Enables retrieval and analysis of graph data from the Pythagraph RED API. Provides detailed graph statistics, node/edge distributions, and formatted table outputs for data visualization and analysis.
Provides tools for AI-powered graph analysis, including relationship extraction, adjacency matrix creation, and network centrality calculations. It enables users to perform complex structural analysis and generate interactive D3.js visualizations from structured data.
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 LLMs and AI agents to query a biomedical knowledge graph stored in RedisGraph, with tools for concept search, synonym enrichment, and study variable discovery through semantic relationships.
Enables creating, managing, analyzing, and visualizing knowledge graphs with support for multiple graph types (topology, timelines, changelogs, requirements, knowledge bases, ontologies) including node/edge management and resource association.