A lightweight server implementation of the Model Context Protocol that connects Memgraph database with LLMs, allowing users to interact with graph databases through natural language.
A Knowledge Graph MCP server optimized for LLM context efficiency through compact JSON and SQLite persistence. It enables full graph management including node/edge CRUD operations, full-text search, and subgraph traversal.
Model Context Protocol (MCP) server for TigerGraph that lets AI agents interact with TigerGraph through the MCP standard using pyTigerGraph's async APIs.
Graph-based MCP server for persistent AI memory, session checkpointing, context compression, and cross-session context management for LLM applications.