"An introduction to Neo4j, a graph database management system" matching MCP servers:

A containerized FastAPI + MCP server that lets LLM agents inject structured entities and relationships into a Neo4j graph database with safe Cypher execution.

Provides LLM clients with a persistent, scalable knowledge graph memory system that supports semantic retrieval, contextual recall, and temporal awareness.

An MCP server that enables LLMs to perform semantic and fulltext searches within Neo4j while executing complex, search-augmented Cypher queries for GraphRAG applications. It provides tools for database schema discovery and supports multi-provider embeddings to facilitate advanced graph traversals.

Enables LLMs to interact with Neo4j graph databases using natural language to execute Cypher queries and introspect database schemas. It supports both read and write operations for local, Docker, and cloud-based instances like Neo4j Aura.

MCP server for Neo4j graph database operations, enabling Cypher queries, node/relationship management, and schema discovery.

This lets you use Claude Desktop, or any MCP Client, to use natural language to accomplish things with Neo4j and your Aura account.

MCP server for Neo4j that provides abstract graph operations for LLMs, enabling safe and consistent interaction with Neo4j databases through tools like search, insert, update, delete, and schema introspection.

An implementation for managing Neo4j graph database operations through the Model Context Protocol, enabling users to execute Cypher queries against their Neo4j database via AI assistants like Cursor and Claude Desktop.

A lean, local knowledge graph that joins a repo's code to its aSPARK delivery artifacts, enabling agents to trace user stories to code and assess impact of changes, served over MCP.

Enables LLMs to run complex graph algorithms on Neo4j databases, answering graph-related questions by selecting and executing appropriate parameterised graph algorithms.

An MCP server that gives your agent a persistent project brain: vision, architecture decisions, conventions, roadmaps, and automatic session handoff.

Enables AI assistants to interact with Neo4j graph databases through natural language, supporting Cypher queries, schema management, data manipulation, and graph algorithms.

Neo4j MCP Canary is a fast-moving, experimental release of the Neo4j MCP server for customers who want to explore emerging capabilities before they are considered for the official server.

A minimal MCP server with get_weather and create_ticket tools, used for testing MCP servers across protocol, unit, eval, transport, and auth layers.

Enhanced knowledge graph memory server for AI assistants that uses Neo4j as the backend storage engine, enabling powerful graph queries and efficient storage of user interaction information with full MCP protocol compatibility.

Enables storage and retrieval of knowledge in a graph database format, allowing users to create, update, search, and delete entities and relationships in a Neo4j-powered knowledge graph through natural language.

Enables querying and modifying a local MySQL database and a Neo4j knowledge graph through separate read-only and read-write tools, with permissions scoped by database user and Neo4j transaction mode. Lets clients run SELECT statements against MySQL, execute inserts/updates/deletes, and run read or write Cypher queries.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

A TypeScript MCP server for executing Cypher queries and exploring Neo4j graph databases, enabling natural language database interaction through Claude.

Enables interaction with Neo4j databases from the Cursor IDE by executing Cypher queries, managing connections, and retrieving database information.