A drop-in MCP proxy that aggregates multiple backend servers into two meta-tools for efficient tool discovery and execution. It enables AI clients to access hundreds of tools while minimizing context window usage through searchable indexing.
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.
Intelligent MCP proxy server that reduces context bloat by serving only the tools your AI actually needs through semantic search and a fixed two-tool surface.
A semantic proxy that reduces AI agent token usage by exposing only three core tools and using local vector embeddings to search for and execute hundreds of underlying MCP tools. It streamlines communication between agents and MCP Routers by identifying relevant tools through natural language queries.
