A universal gateway that aggregates multiple MCP servers into a single interface while providing advanced token optimization, result filtering, and automated summarization. It enables efficient management of large tool catalogs and reduces context usage by up to 95% for major AI clients.
A multiplexing gateway that aggregates multiple MCP servers into a single port, significantly reducing context token usage through a Meta-MCP discovery system. It enables dynamic tool discovery and invocation across various transport protocols including stdio, HTTP, and SSE.
A local MCP gateway that compresses multiple upstream servers into two tools, search and execute, to minimize model context usage. It provides a compact, code-driven interface for discovering and calling tools across various upstream sources on demand.
A unified gateway for AI agent tools that provides a single MCP stdio endpoint for executing tool calls with unified auth, rate limiting, and observability. Enables agents to interact with multiple external APIs through a standardized interface.
A local MCP gateway that allows AI clients to manage and interact with multiple MCP servers through a single connection, providing token-efficient access to tools and resources.
A Model Context Protocol server gateway that reduces context bloat through progressive tool discovery and Lua-based tool chaining, while centralizing multiple MCP servers into a single endpoint.
