Finance-Policy-RAG-Agent
A 24/7 automated RAG agent for answering finance policy questions. Features an n8n no-code pipeline and a Python shadow layer with FastAPI and Streamlit.
Finance teams in mid-size companies spend ~15% of their time answering repetitive policy questions ("how many days to file a reimbursement?", "what's the travel advance limit?"). This bot eliminates that by providing a 24/7 automated Telegram interface that answers policy questions using a Retrieval-Augmented Generation (RAG) pipeline. It logs every Q&A to a compliance spreadsheet and automatically escalates unknown queries via email to the finance team.
⚡ 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/toxicbishop-finance-policy-rag-agent — read its card at https://meshkore.com/agent/toxicbishop-finance-policy-rag-agent/.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/toxicbishop-finance-policy-rag-agentFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/toxicbishop-finance-policy-rag-agent/.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 Finance-Policy-RAG-Agent?
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.