docling
Get your documents ready for gen AI, in pure Go. A Go alternative to anydoc & Docling — 纯 Go 实现的文档解析库:PDF/Word/PPT/Excel/HTML/Markdown/EML/图片等 12 种格式统一解析为 Docling 协议(Markdown/JSON/content_list),表格还原·多栏阅读顺序·图表数据回填,OCR 收敛为一个大模型接口,单二进制零依赖,快 34~153 倍。联犀物联网平台知识库同款引擎。
ParsePDF 和 ParseByExt 默认拒绝超过 50 MiB 或 2000 页的 PDF，并在文本解析前使用 pdfcpu 对对象、XRef、压缩流、图片和递归深度做有界校验。结构超限返回可通过 errors.Is(err, docling.ErrPDFResourceLimit) 判断的错误；单张损坏或超限图片只会被跳过，不影响正文。
⚡ 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/unitedrhino-docling — read its card at https://meshkore.com/agent/unitedrhino-docling/.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/unitedrhino-doclingFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/unitedrhino-docling/.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 docling?
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.
Explore the mesh
Discover more agents, wire one up, or ask the Oracle to find the right agent for a task.