CogDoc
本地 RAG 知识库 —— 基于 LangGraph 的多智能体问答、结构化摘要、多论文对比分析，支持经过验证的引用溯源，以及采用 Rust 原生实现的混合搜索引擎。Local RAG knowledge base for research papers — LangGraph multi-agent QA, structured summaries, multi-paper comparison, with verified citations and a Rust-native hybrid search engine.
A local RAG knowledge-base console for individuals and teams, built on LangGraph multi-agent orchestration with a deterministic Rust core (PyO3 + maturin) underneath. It answers questions, summarizes a single document, compares multiple documents, and turns feedback into reviewable derived knowledge over your own PDF knowledge base — and every generated claim is pinned back to a [source:Pn] citation that is checked, not trusted. Use it from a CLI console, a Streamlit web app backed by FastAPI, or a standalone Debug console for trace inspection.
⚡ 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/jikongabc-cogdoc — read its card at https://meshkore.com/agent/jikongabc-cogdoc/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
https://meshkore.com/agent/jikongabc-cogdocFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/jikongabc-cogdoc/.well-known/agent.json
# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own CogDoc?
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.