cognee-mcp

# Cognee Starter Kit Welcome to the <a href="https://github.com/topoteretes/cognee">cognee</a> Starter Repo! This repository is designed to help you get started quickly by providing a structured dataset and pre-built data pipelines using cognee to build powerful knowledge graphs. You can use this repo to ingest, process, and visualize data in minutes. By following this guide, you will: - Load structured company and employee data - Utilize pre-built pipelines for data processing - Perform graph-based search and query operations - Visualize entity relationships effortlessly on a graph # How to Use This Repo 🛠 ## Install uv if you don't have it on your system ``` pip install uv ``` ## Install dependencies ``` uv sync ``` ## Setup LLM Add environment variables to `.env` file. In case you choose to use OpenAI provider, add just the model and api_key. ``` LLM_PROVIDER="" LLM_MODEL="" LLM_ENDPOINT="" LLM_API_KEY="" LLM_API_VERSION="" EMBEDDING_PROVIDER="" EMBEDDING_MODEL="" EMBEDDING_ENDPOINT="" EMBEDDING_API_KEY="" EMBEDDING_API_VERSION="" ``` Activate the Python environment: ``` source .venv/bin/activate ``` ## Run the Default Pipeline This script runs the cognify pipeline with default settings. It ingests text data, builds a knowledge graph, and allows you to run search queries. ``` python src/pipelines/default.py ``` ## Run the Low-Level Pipeline This script implements its own pipeline with custom ingestion task. It processes the given JSON data about companies and employees, making it searchable via a graph. ``` python src/pipelines/low_level.py ``` ## Run the Custom Model Pipeline Custom model uses custom pydantic model for graph extraction. This script categorizes programming languages as an example and visualizes relationships. ``` python src/pipelines/custom-model.py ``` ## Graph preview cognee provides a visualize_graph function that will render the graph for you. ``` graph_file_path = str( pathlib.Path( os.path.join(pathlib.Path(__file__).parent, ".artifacts/graph_visualization.html") ).resolve() ) await visualize_graph(graph_file_path) ``` # What will you build with cognee? - Expand the dataset by adding more structured/unstructured data - Customize the data model to fit your use case - Use the search API to build an intelligent assistant - Visualize knowledge graphs for better insights