# Knowledge Graph

MemoryMesh is a knowledge graph server designed for AI models, focusing on text role - playing games and interactive narratives. It helps AI maintain consistent and structured memory in conversations through dynamic schema definition and automatic tool generation, enabling a richer and more dynamic interactive experience.

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

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.

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

Logseq Knowledge Graph AI Interaction Tool

A knowledge graph management server based on the MCP protocol, supporting multiple startup methods and complete knowledge graph operation functions, including experimental short story generation capabilities.

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.

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

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.

The Memory Custom project adds custom memory paths and timestamp functions to the Memory server of the MCP team, optimizing the management of knowledge graphs and interaction tracking.

A persistent memory server based on a knowledge graph, supporting cross - session storage and retrieval of user information

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.

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

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.

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.

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

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

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

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.

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

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

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 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.

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.

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.

This project uses Docker Compose to set up multiple Model Context Protocol (MCP) services, including Git operations, file systems, PostgreSQL databases, knowledge graph storage, and visual debugging tools, providing a complete local development environment deployment solution.

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.