clojure-mcp

> By being particularly bad at anything outside of the most popular languages and frameworks, LLMs force you to pick a very mainstream stack if you want to be efficient. Do they? I’ve found Clojure-MCP[1] to be very useful. OTOH, I’m not attempting to replace myself, only augment myself. 1: https://github.com/bhauman/clojure-mcp

I wonder if common lisp with repl and debugger could provide a better tool than your example with nasm wrapped via apt in Docker... Essentially just giving LLMs more state of the art systems made for incremental development? Ed: looks like that sort of exists: https://github.com/bhauman/clojure-mcp (Would also be interesting if one could have a few LLMs working together on red/green TDD approach - have an orchestrator that parse requirements, and dispatch a red goblin to write a failing test; a green goblin that writes code until the test pass; and then some kind of hobgoblin to refactor code, keeping test(s) green - working with the orchestrator to "accept" a given feature as done and move on to the next... With any luck the resulting code might be a bit more transparent (stricter form) than other LLM code)?

> Because most of my day-to-day is in clojure I tend to use sonnet 4 to get the parens right. In case the author is lurking, you may want to apply the same fix they do in clojure-mcp: https://github.com/bhauman/clojure-mcp/blob/8150b855282babcd... The insight that team had was that LLMs get confused with parens, but they are excellent at indentation, so if you run parinfer over the LLMs output it will be correct in 99% of cases.

It appears to have support for Gemini and OpenAI, https://github.com/bhauman/clojure-mcp?tab=readme-ov-file#ll...