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MCP Server Template (Python)

@Nisarg38

代码仓库

关于 MCP Server Template (Python)

暂无概览

#mcp#server#python#template

基本信息

分类

开发工具

运行时

python

传输方式

stdio

发布者

Nisarg38

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mcp-server-template-python-nisarg38": {
      "command": "python",
      "args": [
        "-m",
        "src.main"
      ]
    }
  }
}

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is MCP Server Template (Python)?

A ready-to-use template for building Model Context Protocol (MCP) servers in Python. It helps you quickly create servers that register and expose tools and prompts for AI models to use.

How to use MCP Server Template (Python)?

Install the package with pip, then run with python -m src.main or the mcp-server-template CLI. Customize with command-line options like --port, --debug, --transport stdio, and --log-level. Add your own tools and prompts by editing src/main.py and using the @mcp.tool() and @mcp.prompt() decorators.

Key features of MCP Server Template (Python)

  • Ready-to-use template for MCP servers in Python.
  • Register and expose tools and prompts for AI models.
  • HTTP and stdio transport options.
  • Command-line configuration for port, debug mode, and logging.
  • Docker and cloud deployment support.
  • Development tools: testing, formatting, linting.

Use cases of MCP Server Template (Python)

  • Rapidly prototype an MCP server for AI integration.
  • Build custom tools and prompts for AI models to call.
  • Deploy an MCP server on cloud platforms or containers.
  • Learn and experiment with the Model Context Protocol.
  • Create a foundation for a production MCP server.

FAQ from MCP Server Template (Python)

What is MCP Server Template (Python)?

It is a template for building Model Context Protocol (MCP) servers in Python, designed to quickly create servers that expose tools and prompts for AI models.

What are the prerequisites to use this template?

Python 3.10 or newer is required.

How do I add a new tool or prompt?

Edit src/main.py and add a function with the @mcp.tool() or @mcp.prompt() decorator, following the provided examples.

What transport options are available?

The server supports HTTP (default on port 8080) and stdio transport. Use --transport stdio for stdio.

How can I deploy this server?

You can build a Docker image using the provided Dockerfile, or deploy on cloud platforms like AWS, GCP, or Azure, including Kubernetes.

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