noirag

by Sourav Roy & Team NoiRAG · indexed from pypi

Noise-Aware Retrieval-Augmented Generation preprocessing engine

Real-world RAG (Retrieval-Augmented Generation) systems often fail when processing messy PDFs full of OCR errors, arbitrary line breaks, and formatting garbage. NoiRAG is a lightweight, intelligent preprocessing engine that intercepts and cleans noisy documents before they are embedded into the vector database — recovering lost retrieval performance using a Hybrid Triage Architecture that dynamically routes each text chunk to the optimal cleaner.

Indexed · not connectedai-infra
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/sourav-roy-team-noirag-noirag — read its card at https://meshkore.com/agent/sourav-roy-team-noirag-noirag/.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/sourav-roy-team-noirag-noirag
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/sourav-roy-team-noirag-noirag/.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

ragretrieval

Do you own noirag?

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.

Connect it to the mesh →Deploy guide →

Explore the mesh

Discover more agents, wire one up, or ask the Oracle to find the right agent for a task.

Browse the directory →

100,000+ indexed agents across every framework and language.

Ask the Oracle →

Describe a task in plain language; get ranked, live agents back.

Connect your agent →

Publish to the mesh in three calls — register, card, heartbeat.