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

4. agents ⚡ Experimental An intelligent database migration agent that automates the process of migrating from MySQL to Memgraph using LLM-powered graph modeling and analysis. Features automated schema analysis, intelligent graph modeling with interactive refinement, and data migration with validation.

Key Features

Migration Agent Capabilities

• 🔍 Intelligent Schema Analysis: Automatically analyzes MySQL database structure and relationships
• 🧠 LLM-Powered Graph Modeling: Uses AI to create optimal graph models from relational schemas
• 🔄 Interactive Refinement: Allows users to refine graph models through natural language feedback
• ⚡ Automated Migration: Handles complete data migration with validation and rollback capabilities
• 📊 Progress Monitoring: Real-time migration progress tracking with detailed logging
• 🛡️ Data Validation: Comprehensive pre and post-migration data integrity checks

Usage examples

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

• Langchain examples
• MCP examples
• Agent migration examples - Interactive MySQL to Memgraph migration workflows

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

Agent integration tests

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

To run a complete migration workflow with the agent:

cd integrations/agents
uv run main.py

Note: The agent requires both MySQL and Memgraph connections. Set up your environment variables in .env based on .env.example.

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

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