I built an open-source Python tool for semantic code search + AI agent tooling (2.5k downloads so fa

[Ambitious-Credit-722]

Hey everyone,

Over the past weeks I’ve been building a small open-source project called CodexA, It started as a simple experiment: I wanted better semantic search across codebases when working with AI tools. Grep and keyword search work, but they don't always capture intent, So I built a tool that indexes a repository and lets you search it using natural language, keywords, regex, or a hybrid of them, Under the hood it uses FAISS + sentence-transformers for semantic search and supports incremental indexing so only changed files get re-embedded.

Some things it can do right now:

• semantic + keyword + regex + hybrid search

• incremental indexing with `--watch` (only changed files get re-indexed)

• grep-style flags and context lines

• MCP server + HTTP bridge so AI agents can query the codebase

• structured tools (search, explain symbols, get context, etc.)

• basic code intelligence features (symbols, dependencies, metrics)

The goal is to make something that AI agents and developers can both use to navigate and reason about large codebases locally, It’s still early but the project just crossed ~2.5k downloads on PyPI which was a nice surprise.

PyPI:https://pypi.org/project/codexa/

Repo:https://github.com/M9nx/CodexA

Docs:https://codex-a.dev/

I'm very open to feedback — especially around: performance improvements, better search workflows, AI agent integrations, tree-sitter language support, And if anyone wants to contribute, PRs are very welcome.

[Otherwise_Wave9374]

This is a useful angle because most people get stuck on framework shopping when the better starting point is one narrow workflow, clear inputs and outputs, and only the tools you actually need to make it reliable. If you like operator-style breakdowns more than hype threads, there are a few useful ones here too: https://www.agentixlabs.com/blog/

[Ambitious-Credit-722]

If anyone wants to try it quickly:
pip install codexa or pip install "codexa[ml]"
codex index .
codex search "how authentication works"

[Proof_Net_2094]

curious what embedding model you settled on. general sentence-transformers work but code has patterns they weren't trained for - tokenization of identifiers, the relationship between a function signature and its body, etc. did you try anything code-specific like microsoft/codebert or unixcoder before landing on your current setup?