io.github.rccola990-cloud/mcp-token-optimizer is a Model Context Protocol (MCP) server designed to optimize LLM token usage. It counts tokens, estimates costs, trims prompts, and selects the most cost-effective model capable of handling the task.
🛠️ Key Features
- Count tokens for input and prompt segments
- Estimate token costs across models
- Slim prompts to reduce token overhead
- Choose the cheapest model that meets the required capability
🚀 Use Cases
- Cost-conscious LLM inference budgeting
- Prompt optimization prior to model invocation
- Dynamic model selection based on price and capability
⚡ Developer Benefits
- Clear token- and cost-oriented tooling for MCP pipelines
- Straightforward integration points for token counting and cost estimation
- Helps balance performance and expense in model orchestration
⚠️ Limitations
- Based on token counting and cost estimates; real-world costs may vary by provider and model
- Requires accurate model capability assessment to avoid underpowered selections