token-optimization-mcp
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- AlicenseAqualityCmaintenanceAn MCP server that reduces AI API costs by up to 97% through token measurement, compression, caching, and pruning, all without changing prompts.101Apache 2.0
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- AlicenseNot gradedqualityCmaintenanceA local-first MCP server that reduces LLM token usage by intercepting, deduplicating, compressing, and optimizing MCP tool calls and responses.1 npmMIT
- FlicenseNot gradedqualityBmaintenanceAn MCP server suite that optimizes prompt context by reducing tokens up to 98.8%, acting as persistent long-term memory and codebase scanner to save API costs.-
- FlicenseBqualityDmaintenanceA Model Context Protocol (MCP) server that optimizes token usage by caching data during language model interactions, compatible with any language model and MCP client.42-
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TDQS
Scored across 9 tools
Each tool targets a distinct operation: caching (store/lookup/invalidate), compression, deduplication, analysis, estimation, model routing, and reporting. No two tools overlap in purpose.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., cache_store, compress_prompt, route_model), making them predictable and easy to differentiate.
With 9 tools, the server covers the core aspects of token optimization without being excessive. Each tool serves a clear need within the domain.
The tool set covers analysis, caching, compression, deduplication, estimation, routing, and reporting. The only minor gap is the lack of a cache listing tool, but the core workflow is complete.