eresende

eresende / pitlane-mcp

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Token-efficient code intelligence MCP server. Indexes a codebase once using tree-sitter AST parsing and lets AI agents retrieve exactly the symbols they need: instead of dumping entire files into context.

10
1
100% credibility
Found Mar 30, 2026 at 10 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Rust
AI Summary

Local tool that parses and indexes code symbols from Rust, Python, JavaScript/TypeScript, C, and C++ projects to enable efficient retrieval for AI coding assistants.

How It Works

1
🔍 Discover Pitlane

You hear about a smart helper that lets AI coding tools understand your project's code structure without reading entire files, saving time and effort.

2
📥 Get the Helper

You download the simple program and place it in a folder on your computer where you keep your tools.

3
🚀 Start the Service

You run the program once, and it quietly starts watching, ready to learn about your code.

4
🔗 Link to Your AI

You tell your favorite AI coding assistant to connect to this helper, like adding a new friend to the team.

5
📁 Teach It Your Project

You point the helper to your code folder, and in seconds it scans and remembers all the key parts like functions and classes.

6
🧠 AI Explores Smartly

Now your AI can quickly search for exactly the code pieces it needs, like looking up a recipe ingredient instead of the whole cookbook.

✅ Code Smarter, Faster

Your AI works efficiently with tiny bits of code, helping you build and fix things quicker without overload.

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Star Growth

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AI-Generated Review

What is pitlane-mcp?

Pitlane-mcp is a Rust-built MCP server that indexes your codebase once using tree-sitter AST parsing, letting AI agents retrieve exactly the symbols they need—instead of dumping entire files into context. It provides seven tools like index_project to build the index, search_symbols for queries, get_symbol for precise code snippets, and find_usages for references, all over disk-persisted data that loads in milliseconds. Supports Rust, Python, JS/TS, C/C++ with smart exclusions for deps and builds.

Why is it gaining traction?

It slashes token use dramatically—532x on Rust codebases like ripgrep, 133x on C like Redis—making agent prompts lean and cheap. Background watchers enable incremental updates without full re-indexes, and sub-millisecond queries beat dumping entire files every time. Fully local with no APIs, it fits agent workflows in Claude Code, OpenCode, or VS Code seamlessly.

Who should use this?

AI agent builders integrating code intelligence into tools like custom Claude setups or IDE plugins. Backend devs on Rust/Python/TS projects using agents for refactoring or navigation, tired of bloated contexts wasting tokens. Teams evaluating MCP for precise symbol lookups in monorepos.

Verdict

Worth trying for agent-driven code tasks if you're on supported languages—docs, benchmarks, and tests are solid despite 10 stars and 1.0% credibility signaling early maturity. Pair with agent instructions in CLAUDE.md for best results; scale cautiously on huge codebases.

(198 words)

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