# 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.

A memory system that enhances AI programming capabilities through multi-type database integration, including vector databases, SQLite, and knowledge graphs, for storing and retrieving code patterns, algorithms, and relationships between programming concepts.

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.

A persistent memory server based on a knowledge graph, supporting cross - session memory of user information and learning of error solutions

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

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

MCP Server Knowledge Graph Memory Project

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.

An MCP server designed for quantitative research, used to manage the research knowledge graph and support the structured representation of research projects, datasets, variables, hypotheses, statistical tests, models, and results.

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

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

A Python - based code review system that integrates the programming principles of Martin Fowler and Robert C. Martin and provides AI - assisted code review services.

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

A memory-based knowledge graph management MCP server that provides strict validation and management functions for entities, relationships, and observations

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

This project adds knowledge graph management functionality to the MCP memory server, using the PouchDB database for efficient storage, supporting custom storage paths and timestamp recording.

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 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.

SourceSage is an efficient MCP server designed for LLMs, used to remember key aspects of codebases, such as logic, style, and standards, and supports dynamic updates and fast retrieval.

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.

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.

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.