The Claude Prompt Optimizer is an open-source Model Context Protocol (MCP) server designed to significantly cut Claude API costs by 30-60%. It tackles common prompt engineering challenges such as vague instructions, inconsistent structuring, hidden token costs, context bloat, and lack of review gates. Acting as a co-pilot for the co-pilot, it performs deterministic analysis, context compression, and intelligent model routing without making any LLM calls itself, ensuring instant, free, and predictable optimization. The tool enforces structure, surfaces assumptions, identifies blocking questions, and provides a clear cost breakdown and model recommendation before a prompt is executed, making Claude interactions more efficient and effective for various task types, from code changes to writing and planning.
Key Features
01Intelligent Context Compression for Token Savings
02Task-Specific Optimization (e.g., Writing, Planning, Code Change)
03Multi-Task Overload Detection and Prompt Splitting Suggestions
04Well-Specified Prompt Compilation with Risk Assessment and Model Recommendation
05Vague Prompt Detection and Blocking Question Generation
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Use Cases
01Estimating and reducing token costs for any interaction with Claude API.
02Crafting efficient and targeted prompts for writing, planning, or research tasks.
03Optimizing developer prompts for coding tasks like refactoring or bug fixes.
