ChunkHound’s goal is simple: local-first codebase intelligence that helps you pull deep, core-dev-level insights on demand, generate always-up-to-date docs, and scale from small repos to enterprise monorepos — while staying free + open source and provider-agnostic (VoyageAI / OpenAI / Qwen3, Anthropic / OpenAI / Gemini / Grok, and more).

I’d love your feedback — and if you have, thank you for being part of the journey!

A few years ago I set out to refactor some of my team's code that I wasn't particularly familiar with, but we wanted to modularize and re-use in more places. The primary file alone was 18k+ lines of Typescript that was a terrible mess of spaghetti. Most of it had been written in JavaScript but later converted haphazardly. I ended up writing myself a little app that used the Typescript compiler APIs to help me just explore all the many branches of the code and annotate how I would refactor different parts. It helped a bit, but I never got time to add some of the more intelligent features I wanted like finding every execution path between two points.

I have been working on depgraph (https://github.com/henryhale/depgraph) for a while now. It is truly local with several output options(json, mermaid, jsoncanvas). Mutliple languages are supported (js, go, c) - expanding the list slowly but sure.

Will try this out. Was always envious of how Augment was able to do this. Kudos.

you say "local-first" but have placed voyage API for embeddings as the default (had to go to the website and dig to find that you can infact use local embedding models). Please fix

Perhaps I am missing something, but this seems to require a Lemon (LLM)? Is the idea that the Lemon is used to help build an index AOT that can be queried locally, after?

I want to figure out how to build advanced tools, potentially by leveraging Lemons to iterate quickly, that allow us all to rely _less_ on Lemons, but still get 10,20,30x efficiency gains when building software, without needing to battle the ethics of it all.

I have chunckhound is a few projects and it’s noted in both the agent md file as well as mcp and claude never uses it. Ever. Never once.

Is there a prompt special sauce y’all use to get it to use it?

Might give this a try to experiment if it's really free to use (I'll have to read up on that I guess). The qemu codebase is huge and every contributer seems to solve problems in slightly different ways. Would be nice if this tool could help distill it.

Is there a way to have the model inside of codex to make use of chunkhound instead of its “built in” search/explore functionality with rg? Whenever I spin up a new agent using xhigh thinking it spins its wheels for a while to get up to speed — wondering if chunkhound can make this process faster.

Looks like the tutorial link is broken.

Can you please expose the functionality as a self-documenting CLI command with machine readable output? (Or did I misunderstand that MCP isn't the only way to use it?)

I am curious to try it but do not want to adopt MCP servers.

Telling Claude to call the CLI tool is more efficient.