MCP Server template for better AI Coding

by sontallive

17 stars

459 downloads

Not rated

GitHub

Developer Tools

About

This template provides a streamlined foundation for building Model Context Protocol (MCP) servers in Python. It's designed to make AI-assisted development of MCP tools easier and more efficient.

Details

Author: sontallive
GitHub stars: 17
Downloads: 459
Categories: Developer Tools

- Ready-to-use MCP server implementation in Python
- Configurable transport modes (stdio, SSE)
- Example weather service integration (NWS API)
- Embedded MCP specifications and documentation for AI understanding
- Minimal dependencies and clean, documented code structure
- Cursor Rules integration for improved coding assistance

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name MCP Server template for better AI Coding

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "mcp server template for better ai coding": {
            "mcp-server-python-template": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp server template for better ai coding": {
            "mcp-server-python-template": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp server template for better ai coding": {
            "mcp-server-python-template": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "mcp server template for better ai coding": {
            "mcp-server-python-template": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp server template for better ai coding": {
            "mcp-server-python-template": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp server template for better ai coding": {
            "mcp-server-python-template": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "mcp server template for better ai coding": {
            "mcp-server-python-template": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp server template for better ai coding": {
            "mcp-server-python-template": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp server template for better ai coding": {
            "mcp-server-python-template": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "mcp server template for better ai coding": {
            "mcp-server-python-template": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp server template for better ai coding": {
            "mcp-server-python-template": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp server template for better ai coding": {
            "mcp-server-python-template": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "mcp server template for better ai coding": {
            "mcp-server-python-template": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp server template for better ai coding": {
            "mcp-server-python-template": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp server template for better ai coding": {
            "mcp-server-python-template": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

From the repository

Clone the repository, create a virtual environment, install dependencies with pip install -e ., then run the example server using python server.py --transport stdio (for CLI) or python server.py --transport sse --host 0.0.0.0 --port 8080 (for web apps). Custom tools can be created by importing FastMCP and using the @mcp.tool() decorator.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "mcp server template for better ai coding": {
            "mcp-server-python-template": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

McpServers

{
    "mcp-server-python-template": {
        "command": "python",
        "args": [
            "-m",
            "venv",
            ".venv"
        ]
    }
}

MCP Server template for better AI Coding

> Inspired by MCP Official Tutorial

Overview

This template provides a streamlined foundation for building Model Context Protocol (MCP) servers in Python. It's designed to make AI-assisted development of MCP tools easier and more efficient.

Features

- Ready-to-use MCP server implementation
- Configurable transport modes (stdio, SSE)
- Example weather service integration (NWS API)
- Clean, well-documented code structure
- Minimal dependencies
- Embedded MCP specifications and documentation for improved AI tool understanding

Cursor Rules Integration

This project uses Cursor Rules for improved AI coding assistance, with patterns from Awesome Cursor Rules.

- Clean Code Guidelines: Built-in clean code rules help maintain consistency and quality
- Enhanced AI Understanding: Rules provide context that helps AI assistants generate better code
- Standardized Patterns: Follow established best practices for MCP server implementation

Cursor Rules help both AI coding assistants and human developers maintain high code quality standards and follow best practices.

Integrated MCP Documentation

This template includes comprehensive MCP documentation directly in the project:

- Complete MCP Specification (protocals/mcp.md): The full Model Context Protocol specification that defines how AI models can interact with external tools and resources. This helps AI assistants understand MCP concepts and implementation details without requiring external references.

- Python SDK Guide (protocals/sdk.md): Detailed documentation for the MCP Python SDK, making it easier for AI tools to provide accurate code suggestions and understand the library's capabilities.

- Example Implementation (protocals/example_weather.py): A practical weather service implementation demonstrating real-world MCP server patterns and best practices.

Having these resources embedded in the project enables AI coding assistants to better understand MCP concepts and provide more accurate, contextually relevant suggestions during development.

Requirements

- Python 3.12+
- Dependencies:
- mcp>=1.4.1
- httpx>=0.28.1
- starlette>=0.46.1
- uvicorn>=0.34.0

Getting Started

Installation

1. Clone this repository:

   git clone https://github.com/yourusername/mcp-server-python-template.git

   cd mcp-server-python-template

2. Create a virtual environment and install dependencies:

   python -m venv .venv

   source .venv/bin/activate  # On Windows: .venv\Scripts\activate

   pip install -e .

Running the Example Server

The template includes a weather service example that demonstrates how to build MCP tools:

```bash

No reviews yet — be the first

Use Google, GitHub, or an email account so ratings stay tied to real people.

Email sign in

No reviews posted yet.

About

Details

Jump to

Setting up with Highlight

From the repository

Claude Desktop / Cursor

McpServers

MCP Server template for better AI Coding

Overview

Features

Cursor Rules Integration

Integrated MCP Documentation

Requirements

Getting Started

Installation

Running the Example Server

Install

More like this

Sentry

Github

Git

GitLab

Context 7

Playwright