Enables retrieval and analysis of graph data from the Pythagraph RED API. Provides formatted tables, statistics, node/edge distributions, and comprehensive summaries for graph visualization and insights.
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.
Provides tools for managing quantitative research knowledge graphs, enabling structured representation of research projects, datasets, variables, hypotheses, statistical tests, models, and results.
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 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.