ATLAS is an intelligent task and knowledge management system built on TypeScript and Neo4j, designed for LLM agents, providing a three - layer management architecture for projects, tasks, and knowledge.

An MCP server project for threat information collection, supporting the collection of threat intelligence within a specified time range through command - line tools and integration with the Neo4j knowledge graph.

GraphRAG MCP is a hybrid retrieval system that combines the Neo4j graph database and the Qdrant vector database, providing document retrieval services that combine semantics and graph relationships for large language models.

A knowledge graph server based on Neo4j, integrating AI models and the MCP protocol, supporting dynamic knowledge management and semantic search.

The MCP Neo4j Server is a middleware that connects the Neo4j graph database with the Claude desktop, supporting graph database operations through natural language, including querying, creating nodes and relationships, etc.

An implementation of a knowledge graph management MCP server based on Neo4j, providing standard interfaces for the storage and retrieval of graph databases.

The MCP Neo4j Knowledge Graph Memory Server is an enhanced memory storage system based on the Neo4j graph database, providing high-performance knowledge graph storage and retrieval capabilities for AI assistants.

Adaptive Graph of Thoughts is an intelligent scientific reasoning framework based on the Neo4j graph database, which realizes complex scientific reasoning tasks through graph structure and supports integration with AI applications such as Claude Desktop.

The Graphiti MCP Server is a server based on multi - project knowledge graphs, supporting the rapid construction and management of temporary knowledge graphs for AI agents to query through the model context protocol. This project extends the official getzep/graphiti MCP Server, adds support for multiple servers and a single database, and provides a CLI tool with an optimized developer experience.

The Neo4j MCP Server is a knowledge graph storage service that supports environment variable configuration and is compatible with the Model Context Protocol.

A knowledge graph memory server based on Neo4j, providing efficient storage and retrieval capabilities for AI interactions

Neo4j MCP server implementation that manages graph database operations through the Model Context Protocol, is compatible with Cursor and Claude Desktop, and supports Cypher query execution.

A knowledge graph storage and retrieval service based on Neo4j, implemented as a server for the MCP protocol, supporting database connection configuration through environment variables and providing project - specific knowledge graph management functions.

NeoCoder is an AI programming assistance system based on the Neo4j knowledge graph. It enables the interaction between AI assistants and the knowledge graph through an MCP server, providing standardized coding workflows, dynamic instruction manuals, and project memory functions. The system supports multiple operation modes (incarnations), including basic programming, scientific research, decision - making analysis, complex system modeling, knowledge graph management, and code analysis. It stores workflow templates and execution records in Neo4j to ensure the traceability and standardization of the coding process.

The Unified MCP Tool Graph is a research - driven project that provides an intelligent infrastructure layer for large language models (LLMs) and agent AI systems to dynamically retrieve the most relevant tools by aggregating and structuring tool APIs from different MCP servers into a centralized Neo4j graph database.

A prototype of a knowledge service MCP server based on the Neo4J database that can extract knowledge from Neo4J to answer questions and support use through clients such as Cursor.

A Neo4j database operation service based on the MCP framework, providing asynchronous database operation interfaces and proxy configuration support

A model context protocol (MCP) SDK implemented in Python for building standard servers and clients interacting with LLMs

An interactive chat interface project for querying Neo4j databases through natural language, integrating Chainlit, Neo4j MCP, and Claude LLM technologies.

CodeRAG is a tool that transforms codebases into intelligent knowledge graphs. It builds a code structure diagram through Neo4J, supports multi - language analysis, provides code quality metrics and AI integration, and helps with code review, architecture analysis, and refactoring.