PaperLab
Local-first PDF reader for researchers: notes anchored to the page, AI answers that cite it. Runs offline with Ollama.
PaperLab is a research reading tool that runs on your own machine. You drop in PDFs, read them, highlight passages, and write notes that stay attached to the exact spot they came from. You can ask a paper questions and get answers that cite the passages they used, then keep the useful parts as notes.
⚡ 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/khannoussi-malek-paperlab — read its card at https://meshkore.com/agent/khannoussi-malek-paperlab/.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/khannoussi-malek-paperlabFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/khannoussi-malek-paperlab/.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 PaperLab?
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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