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python-mcp-server

Develop Python MCP servers with tools, resources, and prompts via type hints.

Updated Jan 23, 2026
Search Tags:#python#api development#mcp#ai tools#server development#fastmcp
One-click install
npx skills add https://github.com/pingqLIN/skill-0 --skill python-mcp-server-pingqlin
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: python-mcp-server
Source: https://github.com/pingqLIN/skill-0/tree/main/converted-skills/python-mcp-server
Command: npx skills add https://github.com/pingqLIN/skill-0 --skill python-mcp-server-pingqlin

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides a streamlined framework for developing Model Context Protocol (MCP) servers using Python, simplifying the creation of AI tools and services.

Core Features & Use Cases

  • Rapid Server Development: Quickly set up MCP servers for various transports (stdio, HTTP).
  • Tool and Resource Registration: Easily define and register tools, resources, and prompts using decorators.
  • Structured Data Handling: Enforces type hints and Pydantic models for robust input/output validation and schema generation.
  • Contextual Operations: Access server context for logging, progress reporting, user elicitation, and LLM sampling.
  • Use Case: Develop a Python-based tool that can ingest user queries, interact with external APIs via registered resources, and return structured JSON responses, all managed by the MCP framework.

Quick Start

Use the python-mcp-server skill to create a basic HTTP server that greets the user by name.

Frequently Asked Questions about python-mcp-server

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build a Model Context Protocol server with Python?▼

To build a Model Context Protocol server with Python, use this framework to define and register tools, resources, and prompts via decorators, supporting rapid server development across stdio and HTTP transports with automatic schema generation.

How does FastMCP handle schema generation for tools and resources?▼

FastMCP handles schema generation by enforcing Python type hints and Pydantic models, automatically creating robust input and output validation schemas for registered tools and resources without manual specification.

Can I manage logging and progress reporting within an MCP server?▼

You can manage logging and progress reporting within an MCP server by accessing the integrated context management features, which also support user elicitation and LLM sampling during contextual operations.

Does this framework support streamable-http and stdio transports?▼

The framework supports both streamable-http and stdio transports, allowing you to quickly set up Model Context Protocol servers tailored for different local or network-based communication requirements.

What is the best way to register prompts in a Python MCP server?▼

The best way to register prompts in a Python MCP server is by using the provided decorators, which simplify the definition process and integrate directly with Pydantic models for structured data handling.

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