Enables AI agents to interact with an embedded graph database (GrafeoDB) via the Model Context Protocol, providing tools for graph CRUD, GQL queries, full-text and vector search, and graph algorithms.
Enables AI assistants to interact with Gremlin-compatible graph databases through natural language, supporting schema discovery, complex graph queries, relationship analysis, and data import/export operations.
Enables AI agents to manage and interact with Apache AGE graph databases through natural language. Supports creating, updating, querying, and visualizing multiple graphs with vertices and edges.
Enables AI assistants to interact with Neo4j graph databases through natural language, supporting Cypher queries, schema management, data manipulation, and graph algorithms.
Model Context Protocol (MCP) server for TigerGraph that lets AI agents interact with TigerGraph through the MCP standard using pyTigerGraph's async APIs.
