mcp-builder

To design reliable MCP server tools, build them around complete agent workflows rather than thin API wrappers, optimize inputs and outputs for constrained context windows, and enforce strict schema validation to ensure LLM agents can successfully execute tasks.

The best way to handle errors in a FastMCP server is to follow MCP protocol best practices by designing robust error handling strategies alongside strict input and output schemas, ensuring agents receive clear feedback when external service operations fail.

Yes, this approach supports building MCP servers with the Node TypeScript SDK using Zod for schema validation, providing implementation guidance and best practices alongside Python FastMCP stacks for robust tool design and evaluation.

Evaluate MCP tool usefulness by creating stable XML evaluation questions that measure agent performance using read-only operations, allowing you to iteratively refine tool behavior and schemas based on observable agent success rates.

You should build workflow-aligned tools instead of wrapping API endpoints because thin wrappers reduce agent success rates, whereas tools designed around complete agent workflows with configurable detail and clear identifiers significantly improve task completion reliability.

Using read-only operations for MCP tool evaluation limits validation to observation and query tasks, meaning you cannot test state-changing workflows or mutating external service actions, restricting evaluation scope to non-destructive agent performance metrics.