Code Graph Navigator

Stop grepping blind. Query your code graph.

Pre-computed symbols, calls, imports queried in microseconds.
Single binary. No Python, No Docker.

⚡ 8μs
query latency*
🎯 97%
symbol recall*
🌐 10
languages supported
🔒 100%
local — your code stays private

* Measured across 13 scenarios, 5 languages. Latency is the outline-query median on the Python fixture; 97% recall requires a matching language server on PATH (heuristic-only resolution lands around 25–37%). Benchmark suite →

Cartog demo
Animated demo: cartog init, index, map, search, refs, impact in a terminal
Quick Install
macOS / Linux curl -fsSL https://jrollin.github.io/cartog/install.sh | sh
Claude Code plugin /plugin marketplace add jrollin/cartog

More install options ↓

Why Cartog ↓ Agents ↓
How it works

Two commands to get started.

cartog init scaffolds .cartog.toml. cartog index builds the graph. Want MCP in your editor? Add cartog ide. Idempotent, skippable.

your-repo
$ cartog init + .cartog.toml: created from template Next steps: 1. Edit .cartog.toml if you want to change defaults (DB path, embedding provider). 2. Run `cartog index` to build the code graph. $ cartog index Indexed 142 files (0 unchanged), 3891 symbols, 8217 edges in 95ms # Optional — wire cartog into your editor for AI agents $ cartog ide --scope project + cursor (project, .cursor/mcp.json): created + vscode (project, .vscode/mcp.json): created

⚙️ cartog init

Drops a commented .cartog.toml template. Config only — re-runs are a no-op, your toml is never overwritten.

📚 cartog index

tree-sitter parses 10 languages into a local SQLite file. Incremental on re-runs; only changed files re-parse. Pair with cartog watch for auto-refresh.

🛠️ cartog ide (optional)

Skip this if you only use the CLI. Need MCP in Claude Code, Cursor, VS Code, Codex CLI, Gemini CLI, OpenCode, Windsurf, Zed, or Claude Desktop? Run it once per machine.

CLI-only users stop at step 2. The third verb is purely for plugging cartog into MCP-aware editors.

🩺 cartog doctor — health check

Run it after install or when something looks off. Reports git, config, database, and model status.

cartog doctor
$ cartog doctor [+] git: git repository at /your/repo [+] config: loaded from .cartog.toml [+] database: 142 files, 3891 symbols [+] embedding: local model cached [+] reranker: local model cached All 5 checks passed
Features

Navigate your codebase, not file contents.

Single binary, zero config, zero dependencies.

⚡ Zero dependencies

Single binary + SQLite file. No Docker, no language servers required, no graph databases. cargo install and you're done.

🔄 Live index

cartog watch auto re-indexes on file changes. Debounced, incremental, near-instant. Always query fresh data.

🔍 Dual search

Keyword search (sub-ms, symbol names) + semantic search (natural language). Local embeddings with optional GPU acceleration via Ollama.

🎯 Impact analysis

cartog impact --depth 3 traces callers-of-callers instantly. Know the blast radius before you change anything.

🔬 LSP precision, built in

Auto-detects language servers on PATH. Boosts edge resolution from ~25% to ~44–81%. Works without them, better with them.

🔒 100% local

tree-sitter parsing, SQLite storage, local embeddings. No API keys, no telemetry. Works in air-gapped environments.

Languages

10 languages supported — more coming

Python TypeScript JavaScript Rust Go Ruby Java PHP Dart Markdown
Why Cartog

Code is a graph. Query it like one.

Pre-compute the structure once, then answer any question in microseconds.

01

Grep can't trace what breaks

Transitive impact analysis is impossible with grep. cartog impact --depth 3 traces callers-of-callers instantly. Know the blast radius before you change anything.

02

Structured answers, not file dumps

One refs call returns every caller, importer, and type reference — with file paths and line numbers. No parsing output, no false positives.

03

Your code stays on your machine

tree-sitter parsing, SQLite storage, local embeddings. No API keys, no telemetry, no cloud. Works in air-gapped environments.

grep / cat / find Language server (LSP) Cartog
Transitive analysis impossible limited impact --depth 3
Query latency multi-step seconds 8-450 μs
Setup none per-language server single binary
Startup time instant seconds to minutes instant
Language coverage any 1 per server 10 languages
Semantic search no no local ONNX / Ollama
Privacy local local 100% local

Measured across 13 scenarios, 5 languages. Benchmark suite →

Alternatives

Why not...

01

grep / ripgrep

Great for string literals and config values. But grep can't trace call chains, can't do transitive impact analysis, and floods your context with raw text. Cartog returns structured, ranked, deduplicated results — one refs call replaces 6+ discovery steps.

