Token Optimizer MCP
T

Token Optimizer MCP

Token Optimizer MCP is an intelligent token optimization MCP server that can reduce context window usage by 60-90% through intelligent caching, compression, and tool replacement. It supports AI tools such as Claude Code and Claude Desktop.
2.5 points
10.2K

What is Token Optimizer MCP?

Token Optimizer MCP is an intelligent token optimization server designed specifically to reduce token consumption when AI assistants (such as Claude) process files, API requests, and database queries. By storing large content in an external SQLite database and providing a compressed version, it can significantly reduce context window occupancy, allowing you to process more content.

How to use Token Optimizer MCP?

With just one global installation, Token Optimizer MCP will automatically optimize all AI tool calls. It will intelligently replace standard file operation tools (such as Read, Grep, Glob) with optimized versions, using cached and compressed versions while maintaining full functionality. You can also directly call its optimization tools to process specific content.

Use Cases

Suitable for development workflows that need to process large codebases, frequently access the same APIs, perform database queries, or process a large number of log files. Particularly suitable for users of AI programming assistants such as Claude Code, Claude Desktop, Cursor, and Cline.

Main Features

Intelligent Tool Replacement
Automatically replace standard file operation tools (such as Read, Grep, Glob) with optimized versions, achieving a 60-90% token reduction.
Context Window Optimization
Store large content in an external SQLite database to free up context window space, allowing AI to process more information.
Efficient Compression
Use the Brotli compression algorithm with a typical compression ratio of 2-4 times and up to 82 times for repetitive content.
Persistent Cache
Cache in an SQLite database, persistently saved across sessions, and automatically clean old data older than 7 days.
Accurate Token Counting
Use tiktoken (GPT-4 tokenizer) to accurately calculate token usage and provide accurate savings statistics.
Global Hooks System
7-stage optimization process, automatically applied to all AI tool calls without manual intervention.
Multi-Tool Support
Supports 65 dedicated tools, covering file operations, API caching, database optimization, monitoring, etc.
Fully Offline Operation
Zero external dependencies, all operations are completed locally to protect data privacy.
Advantages
Significantly reduce costs: Reduce token usage by 60-90%, saving 300K-700K tokens (worth $0.90-$2.10) per session.
Improve performance: Increase operation speed by 80-90% when the cache hits, with a hook overhead of <10ms.
Easy to use: One installation, automatically optimize all operations without additional configuration.
Wide compatibility: Support mainstream AI tools such as Claude Code, Claude Desktop, Cursor, Cline, and GitHub Copilot.
Intelligent caching: Multi-level caching strategy, automatic pre-warming, and intelligent invalidation mechanism.
Detailed analysis: Provide session statistics, project analysis, and cost estimates.
Limitations
Limited optimization for small text: Most suitable for content over 500 characters, with relatively large cache overhead for small fragments.
No benefits for one-time content: Content that will not be referenced repeatedly cannot benefit from caching.
Slow initial loading: Need to establish cache and index for the first operation.
Storage space requirements: The cache database may grow and require regular cleaning.
Approximate token counting: Using the GPT-4 tokenizer, it is an approximation for Claude but close enough.

How to Use

Install Token Optimizer MCP
Install globally using npm. The installation script will automatically detect and configure all installed AI tools.
Verify Installation
Check if the global hooks are successfully installed and configured.
Start Using AI Tools
Use Claude Code, Claude Desktop, or other supported AI tools normally. Optimization will be automatic.
Monitor Optimization Results
Use built-in tools to view token savings and cache performance.

Usage Examples

Processing Large Codebases
When you need an AI assistant to analyze a large codebase, using intelligent file reading can significantly reduce token consumption.
Optimizing Frequent API Calls
When you need to frequently query the same API, using API requests with caching can avoid repeatedly transmitting the same data.
Caching Database Query Results
When an AI needs to perform complex database queries, it can cache the query results for subsequent analysis.
Token Analysis for Project Scope
Before starting a large project, analyze the token usage and optimization potential of the entire project first.

Frequently Asked Questions

What should I do if Claude Code shows an "Invalid Settings" error after installation?
Why is my cache hit rate very low (<50%)?
How much operation delay will Token Optimizer add?
How can I view the actual token savings?
How much disk space will the cache files occupy?
Which AI tools are supported?
How can I get help if I encounter problems?

Related Resources

Detailed Tool Documentation
Complete usage instructions and parameter details for 65 tools.
Installation Guide
Detailed installation steps and configuration instructions for each platform.
GitHub Repository
Source code, issue tracking, and contribution guidelines.
Model Context Protocol Official Website
Official documentation and specifications for the MCP protocol.
npm Package Page
npm package information and version history.

Installation

Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.

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