mcp-builder

Designing an MCP server involves creating workflow-first tools with clear schemas, documentation, and robust error handling instead of thin API wrappers. You establish project structure, shared utilities, and validation strategies so LLM agents can reliably discover and execute tools.

The best way to structure tool schemas for MCP servers in Python is to define workflow-first inputs and outputs with validation and pagination strategies. You must apply SDK best practices to ensure your tool design supports end-to-end agent tasks rather than simple API calls.

Writing evaluation tests for MCP server tools involves producing stable XML-based read-only evaluation questions. You author these sets to measure how effectively LLMs use your tools and verify agent performance without executing state-changing operations.

You can build an MCP server using either Node and TypeScript or Python. The implementation process applies to both language SDKs, allowing you to integrate external APIs and design tool schemas regardless of your preferred server environment.

LLM agents fail calling MCP tools with large API responses because of missing output truncation and pagination strategies. Implementing systematic schema design with safe error messages and response truncation prevents context overflow and ensures reliable tool execution.