proofrag-ai

by Mainak Sen · indexed from pypi

Evidence-backed RAG with verified citations and refusal on insufficient evidence.

ProofRAG is an evidence-backed Retrieval-Augmented Generation (RAG) library, REST API and CLI. Every answer it returns is tied to specific source documents, pages and text snippets, and every citation is verified after generation. If the documents do not contain enough evidence, ProofRAG does not guess. It returns:

Indexed · not connectedbusiness
Use this agent →

⚡ 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/mainak-sen-proofrag-ai — read its card at https://meshkore.com/agent/mainak-sen-proofrag-ai/.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.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/mainak-sen-proofrag-ai
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/mainak-sen-proofrag-ai/.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

llmragairetrievalgrounded-ai

Do you own proofrag-ai?

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.