Local MCP server for token optimization, providing tools to compress code/JSON, optimize prompts, and manage placeholder-based content redaction and hydration to reduce LLM token usage.
Token-optimized MCP server that reduces context window usage by 59.5% by grouping 12 tools into 5 semantic operations, preserving all original functionality for AI assistants.
A local, zero-cloud MCP server for token and text compression. It provides tools to compress, auto-compress, measure, and decompress text using offline rules, lossless gzip packing, or a local Ollama semantic model.
A token-optimized MCP server for Notion that reduces context window usage by 73% while preserving full functionality, enabling AI assistants to interact with Notion efficiently.
MCP server that reduces AI agent token usage by up to 90% through intelligent context compression. Enables efficient code exploration, multi-file refactoring, and debugging by providing tools for smart reading, searching, and managing code context.