# Knowledge Graph

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.

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.

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

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

An implementation of a persistent memory server based on knowledge graphs, supporting cross - session memory of user information and an error learning system, including core functions such as entity management, relationship establishment, observation recording, and error lessons.

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.

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

A student knowledge graph management server that provides structured management and progress tracking of learning resources such as courses, assignments, and exams

An intelligent context management system designed for development teams, persistently recording project structure, dependencies, and development progress

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.

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.

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 persistent memory service implementation based on a knowledge graph that allows Claude to remember user information across chats and builds a memory network through entities, relationships, and observation data.

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

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

A fully functional LightRAG MCP server that provides 22 complete tools, covering four major functional modules: document management, query operations, knowledge graphs, and system management, achieving 100% compatible integration with the LightRAG API.

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.

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

A universal resource management system that supports managing multiple types of resources (papers, web pages, books, etc.) and integrating with knowledge graphs, providing functions such as resource identification, note - taking, status tracking, and entity association.

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

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

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

An MCP server integrating the Vibe Coding method and knowledge graph technology, using the Kuzu graph database for AI-assisted software development, supporting multi-language code analysis and enterprise-level security performance.

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

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.

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