MCP Server Cookiecutter Template

@shubhamgupta-dat

About MCP Server Cookiecutter Template

Easy Manageable Way to create your own MCP Server

#mcp-server #cookiecutter #python

Basic information

Category

Developer Tools

Runtime

python

Transports

stdio

Publisher

shubhamgupta-dat

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "mcp-server-template-shubhamgupta-dat": {
      "command": "uv",
      "args": [
        "venv"
      ]
    }
  }
}

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is MCP Server Cookiecutter Template?

A Cookiecutter template for creating Model Context Protocol (MCP) servers with Python. It provides a complete project structure with sample implementations of tools, resources, and prompts, and integrates FastMCP, Docker, and Claude Desktop.

How to use MCP Server Cookiecutter Template?

Install Cookiecutter, then run cookiecutter gh:shubhamgupta-dat/mcp-server-cookiecutter. Navigate to the generated project, run make setup, activate the virtual environment, and use make dev for development or make install to add it to Claude Desktop.

Key features of MCP Server Cookiecutter Template

Complete project structure pre-configured for MCP servers
Sample implementations of tools, resources, and prompts
FastMCP integration for decorator-based development
Lifecycle management with resource initialization and cleanup
Modern Python practices with type hints and documentation
Docker support for containerized deployment

Use cases of MCP Server Cookiecutter Template

Create a custom MCP server to provide real‑time data to Claude
Build tools that let LLMs interact with external APIs
Set up a reusable project with standardized prompts and resources
Quickly scaffold a production‑ready MCP server with testing and Docker

FAQ from MCP Server Cookiecutter Template

What is MCP (Model Context Protocol)?

MCP is an open standard that lets applications provide context for LLMs like Claude in a standardized way, exposing Tools, Resources, and Prompts.

What are the prerequisites?

Python 3.12+ and Cookiecutter installed via pip (pip install cookiecutter).

How can I test my generated server?

Run make test in the project directory to execute tests with pytest.

How do I run the server in Docker?

Use make docker-build to build the image and make docker-run to run the container on port 8000.

How is the server configured?

Via environment variables prefixed with MCP_ (e.g., MCP_API_KEY) or a config file specified by the MCP_CONFIG_FILE environment variable.

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