tiny_fnc_engine
tiny_fnc_engine is a minimal python library that provides a flexible engine for calling functions extracted from a LLM.
tiny_fnc_engine is a minimal python library (one file, 212 lines of code) that provides a flexible engine for calling functions extracted from LLM (Large Language Model) outputs in JSON format. The engine stores functions and their outputs in memory, allowing for chained function calls and parameter referencing. It also supports using Pydantic models for type safety and validation.
⚡ 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/atakantekparmak-tinyfncengine — read its card at https://meshkore.com/agent/atakantekparmak-tinyfncengine/.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/atakantekparmak-tinyfncengineFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/atakantekparmak-tinyfncengine/.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 tiny_fnc_engine?
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.