u/OwnEntrepreneur256

Hi folks – I’ve been working on an open-source project called \*\*spy-code\*\* that turns a codebase into a queryable graph for AI coding agents and developer tools.

The idea is to give agents a structured view of a repository rather than just a pile of files. Spy-code parses your source with \[tree-sitter\](https://tree-sitter.github.io/), extracts functions, classes and constants as nodes, maps calls, imports and references as edges, and stores the graph locally in a SQLite database. You can then query it via a CLI, a GraphQL API or an MCP server.

This lets agents (or humans) ask targeted questions like:

\- What calls this function?

\- Where is authentication implemented?

\- What changed since a given git ref?

\- What depends on this class?

It’s local-first (no remote indexing) and language-aware. I’m starting with Rust support first; Python, TypeScript/JavaScript and Go are on the roadmap.

I’m looking for feedback from people building local LLM agents or working with large repos. Does this seem useful? What graph queries would you want against your codebase? Is GraphQL overkill, or would a simpler API suffice? What languages should be prioritised next?

Repo (MIT licensed) is here: [Spy-code

Would love to hear your thoughts – thanks!

Hi folks – I’ve been working on an open-source project called \*\*spy-code\*\* that turns a codebase into a queryable graph for AI coding agents and developer tools.

The idea is to give agents a structured view of a repository rather than just a pile of files. Spy-code parses your source with \[tree-sitter\](https://tree-sitter.github.io/), extracts functions, classes and constants as nodes, maps calls, imports and references as edges, and stores the graph locally in a SQLite database. You can then query it via a CLI, a GraphQL API or an MCP server.

This lets agents (or humans) ask targeted questions like:

\- What calls this function?

\- Where is authentication implemented?

\- What changed since a given git ref?

\- What depends on this class?

It’s local-first (no remote indexing) and language-aware. I’m starting with Rust support first; Python, TypeScript/JavaScript and Go are on the roadmap.

I’m looking for feedback from people building local LLM agents or working with large repos. Does this seem useful? What graph queries would you want against your codebase? Is GraphQL overkill, or would a simpler API suffice? What languages should be prioritised next?

Repo (MIT licensed) is here: [https://github.com/psyborgs-git/spy-code\](https://github.com/psyborgs-git/spy-code)

Would love to hear your thoughts – thanks!

Hi everyone—I’m working on an open‑source tool called spy‑code that parses a repo with tree‑sitter, extracts functions, classes, constants and tracks calls, imports and references as edges, builds a local SQLite graph and exposes it via CLI / GraphQL / MCP. The goal is to give AI coding agents a structured map of the codebase rather than a bundle of files. It’s local‑first and currently targets Rust, Python, TypeScript/JS and Go.

What queries would you want against such a graph? Do you prefer GraphQL or a simpler API?

I’ve omitted the link from this post to comply with rule 3; I’ll add it in the comments.

Why is it, that even after being one of the largest states with enormous population and abundant resources everything outside of Konkan region feels like a third world state?

So guys, I grew up in Gujarat and I’ve lived across multiple states in India, including Karnataka, Delhi n Maharashtra. To me these people just seem so weird, they hate capitalism, they hate rich people as if unka paisa khaa k betha ho, to me as a gujju this seems so weird like wtf guys. Are we different or they stupid ?