): Query for retrieval
- graph_model_file (String, optional): Filename of a custom pydantic graph model implementation
- graph_model_name (String, optional): Class name of a custom pydantic graph model implementation
- Output:
- Retrieved edges of the knowledge graph

Configuration

Usage with Claude Desktop

Add this to your claude_desktop_config.json:
<details>
<summary>Using uvx</summary>

"mcpcognee": {
  "command": "uv",
  "args": [
    "--directory",
    "/path/to/your/cognee-mcp-server",
    "run",
    "mcpcognee"
  ],
  "env": {
    "ENV": "local",
    "TOKENIZERS_PARALLELISM": "false",
    "LLM_API_KEY": “your llm api key”,
    "GRAPH_DATABASE_PROVIDER": “networkx”,
    "VECTOR_DB_PROVIDER": "lancedb",
    "DB_PROVIDER": "sqlite",
    "DB_NAME": “cognee_db”
  }
}
</details>
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