# Knowledge Graph

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

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

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.

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.

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

LLM Conversation Memory System Based on Redis 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 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.

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

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

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

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

Knowledge Graph Generator MCP Server Project

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.

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.

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.

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.

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

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

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.

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.

Logseq Knowledge Graph AI Interaction Tool

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.

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