AI/TLDR

CodeGraph

A local code knowledge graph that answers an agent's question in one tool call

Code Indexing & SearchOpen source
Latest
0.7.10
Updated
19 May 2026
License
MIT
Coverage
1 story

What's new

0.7.1019 May 2026

CodeGraph trended on GitHub with a local SQLite plus tree-sitter knowledge graph exposed over MCP, reported to cut Claude Code, Codex and Cursor codebase-exploration tool calls by 94%.

Latest news

Overview

CodeGraph pre-indexes a codebase into a knowledge graph so a coding agent can ask one question instead of running a dozen greps. A single MCP tool call returns the verbatim source of the symbols involved, the call paths through them, and the blast radius of a change — the context an agent would otherwise assemble by reading files one at a time.

The indexer is a native Rust kernel that parses source with tree-sitter, extracting nodes (functions, classes) and edges (calls, imports), then resolves references: calls to definitions, imports to their sources, inheritance chains. Everything lands in a local SQLite database with FTS5 full-text search, and a file watcher on native OS events keeps the graph in sync as you edit. Nothing leaves the machine — there is no external service in the path.

It understands more than plain call graphs: it recognises routing patterns across 17 web frameworks, and bridges cross-language boundaries such as Swift↔Objective-C, the React Native bridge and Expo Modules. A browser viewer renders the graph interactively — callers, source, callees and entry points — which is also the quickest way to sanity-check what the agent is being told.

What it does

  • Rust tree-sitter kernel indexing 30+ languages, from TypeScript, Python, Go and Rust to Swift, Kotlin, Solidity and Terraform
  • One MCP call returns verbatim source, call flow and blast-radius impact instead of a grep-and-read loop
  • Local SQLite storage with FTS5 full-text symbol search — no external service, fully offline
  • File watcher on native OS events auto-syncs the graph after a debounce as you code
  • Reference resolution: calls to definitions, imports to sources, inheritance chains
  • Framework-aware route detection across 17 web frameworks, plus Swift↔Objective-C and React Native bridging
  • Installer auto-detects agents — Claude Code, Cursor, Codex CLI, opencode, Gemini CLI, Antigravity, Kiro, GitHub Copilot and Hermes Agent
  • Browser viewer showing callers, source, callees and entry points

Getting started

Install the binary, let the installer configure your agents, then build the index once per repository.

Install without Node

A shell installer for macOS and Linux, or PowerShell on Windows.

bashbash
curl -fsSL https://raw.githubusercontent.com/colbymchenry/codegraph/main/install.sh | sh

# Windows (PowerShell)
irm https://raw.githubusercontent.com/colbymchenry/codegraph/main/install.ps1 | iex

Or install with npm

If you already have Node on the machine.

bashbash
npm i -g @colbymchenry/codegraph

Wire it into your agents and index the repo

`codegraph install` detects and configures supported agents; `codegraph init` builds the index once per repository; `codegraph ui` opens the browser viewer.

bashbash
codegraph install
codegraph init
codegraph ui

Let the watcher keep it fresh

After `init`, the file watcher tracks the project with native OS events and syncs changes after a short debounce, so you do not re-index by hand as you work.

Commands and code are distilled from the project's own documentation — always check the official repo for the latest.

When to use it

  • Cut the exploration tool calls a coding agent makes on a large repository by giving it symbols and call paths directly
  • Ask what a change would break before making it, using blast-radius impact analysis
  • Keep code context fully local — the index is SQLite on disk, with no external service in the path
  • Trace a request across a language boundary in a mobile codebase, such as Swift to Objective-C or a React Native bridge

How CodeGraph compares

CodeGraph alongside other open-source code indexing & search tools AI/TLDR tracks, ranked by GitHub stars.

ToolStarsWhat it does
CodeGraph★ 70.4kA local code knowledge graph that answers an agent's question in one tool call
GitNexus★ 47.2kIndexes a codebase into a knowledge graph of dependencies, call chains and execution flows, then exposes it to Claude Code, Cursor and Codex through MCP tools.
Claude Context★ 12.5kAn MCP server that indexes your codebase into a vector database so AI coding agents can find relevant code by meaning instead of loading whole folders.
Semble★ 6kA CPU-only code search library and MCP server that indexes a repository with tree-sitter chunking, Model2Vec embeddings and BM25, so an agent retrieves the few relevant snippets instead of grepping and reading whole files.