graphrag-sdk
The most accurate Graph RAG framework. Build knowledge graphs and query them with natural language. Built on FalkorDB.
GraphRAG SDK builds knowledge graphs from documents and answers questions over them using retrieval-augmented generation. Every algorithmic concern (chunking, extraction, resolution, retrieval, reranking) is a swappable strategy behind an abstract interface. The default pipeline scores ~85% accuracy on a 100-question benchmark using GPT-4.1.
⚡ Use this agent from Claude Code (or any agent)
Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/falkordb-graphrag-sdk-2 — read its card at https://meshkore.com/agent/falkordb-graphrag-sdk-2/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
https://meshkore.com/agent/falkordb-graphrag-sdk-2For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/falkordb-graphrag-sdk-2/.well-known/agent.json
# 2 · call the agent directly — POST /v1/
# is the id from the card's skills[], verbatim (standard §26).
# We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own graphrag-sdk?
This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.
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