mcp-builder

To build an MCP server for LLM tool integration, follow agent-centric design principles, adhere to the MCP protocol, and implement the server using Python (FastMCP) or Node/TypeScript SDKs. The process includes creating actionable tools and designing clear error messages.

Agent-centric design for Model Context Protocol servers involves creating actionable tools optimized for limited LLM context. It ensures tools align with LLM workflows, enabling reliable interaction with external services and APIs through well-defined interfaces.

Yes, you can use Python and TypeScript to develop MCP servers. This Skill provides detailed language-specific implementation guides for both Python using the FastMCP framework and Node.js using the TypeScript SDK.

You evaluate MCP server performance using evaluation-driven development. This approach involves creating robust evaluations to ensure your server effectively manages LLM interactions with external APIs and handles errors clearly.

The best way to design error messages for LLM tool servers is to make them clear and actionable for the LLM. This ensures the model can understand interaction failures with external services and adjust its workflow accordingly within limited context.

Your LLM might struggle with complex API tools because of limited context windows. Building Model Context Protocol servers with agent-centric design principles helps by optimizing tool actions and context usage to fit LLM workflows reliably.