How does this improve AI agent performance?

It emphasizes agent-centric design, which involves creating tools around logical workflows and providing concise, high-signal responses that fit within an LLM's limited context window.

What is an MCP server?

An MCP (Model Context Protocol) server is a standardized interface that allows Large Language Models to interact with external data sources, tools, and APIs securely and consistently.

Does this skill support both Python and TypeScript?

Yes, it provides specific implementation guides and best practices for both the Python FastMCP framework and the official TypeScript MCP SDK.

Can I test my server using this skill?

Absolutely. The skill includes a dedicated evaluation phase that helps you generate complex, realistic test cases and verification pairs to ensure your server functions as expected.

What are 'agent-centric' design principles?

They are principles that prioritize building tools for how AI thinks—focusing on actionable error messages, human-readable identifiers, and task-oriented tool grouping rather than mirroring raw API structures.

MCP Server Builder

Name: MCP Server Builder
Author: organvm-iv-taxis

byorganvm-iv-taxis

•

Desarrollo de API

Architects and implements high-quality Model Context Protocol (MCP) servers for seamless integration between LLMs and external services.

The MCP Server Builder skill provides a comprehensive framework for developing robust Model Context Protocol servers in Python and TypeScript. It guides developers through the entire lifecycle of tool creation, from agent-centric design principles and protocol documentation to implementation and automated evaluation. By focusing on workflow-optimized tool definitions rather than simple API wrapping, this skill ensures that AI agents can interact with your services efficiently while respecting context window constraints and handling errors gracefully.

Características Principales

01Multi-language support for Python (FastMCP) and TypeScript SDKs

02Comprehensive evaluation framework for testing server reliability

03Standardized implementation patterns for pagination and error handling

042 GitHub stars

05Agent-centric tool design and workflow optimization

06Automated protocol and framework documentation retrieval

Casos de Uso

01Developing standardized internal tools for engineering teams using the Model Context Protocol

02Optimizing legacy tool definitions for higher LLM success rates and lower token usage

03Building custom API connectors to extend Claude's capabilities with external data

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add organvm-iv-taxis/a-i--skills mcp-builder

For use in Claude.ai and ChatGPT

Características Principales

01Multi-language support for Python (FastMCP) and TypeScript SDKs

02Comprehensive evaluation framework for testing server reliability

03Standardized implementation patterns for pagination and error handling

042 GitHub stars

05Agent-centric tool design and workflow optimization

06Automated protocol and framework documentation retrieval

Casos de Uso

01Developing standardized internal tools for engineering teams using the Model Context Protocol

02Optimizing legacy tool definitions for higher LLM success rates and lower token usage

03Building custom API connectors to extend Claude's capabilities with external data

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add organvm-iv-taxis/a-i--skills mcp-builder

For use in Claude.ai and ChatGPT