cognee-mcp

Features

• Interconnect and retrieve your past conversations, documents, images and audio transcriptions
• Replaces RAG systems and reduces developer effort, and cost.
• Load data to graph and vector databases using only Pydantic
• Manipulate your data while ingesting from 30+ data sources

Get Started

Get started quickly with a Google Colab notebook, Deepnote notebook or starter repo.

Installation

You can install Cognee using either pip, poetry, uv or any other python package manager. Cognee supports Python 3.8 to 3.12.

With pip

pip install cognee

Local Cognee installation

You can install the local Cognee repo using pip, poetry and uv. For local pip installation please make sure your pip version is above version 21.3.

with UV with all optional dependencies

uv sync --all-extras

Basic Usage# Setup

import os
os.environ["LLM_API_KEY"] = "YOUR OPENAI_API_KEY"

Simple example

import cognee
import asyncio

async def main():
    await cognee.add("Natural language processing (NLP) is an interdisciplinary subfield of computer science and information retrieval.")
    results = await cognee.search("Tell me about NLP")
    for result in results:
        print(result)

if __name__ == '__main__':
    asyncio.run(main())

Cognee UI

You can also cognify your files and query using cognee UI. Try cognee UI out locally.