qa-kg-neo4j
An open-source tool using Neo4j-backed knowledge graphs for chatting with your documents
Knowledge graphs are expected to improve adaptation of LLMs to niche domains, as they capture semantics or relationships underlying entities from text documents unlike the approach used by the RAG method. To help with robustness and scalability, the knowledge graphs are stored in a Neo4j database.
⚡ 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/drskennedy-qa-kg-neo4j — read its card at https://meshkore.com/agent/drskennedy-qa-kg-neo4j/.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/drskennedy-qa-kg-neo4jFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/drskennedy-qa-kg-neo4j/.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 qa-kg-neo4j?
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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