# Knowledge Graph

A general resource management system that supports the management of multiple resource types (papers, web pages, books, etc.) and integrates with the knowledge graph, providing structured notes and status tracking 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.

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.

The GraphDB MCP Server provides read-only access to Ontotext GraphDB, supporting SPARQL queries and RDF graph exploration

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.

An enhanced MCP memory server with functions of dynamic compression, context management, and integration of thinking processes

A Python in - memory MCP server based on a knowledge graph, using SQLite as the backend to achieve cross - session persistent memory storage and management.

The knowledge graph memory server is a persistent memory system based on a local knowledge graph that supports remembering user information across chat sessions.

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

MCP Memory is a persistent memory system based on Elasticsearch, providing cross - session memory storage and retrieval functions for AI conversations, solving the AI forgetting problem and enabling long - term context association.

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 Python memory server based on a knowledge graph for implementing the persistent memory function of Claude AI

Flexible GraphRAG is a flexible platform that supports multi - data source document processing, automatic knowledge graph construction, hybrid search (full - text, vector, graph), and AI Q&A. It includes a FastAPI backend, an MCP server, and various front - end interfaces.

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.

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.

The Project MCP Server is a tool for managing project knowledge graphs, providing structured representations of projects, tasks, milestones, resources, and team members to help project managers track progress, manage risks, allocate resources, and make decisions.

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

MCP Server Knowledge Graph Memory Project

An MCP memory server based on the Qdrant vector database, providing knowledge graph and semantic search capabilities.

A server for managing qualitative research knowledge graphs, providing structured representation and management tools for research projects, participants, interviews, coding, and themes

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

Memento MCP is a knowledge - graph - based LLM memory system that provides semantic retrieval, context recollection, and time awareness functions, supporting long - term persistent storage and efficient retrieval.

An implementation of the MCP server based on txtai, providing semantic search, knowledge graph, and AI text processing functions, supporting local knowledge base construction and standardized interface access.

The Knowledge Graph Memory Server implements a persistent memory function and supports cross - session storage of user information

Logseq Knowledge Graph AI Interaction Tool

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.

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.