Cognee MCP Server

Cognee MCP provides a powerful knowledge management system that enables semantic search and retrieval across your data. It specializes in code understanding through its code graph pipeline, allowing for intelligent navigation and comprehension of codebases. The MCP server integrates with the broader Cognee ecosystem to provide context-aware responses and insights based on your data.

Cognee MCP

Cognee MCP is a Model Context Protocol server that provides knowledge management and retrieval capabilities with a focus on code understanding.

Installation

To install and use Cognee MCP, follow these steps:

Clone the repository:

git clone https://github.com/topoteretes/cognee.git
cd cognee/cognee-mcp

Set up a Python environment (the repository uses Python 3.9+):

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

Install dependencies:

pip install -e .

Configuration

Cognee MCP can be configured through environment variables. Key configuration options include:

Database connections (PostgreSQL with pgvector support)
Vector embedding settings
Graph database configuration
Authentication settings

Usage

Once installed, you can start the Cognee MCP server by running:

python -m cognee_mcp

The server will start and listen for MCP requests, providing access to Cognee's knowledge management capabilities.

Features

Semantic Search: Search through your data using natural language queries
Code Graph Pipeline: Analyze and understand code repositories by building dependency graphs
Document Management: Store, retrieve, and manage various document types
Vector Search: Leverage vector embeddings for similarity-based retrieval
Dataset Organization: Group related data into datasets for better organization

Integration with AI Assistants

Cognee MCP is designed to work with AI assistants that support the Model Context Protocol, providing them with access to your knowledge base and code understanding capabilities.