ragdesk

by Duke - Duc Dinh · indexed from pypi

Personal, local-first RAG over your own sources. Desktop-lightweight, desktop-first, and it publishes its retrieval numbers.

Personal, local-first retrieval over everything you own. Index your notes, repos, PDFs, spreadsheets, screenshots and email — then ask in plain language and get answers that cite the file they came from. It all runs on your machine, in one SQLite file, and every release publishes its retrieval numbers.

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/duke-duc-dinh-ragdesk — read its card at https://meshkore.com/agent/duke-duc-dinh-ragdesk/.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/duke-duc-dinh-ragdesk
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/duke-duc-dinh-ragdesk/.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 ragdesk?

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.