Does it support modern schema validation?

Yes, it guides you through using Zod (TypeScript) and Pydantic (Python) to create strict input and output schemas that improve LLM reliability.

Can I build local servers with this skill?

Yes, the builder includes patterns for both local stdio-based transport and remote streamable HTTP transport mechanisms.

How does this skill help with tool discovery?

It enforces specific naming conventions and description patterns to ensure LLMs can accurately identify, select, and parameterize the correct tools for any given task.

What languages does this MCP builder support?

It provides comprehensive implementation guides for both TypeScript using the official MCP SDK and Python using the FastMCP framework.

Why is the evaluation phase important?

The evaluation phase allows you to create complex, verifiable QA pairs to ensure your MCP server remains stable and that the LLM can successfully navigate multi-step tool workflows.

MCP Server Builder

Name: MCP Server Builder
Author: zephyrwang6

byzephyrwang6

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API Development

Builds high-quality Model Context Protocol (MCP) servers to bridge LLMs with external APIs and services using standardized implementation patterns.

About

The mcp-builder skill provides a comprehensive, four-phase workflow for developing robust MCP servers in TypeScript or Python. It guides developers through deep research using the MCP specification, implementation of structured tool schemas with Zod or Pydantic, proper error handling, and the creation of rigorous evaluation suites. By following these industry best practices, developers can ensure their LLM agents interact seamlessly and reliably with external services through well-defined tools, resources, and context management protocols.

Key Features

Built-in reference library for MCP protocol specifications and best practices
Standardized tool naming and discoverability optimization guidelines
Integrated evaluation framework for testing LLM tool-calling accuracy
Cross-language support for TypeScript SDK and Python FastMCP frameworks
37 GitHub stars
Automated project structure setup for local (stdio) and remote (HTTP) transports

Use Cases

Integrating proprietary internal APIs into a Claude-based AI developer workflow
Building custom connectors for third-party SaaS platforms like GitHub, Slack, or Jira
Developing production-grade MCP servers with rigorous validation and verifiable test suites

About

Key Features

Built-in reference library for MCP protocol specifications and best practices
Standardized tool naming and discoverability optimization guidelines
Integrated evaluation framework for testing LLM tool-calling accuracy
Cross-language support for TypeScript SDK and Python FastMCP frameworks
37 GitHub stars
Automated project structure setup for local (stdio) and remote (HTTP) transports

Use Cases

Integrating proprietary internal APIs into a Claude-based AI developer workflow
Building custom connectors for third-party SaaS platforms like GitHub, Slack, or Jira
Developing production-grade MCP servers with rigorous validation and verifiable test suites