Memgraph AI Toolkit

A unified mono-repo for integrating AI-powered graph tools on top of Memgraph.
This repository contains the following libraries:

1. memgraph-toolbox Core Python utilities and CLI tools for querying and analyzing a Memgraph database. The package is available on the PyPi

2. langchain-memgraph A LangChain integration package, exposing Memgraph operations as LangChain tools and toolkits. The package is available on the PyPi

3. mcp-memgraph An MCP (Model Context Protocol) server implementation, exposing Memgraph tools over a lightweight STDIO protocol. The package is available on the PyPi

Usage examples

For individual examples on how to use the toolbox, LangChain, or MCP, refer to our documentation:

• Langchain examples
• MCP examples

Developing locally

You can build and test each package directly from your repo. First, start a Memgraph MAGE instance with schema info enabled:

docker run -p 7687:7687 \
  --name memgraph \
  memgraph/memgraph-mage:latest \
  --schema-info-enabled=true

Once Memgraph is running, install any package in “editable” mode and run its test suite. For example, to test the core toolbox:

uv pip install -e memgraph-toolbox[test]
pytest -s memgraph-toolbox/src/memgraph_toolbox/tests

Core tests

To test the core toolbox, just run:

uv pip install -e memgraph-toolbox[test]
pytest -s memgraph-toolbox/src/memgraph_toolbox/tests

Langchain integration tests

To run the LangChain tests, create a .env file with your OPENAI_API_KEY, as the tests depend on LLM calls:

uv pip install -e integrations/langchain-memgraph[test]
pytest -s integrations/langchain-memgraph/tests

MCP integration tests

uv pip install -e integrations/mcp-memgraph[test]
pytest -s integrations/mcp-memgraph/tests

If you are running any test on MacOS in zsh, add "" to the command:

uv pip install -e memgraph-toolbox"[test]"