mcp-builder

You build an MCP server by defining clear tools, transports, and schemas that let LLMs interact with external services. This guide provides implementation patterns for API integration, tool registration, and structured outputs for agent workflows.

Input validation for a Model Context Protocol server is handled using Pydantic for Python FastMCP implementations and Zod for TypeScript MCP SDK implementations, ensuring robust structured data schemas for your tools.

Yes, FastMCP supports both stdio and streamable HTTP transports for MCP servers. The guide covers transport support alongside pagination metadata and actionable error messages for reliable external service communication.

You test MCP server tool schemas and pagination using the provided evaluation harness. It runs automated read-only testing against your server to verify tool schemas, pagination behavior, and overall agent workflows.

Yes, you can use the MCP SDK to integrate third-party APIs like GitHub and Slack into LLM-driven workflows. The guide provides concrete patterns for connecting external services with robust, testable tools.

structuredContent returns and clear tool annotations are needed in your MCP server to ensure reliable context management and well-designed tool discovery. They enable LLMs to correctly parse outputs and understand tool purposes.