Agent frameworks are solving the wrong problem

every agent framework is competing on how many abstractions they can stack. graphs, crews, nodes, edges, state machines. i just wanted to run an agent that calls my own python functions.

kanly is the opposite of a framework. you write plain python functions. you define an agent with one api call. you trigger runs from webhooks or cron or wherever. the llm loop runs on the server and your tools execute on your machine over websocket.

whatever you want to build you just write the handler functions for it. bug fixer, deploy bot, alert triage at 3am. kanly just runs the loop and calls your code.

the only real design decision was that the llm should never directly execute anything. every tool call goes through a runtime on your machine. cli commands can require human approval before running. credentials never leave your infra.

2k lines of python. mit licensed. works with any openai compatible model.