# Knowledge Graph

The Neo4j MCP project connects LLMs with external systems through a standardized protocol to enable natural - language operation of Neo4j databases, knowledge graph storage, and Aura cloud service management.

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

An MCP server that connects AI agents with Apache Jena, providing SPARQL query functionality

An MCP server for the AI Memory Engine Cognee, supporting the construction of knowledge graphs from text and searching.

The MCP context manager is a solution for achieving cross - session persistent AI context through a knowledge graph, supporting multi - domain intelligent management.

This project adds custom memory paths and timestamp functions to the MCP team's Memory server, supporting the construction of a knowledge graph through LLM to manage interaction memory.

An implementation of the MCP server based on txtai, providing semantic search, knowledge graph, and AI text processing functions.

A persistent memory server based on knowledge graphs that supports remembering user information across sessions and accumulating experience through an error - learning system. It provides functions for entity - relationship management, observation record storage, and error - solution management, and can be integrated into the Cursor MCP client.

A knowledge graph service supporting both FastAPI and FastMCP protocols, providing core operation functions of the Qdrant vector database.

A Wikidata API service implementation based on the Model Context Protocol, providing entity/property search, metadata extraction, and SPARQL query functions.

An implementation of a persistent memory server based on knowledge graphs, allowing Claude to remember user information across different chats. It provides functions for creating, querying, updating, and deleting entities, relationships, and observations, and supports local JSON storage.

A knowledge graph memory server implemented in Go, providing persistent memory management capabilities across conversations for AI assistants

A knowledge graph memory server implemented in Swift, providing persistent memory functions for large - language models

A Python memory MCP server based on a knowledge graph, using SQLite as the backend to achieve persistent memory storage and management across conversations.

The Graphiti MCP Server is a multi - project knowledge graph server extension based on the official getzep/graphiti. It supports multi - server single - database configuration, provides a developer - friendly CLI tool, and can build temporary knowledge graphs for each project for AI agents to query through the model context protocol.

Repo GraphRAG MCP Server is a service based on the MCP protocol that uses LightRAG and Tree - sitter to build a knowledge graph from code and text documents and provides functions such as question - answering and implementation planning.

The Memory Journal MCP Server is a project context management tool for AI-assisted development, solving the problem of AI context loss across multiple threads and sessions through persistent knowledge graphs and intelligent context recall.

The AI Memory Protocol is a versioned, graph - based persistent memory system designed for AI programming agents, implemented using Sphinx - Needs, supporting the creation, search, update of memories, and integration with AI clients through the MCP protocol.

Fodda MCP Server is an AI knowledge graph service based on the Model Context Protocol (MCP), providing expert knowledge graphs from fields such as PSFK retail, beauty, and sports for AI agents to perform operations such as search, traversal, and evidence retrieval.

KIP is a graph interaction protocol designed for large language models, connecting LLMs with knowledge graphs and providing capabilities for memory persistence, knowledge evolution, and interpretable interaction.

Penfield is a service that provides persistent memory for AI agents. It supports cross - session storage of decisions, preferences, and context, builds a knowledge graph that grows over time, and is compatible with multiple MCP tools.

Memento is a knowledge graph memory system based on SQLite, providing persistent memory functions, supporting full - text retrieval and semantic search, and realizing intelligent context retrieval through BGE - M3 embedding. It is suitable for technical and creative project management.

Project Synapse is a revolutionary MCP server that transforms text into an interconnected knowledge network through semantic analysis and knowledge graph technology and autonomously generates insights. It combines Montague semantics and the Zettelkasten method to achieve the cognitive collaboration ability of AI.

MCP Server Knowledge Graph Memory Project

An implementation of the MCP Server based on txtai, providing semantic search, knowledge graph, and AI text processing functions.

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.

A Deno-based MCP server template that supports publishing through JSR.io and optional Deno Deploy hosting, including knowledge graph functionality implemented with the Deno KV database.

A knowledge graph builder that uses a local AI model to convert text or web page content into structured knowledge graphs, supporting large-scale content processing, real-time visualization, and integration with Neo4j and Qdrant databases.

A flexible resource management system that supports managing multiple types of resources (papers, web pages, books, etc.) and integrating with knowledge graphs, providing functions such as unified identification, structured notes, and status tracking.

A memory server implementing the Model Context Protocol (MCP), providing persistent memory storage and retrieval functions based on a knowledge graph for large language models.