Lightweight MCP wrappers that consolidate multiple tools from services like Supabase, Linear, Chrome DevTools, and Context7 into single-action tools, reducing context token usage by ~80% while maintaining full functionality.
Token-efficient MCP reimplementation with progressive tool discovery, result handling, and compact wire encoding, reducing token usage by up to 89% on tool definitions.
An MCP proxy that embeds tool definitions and returns only the top-k semantically relevant tools per query, reducing context usage and routing calls to upstream MCP servers.
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.
An adaptive tiny-model layer that sits between an LLM and its MCP tools, compressing verbose tool outputs to reduce token usage by up to two orders of magnitude.
