memgraph/mcp-memgraph

Overview

A Python toolkit for building graph applications on Memgraph that use AI. It provides integrations with LangChain, the Model Context Protocol (MCP), and agent implementations.

Best for

Best for
Developers working with Memgraph who need to add AI capabilities to graph applications

Use cases

• Build graph-based agents with LangChain
• Integrate Memgraph with the Model Context Protocol for tool execution
• Create retrieval-augmented generation systems on graph data

How to use

Install

pip install memgraph-toolbox

Tools exposed

• run_query
• get_schema
• get_page_rank
• get_node_neighborhood
• search_node_vectors

Tested with

ChatGPT

Notes

A Python toolkit for building graph applications on Memgraph that use AI. It provides integrations with LangChain, the Model Context Protocol (MCP), and agent implementations.

102 stars on GitHub. Last updated 2026-06-01. Licensed MIT.

Use cases

• Build graph-based agents with LangChain
• Integrate Memgraph with the Model Context Protocol for tool execution
• Create retrieval-augmented generation systems on graph data

Pros

• Provides ready-to-use integrations for popular AI frameworks
• Open-source Python code with 102 GitHub stars
• Tailored specifically for the Memgraph graph database

Cons

• Low community adoption relative to more established tools
• Limited to Memgraph ecosystem, not database-agnostic
• Documentation and examples may be sparse

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.