Tokensave
The most comprehensive code intelligence MCP server for AI coding agents. 40+ tools, 30+ languages, 9 agent integrations. Pre-indexed semantic knowledge graphs for instant code understanding — fewer tokens, fewer tool calls, 100% local.
What is Tokensave?
Tokensave is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to most comprehensive code intelligence mcp server for ai coding agents. 40+ tools, 30+ languages, 9 agent integrations. pre-indexed semantic knowledge graphs for instant code understanding — fewer token...
The most comprehensive code intelligence MCP server for AI coding agents. 40+ tools, 30+ languages, 9 agent integrations. Pre-indexed semantic knowledge graphs for instant code understanding — fewer tokens, fewer tool calls, 100% local.
This server falls under the Coding Agents and Developer Tools categories on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- The most comprehensive code intelligence MCP server for AI c
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx tokensaveConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use Tokensave
Tokensave is a Rust-based MCP server that builds a pre-indexed semantic knowledge graph of your codebase using a local libSQL database, so AI coding agents can query symbols, call graphs, and code relationships instead of repeatedly reading files with grep and glob. It exposes 80+ MCP tools covering semantic search, call graph traversal, dead code detection, atomic edit primitives, and code health metrics across 50+ programming languages including Rust, Go, Java, Python, TypeScript, C/C++, Swift, and shader languages. With support for 12+ agent integrations — Claude Code, Codex, Gemini CLI, Cursor, Copilot, Cline, and more — it is designed to dramatically reduce token consumption on complex coding tasks while running entirely locally with no external API calls.
Prerequisites
- Rust 1.70+ if installing via cargo (or use Homebrew/Scoop/prebuilt binary)
- macOS, Linux (x86_64 or ARM64), or Windows
- At least one supported AI coding agent: Claude Code, Cursor, Gemini CLI, Codex CLI, GitHub Copilot, or similar
- A codebase to index (any language supported in the lite/medium/full tier)
Install tokensave for your platform
Choose the installation method for your OS. Homebrew is recommended on macOS, Scoop on Windows, and cargo on any platform. Prebuilt binaries are also available on the GitHub releases page.
# macOS (Homebrew)
brew install aovestdipaperino/tap/tokensave
# Windows (Scoop)
scoop bucket add tokensave https://github.com/aovestdipaperino/scoop-bucket
scoop install tokensave
# Any platform (cargo - full tier with 50+ languages)
cargo install tokensave
# Minimal binary (lite tier)
cargo install tokensave --no-default-featuresRegister tokensave with your AI coding agent
Run tokensave install to auto-detect installed agents and register the MCP server. Pass --agent to target a specific agent. For Claude Code, this also installs PreToolUse hooks that block wasteful Explore sub-agents.
# Auto-detect all installed agents
tokensave install
# Target a specific agent
tokensave install --agent claude # Claude Code
tokensave install --agent cursor # Cursor
tokensave install --agent gemini # Gemini CLI
tokensave install --agent codex # OpenAI Codex CLI
tokensave install --agent copilot # GitHub CopilotIndex your project
Navigate to your project root and run tokensave init. This builds the local libSQL knowledge graph from your source files. The index stays fresh automatically via a post-commit hook and on-demand sync.
cd /path/to/your/project
tokensave initVerify the index and check token savings
Use the CLI to confirm the index is up to date and view a savings dashboard showing how many tokens and tool calls tokensave has saved versus raw file scanning.
# Check index status
tokensave status
# View token savings dashboard
tokensave dashboard
# View cumulative savings across sessions
tokensave savings --allSearch your codebase from the CLI
Use tokensave search to run a semantic query directly from the terminal, validating that the index works before involving an AI agent.
tokensave search "authentication flow"Tokensave Examples
Client configuration
After running tokensave install --agent claude, the MCP config is written automatically. The equivalent manual config for Claude Code's .mcp.json looks like this:
{
"mcpServers": {
"tokensave": {
"command": "tokensave",
"args": ["serve"]
}
}
}Prompts to try
Once tokensave is indexed and registered, AI agents use the MCP tools automatically. You can also ask the agent directly.
- "Find all callers of the authenticate() function in this codebase"
- "Show me the full call graph for the payment processing module"
- "What functions are dead code in the src/utils directory?"
- "Search for all code related to rate limiting and return the relevant symbols"
- "What is the code health score for this project and where are the riskiest files?"Troubleshooting Tokensave
tokensave init completes but the agent still reads files with grep/glob
Ensure tokensave install was run for your specific agent after init. For Claude Code, verify the PreToolUse hook is installed by checking CLAUDE.md in the project root for tokensave instructions.
cargo install fails with compilation errors
tokensave requires Rust 1.70+. Run rustup update stable to update your toolchain. If you want to avoid compiling, use the prebuilt binary from the GitHub releases page or Homebrew.
Index becomes stale after many file changes
Run tokensave init again to trigger a full re-index, or call the reindex MCP tool from your agent. Install the global git post-commit hook with tokensave install --git-hook yes to keep the index automatically fresh after every commit.
Frequently Asked Questions about Tokensave
What is Tokensave?
Tokensave is a Model Context Protocol (MCP) server that most comprehensive code intelligence mcp server for ai coding agents. 40+ tools, 30+ languages, 9 agent integrations. pre-indexed semantic knowledge graphs for instant code understanding — fewer tokens, fewer tool calls, 100% local. It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Tokensave?
Follow the installation instructions on the Tokensave GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with Tokensave?
Tokensave works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Tokensave free to use?
Yes, Tokensave is open source and available under the MIT License license. You can use it freely in both personal and commercial projects.
Tokensave Alternatives — Similar Coding Agents Servers
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Browse More Coding Agents MCP Servers
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Set Up Tokensave in Your Editor
Choose your AI client for step-by-step setup instructions.
Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
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