How does this skill help with tool discovery?

It provides guidelines on tool naming conventions, action-oriented prefixes, and concise descriptions to help AI agents identify the correct tools.

Why is the evaluation phase important?

Evaluations ensure that your MCP server effectively solves real-world tasks through complex, multi-step tool calls that are verifiable and stable.

Can I use this for local development?

Yes, it includes instructions for building servers using stdio transport for local use and streamable HTTP for remote deployments.

What languages does the mcp-builder skill support?

It provides detailed implementation patterns and documentation for both TypeScript (using the MCP SDK) and Python (using FastMCP).

MCP Server Builder

Name: MCP Server Builder
Author: dobeutech

bydobeutech

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API Development

Guides developers through the end-to-end process of building high-quality Model Context Protocol (MCP) servers for Python and TypeScript.

About

The mcp-builder skill provides a comprehensive framework for developing Model Context Protocol (MCP) servers that allow LLMs to interact seamlessly with external services. It offers domain-specific guidance on API coverage, tool design, and transport selection, covering both the TypeScript and Python SDKs. By following its structured four-phase workflow—spanning research, implementation, rigorous testing, and evaluation creation—developers can ensure their MCP integrations are robust, discoverable, and highly effective for real-world agentic tasks.

Key Features

1 GitHub stars
Standardized workflow for MCP server development
Guidance on tool naming and context management
Support for both TypeScript and Python SDKs
Framework for creating verifiable evaluation QA pairs
Integration with MCP Inspector for testing

Use Cases

Generating evaluation datasets to test LLM tool-calling performance
Creating production-grade connectors for third-party SaaS platforms
Building an MCP server to integrate a custom internal API with Claude

About

Key Features

1 GitHub stars
Standardized workflow for MCP server development
Guidance on tool naming and context management
Support for both TypeScript and Python SDKs
Framework for creating verifiable evaluation QA pairs
Integration with MCP Inspector for testing

Use Cases

Generating evaluation datasets to test LLM tool-calling performance
Creating production-grade connectors for third-party SaaS platforms
Building an MCP server to integrate a custom internal API with Claude