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aovestdipaperino/tokensave

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Semantic Code Intelligence for AI Coding Agents

Overview

Semantic Code Intelligence for AI Coding Agents

README

Semantic Code Intelligence for AI Coding Agents

Fewer tokens • Fewer tool calls • 100% local


Why tokensave?

AI coding agents waste tokens exploring codebases. Every grep, glob, and file read costs money. On complex tasks, agents spawn multiple Explore sub-agents that scan hundreds of files just to build context.

tokensave gives agents a pre-indexed semantic knowledge graph. Instead of scanning files, the agent queries the graph and gets instant, structured answers – the right symbols, their relationships, and source code, in one call.

How It Works

flowchart TB
    subgraph agent["AI Coding Agent (Claude Code, Codex, Gemini, Cursor, ...)"]
        task["Implement user authentication"]
        first["Sub-agent"]
        second["Sub-agent"]
        task --> first
        task --> second
        first --- second
    end

    subgraph server["tokensave MCP Server"]
        search["Search: auth"]
        callers["Callers: login()"]
        context["Context for task"]
        db[("libSQL Graph DBInstant lookupsFTS5 search")]
        search --> db
        callers --> db
        context --> db
    end

    first --> search
    first --> callers
    second --> context

Without tokensave: Agents use grep, glob, and Read to scan files – many API calls, high token usage.

With tokensave: Agents query the graph via MCP tools – instant results, local processing, fewer tokens.


Key Features

Smart Context Building Semantic Search Impact Analysis
One tool call returns everything the agent needs – entry points, related symbols, and code snippets. Find code by meaning, not just text. Search for “authentication” and find login, validateToken, AuthService. Know exactly what breaks before you change it. Trace callers, callees, and the full impact radius of any symbol.
80+ MCP Tools 50+ Languages 12+ Agent Integrations
From call graph traversal to dead code detection, atomic edit primitives, code-health metrics, test mapping, and complexity analysis. Rust, Go, Java, Python, TypeScript, C, C++, Swift, Svelte, Astro, and 43 more including WGSL/HLSL/Metal shaders, CUDA/HIP, and Markdown. Three tiers (lite/medium/full) control binary size. Claude Code, Codex CLI, Gemini CLI, Qwen Code, Kiro, Cursor, OpenCode, Copilot, Cline, Roo Code, Zed, Antigravity, Kilo CLI, Kimi CLI, Mistral Vibe, Grok Build, Factory Droid, OMP, Pi, Plank.
Multi-Branch Indexing (opt-in) 100% Local Always Fresh
Optional per-branch databases. Cross-branch diff and search without switching your checkout. No data leaves your machine. No API keys. No external services. Everything runs on a local libSQL database. On-demand staleness check on every MCP call (30 s cooldown) plus catch-up sync when the server connects. Multi-agent work is expected to use git worktrees — each agent gets its own checkout and the index diverges are merged by git, not by a file watcher.
Subprocess-Isolated Extraction Code-Health Analytics Atomic Edit Primitives
A native crash in any tree-sitter grammar (abort, segfault, anything) kills only the worker; the pool respawns it and sync continues. Sync never dies on a malformed file. Composite health score (0-10000), Gini inequality, file-DAG depth, design-structure matrix, risk-weighted test gaps, and session deltas. Edit files without regex or shell-quoting hazards: unique-anchor str_replace, atomic multi-replace, AST-rewrite, anchored insert. Auto re-indexes after writes.

Quick Start

1. Install

Choose one installation method:

Platform Command
Any platform (Cargo) cargo install tokensaveor, with cargo-binstall, cargo binstall tokensave
macOS (Homebrew) brew install aovestdipaperino/tap/tokensave
Windows (Scoop) scoop bucket add tokensave https://github.com/aovestdipaperino/scoop-bucket``scoop install tokensave

You can also download a prebuilt binary and add it to your PATH.

To build unreleased code from the upstream master branch, see Installing from upstream master.

2. Configure your agent

Run the setup command to auto-detect your installed agents:

tokensave install

To choose an agent, use --agent (for example, codex, claude, or cursor):

tokensave install --agent codex

Setup registers the MCP server and the agent’s integration for Claude Code, Codex CLI, Gemini CLI, Cursor, Copilot, Kiro, Pi, Zed, and more than a dozen other agents. It also offers global Git hooks to keep initialized projects up to date. You can safely run setup again after upgrading. See Agent Integrations for project-local installs, several agents at once, and what setup writes for each agent.

3. Index your project

cd /path/to/your/project
tokensave init

This creates a .tokensave/ directory with the knowledge graph database. A repository you create with git init is initialized automatically on its first commit or agent session (auto_init, on by default). After that, tokensave sync updates the index incrementally, and a connected agent keeps it fresh automatically. Commands work from any subdirectory of the project. See Indexing and Freshness for details.


Documentation

The full documentation lives in docs/guide/ and is mirrored to the GitHub Wiki.

Topic What it covers
Installation and Upgrades Language tiers, self-upgrade and channels, versioning, building from source
Agent Integrations Supported agents, project-local setup, what install writes
Indexing and Freshness Project discovery, index freshness, crash-resilient sync, custom extensions
MCP Tools The 80+ tools by category, cross-project queries, MCP resources
Multi-Branch Indexing Per-branch graphs, automatic tracking, branch quality regressions
Token Tracking and Cost Savings ledger, cost reports, live monitor, memory diagnostics
Performance Profiling Opt-in latency attribution for database operations, MCP tool phases and indexing
CLI Reference Every command at a glance
Supported Languages 50+ languages and their feature tiers
Network Calls and Privacy What leaves your machine and how to opt out
Troubleshooting tokensave doctor and common problems
Benchmarks Retrieval-savings and performance benchmarks
Comparisons tokensave compared with CodeGraph and alternatives

The long-form User Guide walks through everyday use in more depth. To contribute, see CONTRIBUTING.md.


Origin

This project is a Rust port of the original CodeGraph TypeScript implementation by @colbymchenry. The port maintains the same architecture and MCP tool interface while leveraging Rust for performance and native tree-sitter bindings.


Building

To build from source, see Building from source and CONTRIBUTING.md.

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License

MIT License – see LICENSE for details.

tokensave.dev

View the full README on GitHub

Install

This server does not publish a one-line install command.

Open the repository installation guide New to MCP? Start with the mcpskill.org guide →