An MCP server proxy that reduces context window bloat by stripping metadata and fetching schemas on-demand, while managing backend MCP servers across multiple transports. It also provides a web dashboard for monitoring and restarting backend servers.
A single MCP endpoint for AI agents to browse, inspect, and call tools from multiple upstream MCP servers without loading all schemas upfront, reducing context overhead.
A smart MCP proxy server that lazily loads relevant MCP tool servers based on project context, keeping AI tool counts within recommended limits. It enables agents to dynamically activate, deactivate, and discover MCP servers to optimize context usage.
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.
Acts as a proxy for multiple MCP servers, reducing context window usage from 15,000+ tokens to ~500 tokens by dynamically loading servers on-demand and exposing only 3 tools instead of all tool definitions.