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Proxy multiple MCP servers while reducing token usage with on-demand tool loading.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "mcp-proxy" yet — see the docs or source repo.
I have multiple MCP backend servers and want to add a proxy layer in front of my AI app to reduce token usage from tool definitions in context. Explain how to configure mcp-proxy, connect multiple backends, and how on-demand tool loading works.
A setup guide covering multi-backend connections, proxy behavior, and how token savings are achieved.
Help me evaluate the benefits of using mcp-proxy in an MCP environment with 20 tools. Compare local caching of tool definitions and on-demand loading against exposing all tools directly, including possible token and performance gains.
A comparative analysis of the proxy approach's potential advantages in token usage, response efficiency, and scalability.
I want to unify three MCP services for document retrieval, database queries, and automation execution. Design a multi-backend proxy architecture with mcp-proxy and provide recommendations for routing, caching, and maintenance.
A clear proxy architecture plan including service organization, plus caching and operational recommendations.
Aggregate multiple MCP resource servers behind one HTTP endpoint.
Manage multiple MCP servers and load tool schemas on demand efficiently.
Securely proxy OAuth for MCP servers to connect with Claude and ChatGPT.
Aggregate multiple MCP servers into one for search, parallel calls, and orchestration.
Compress and proxy MCP responses to reduce token usage for LLM tool calls.
Run a local-first MCP proxy with secure discovery and major token savings.