The integration of HugeGraph with AI/LLM & GraphRAG
hugegraph-ai connects the HugeGraph graph platform with artificial intelligence tools, including large language models, graph retrieval, knowledge-graph construction, and graph machine learning. It is intended for developers building applications that query, analyze, or reason over graph data through Python interfaces and related modules.
This repository also configures its own agents. See what hugegraph-ai tells them →
Skill Codex ✓ vendor
Route HugeGraph MCP graph data extraction and controlled import/delete tasks to stable public tools. Use when the user asks to extract graph data from text, import structured vertices or edges, verify an import, or asks whether table, SQL, update, or delete graph writes are available.
Skill Codex ✓ vendor
Route HugeGraph MCP operational checks to status, schema, MCP read-only state, AI availability, and read-only verification tools. Use when the user asks to check the current graph, schema, MCP connection, readonly state, HugeGraph-AI state, counts, indexes, or readiness.
Skill Codex ✓ vendor
Route HugeGraph MCP structured graph query tasks to stable read-only tools. Use when the user asks graph questions, asks to generate Gremlin, provides Gremlin to explain, or needs read-only graph exploration.
Skill Codex ✓ vendor
Route HugeGraph MCP regression testing tasks to the current public tool surface, including inspection, read-only queries, Gremlin generation, extraction, controlled import, schema validate/dry-run, safety guards, and admin-gated tool checks.
Skill Codex ✓ vendor
Route HugeGraph MCP schema design, validation, and dry-run preview tasks to stable public tools. Use when the user asks to design vertex labels, edge labels, properties, primary keys, indexes, or preview schema operations.
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: