codegraph

Give your AI the map before it starts exploring.

The Problem · What It Does · Quick Start · Commands · Languages · AI Integration · How It Works · Practices · Roadmap

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The Problem

AI agents face an impossible trade-off. They either spend thousands of tokens reading files to understand a codebase's structure — blowing up their context window until quality degrades — or they assume how things work, and the assumptions are often wrong. Either way, things break. The larger the codebase, the worse it gets.

An agent modifies a function without knowing 9 files import it. It misreads what a helper does and builds logic on top of that misunderstanding. It leaves dead code behind after a refactor. The PR gets opened, and your reviewer — human or automated — flags the same structural issues again and again: "this breaks 14 callers," "that function already exists," "this export is now dead." If the reviewer catches it, that's multiple rounds of back-and-forth. If they don't, it can ship to production. Multiply that by every PR, every developer, every repo.

The information to prevent these issues exists — it's in the code itself. But without a structured map, agents lack the context to get it right consistently, reviewers waste cycles on preventable issues, and architecture degrades one unreviewed change at a time.

What Codegraph Does

Codegraph builds a function-level dependency graph of your entire codebase — every function, every caller, every dependency — and keeps it current with sub-second incremental rebuilds.

It parses your code with tree-sitter (native Rust or WASM), stores the graph in SQLite, and exposes it where it matters most:

• MCP server — AI agents query the graph directly through 34 tools — one call instead of dozens of grep/find/cat invocations
• CLI — developers and agents explore, query, and audit code from the terminal
• CI gates — check and manifesto commands enforce quality thresholds with exit codes
• Programmatic API — embed codegraph in your own tools via npm install

Instead of an agent editing code without structural context and letting reviewers catch the fallout, it knows "this function has 14 callers across 9 files" before it touches anything. Dead exports, circular dependencies, and boundary violations surface during development — not during review. The result: PRs that need fewer review rounds.