02

A language server

LSPs give perfect precision but require per-language setup, take seconds to start, and only cover one language at a time. Cartog covers 9 languages with one binary and answers in microseconds. When you need LSP precision, cartog uses it as an optional layer.

03

Python-based graph tools

They solve a similar problem but require a Python runtime, pip dependencies, and virtual environments. Cartog is a single static binary — download and run. It also queries 10-100x faster thanks to compiled Rust + SQLite.

LLM Agents

Supercharge your AI coding agent

83% fewer tokens per query, 97% recall*. Your agent queries the graph instead of grepping blind.

Wires into your editor with cartog ide

Claude Code Cursor VS Code Claude Desktop Codex CLI Gemini CLI OpenCode Windsurf Zed

Claude Code, Cursor, and VS Code get project-scoped MCP files in your repo; the rest get user-scope configs in your home directory. Only editors actually installed are touched.

01

One command to wire it in

cartog ide writes cartog serve into installed editors (Cursor, VS Code, Codex CLI, Gemini CLI, OpenCode, Windsurf, Zed, Claude Desktop). Idempotent merge — existing MCP servers are preserved. Skip it if you only use the CLI.

02

13 MCP tools

cartog serve exposes cartog_map, cartog_search, cartog_refs, cartog_impact, cartog_rag_search, and 8 more. Each tool description tells the agent when (and when not) to use it.

03

Agent skill

The bundled skill teaches your agent when and how to use cartog — search routing, refactoring workflows, fallback heuristics — so it picks the right tool first.

Integration Setup What it does
CLI bootstrap cartog init + cartog index Scaffold .cartog.toml, then build the graph. CLI-only flow.
Editor MCP wiring (optional) cartog ide [--client X] 9 clients across 5 config shapes (incl. Codex TOML); idempotent, dry-run-able
Claude Code plugin /plugin marketplace add jrollin/cartog
/plugin install cartog@cartog-plugins		 Skill + MCP + auto-setup, all-in-one
MCP server (manual) cartog serve --watch --rag 13 tools over stdio, live index + semantic search
Agent skill npx skills add jrollin/cartog Behavioral rules for any compatible agent
CLI (any agent with bash) cargo install cartog Direct commands — works with any tool-using LLM

See MCP Server docs and Agent Skill docs for per-client setup. Supported clients: Claude Code (project + user), Claude Desktop, Codex CLI, Cursor, Gemini CLI, OpenCode, VS Code, Windsurf, Zed.

Install

Get started in seconds

Pick one install method below — these are alternatives, not steps. Once cartog is on your PATH, run cartog init + cartog index in any repo.

① Install script — macOS / Linux, no Rust required

curl -fsSL https://jrollin.github.io/cartog/install.sh | sh

Detects your OS + architecture, downloads the matching binary from the latest GitHub Release, verifies its SHA-256, and installs to /usr/local/bin (or ~/.local/bin if non-root). Override the target with CARTOG_INSTALL_DIR, pin a version with CARTOG_VERSION. Audit the script: scripts/install.sh.

② From crates.io — Rust toolchain required

cargo install cartog                              # default: LSP + S3 sync + Ollama
cargo install cartog --no-default-features        # minimal: drops LSP, S3, Ollama
cargo install cartog --no-default-features --features lsp  # LSP only

LSP, S3 index sync, and the Ollama provider are all enabled by default. Local ONNX stays the default embedding provider; set provider = "ollama" in .cartog.toml to use Ollama. Disable LSP at runtime with --no-lsp, or strip features at build time with --no-default-features.

③ Pre-built binaries — manual download

# macOS (Apple Silicon)
curl -L https://github.com/jrollin/cartog/releases/latest/download/cartog-aarch64-apple-darwin.tar.gz | tar xz
sudo mv cartog /usr/local/bin/

# Linux (x86_64)
curl -L https://github.com/jrollin/cartog/releases/latest/download/cartog-x86_64-unknown-linux-gnu.tar.gz | tar xz
sudo mv cartog /usr/local/bin/

All four targets + SHA256SUMS on GitHub Releases (macOS arm64, Linux arm64/x86_64, Windows x86_64).

Already in Claude Code? /plugin marketplace add jrollin/cartog bundles install + skill + MCP. Use any agent? npx skills add jrollin/cartog adds the behavioural skill alongside any install method above.

Start mapping your codebase

Open source, free forever. One command to install, one to wire it up.

curl -fsSL https://jrollin.github.io/cartog/install.sh | sh

Then cartog init + cartog index in your repo. Read the documentation →