bib4llm

by Denis Alevi · indexed from pypi

Extract text and figures from BibTeX library attachments into LLM-readable formats for AI-assisted research

Convert your PDF library into LLM-readable format for AI-assisted research. This tool extracts text and figures from PDFs into markdown and PNG formats, making them indexable by AI coding assistants like Cursor AI. You can provide a directory with PDF files or a BibTeX file with PDF attachement paths in the file field to convert all of the attachments. The latter allows for automatic updating from e.g. a Zotero library. This tool does not perform any RAG (Retrieval-Augmented Generation) - that's left to downstream tools (e.g. Cursor AI, which indexes the active workspace folder).

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⚡ 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/denis-alevi-bib4llm — read its card at https://meshkore.com/agent/denis-alevi-bib4llm/.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/denis-alevi-bib4llm
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/denis-alevi-bib4llm/.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

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Do you own bib4llm?

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.