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MCP-Server
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🌐 Claude MCP Server Quickstart
A ready-to-use implementation of the Model Context Protocol (MCP) server that integrates with Claude AI models.
🔍 Overview
This project provides a fully functional MCP server implementation that allows you to:
- Connect Claude AI models through a standardized protocol
- Process context-aware requests
- Handle model responses efficiently
- Streamline AI integrations in your applications
Built following the official MCP Server Quickstart guide.
✨ Features
- ✅ Complete MCP protocol implementation
- ✅ Claude AI model integration
- ✅ Context-aware request processing
- ✅ Streaming response support
- ✅ Easy configuration and setup
- ✅ Well-documented codebase
📋 Prerequisites
- Python 3.8+
- Access to Claude AI API credentials
- Basic understanding of REST APIs
🚀 Installation
# Clone the repository
git clone https://github.com/gabrieldsguilherme/mcp-server.git
cd mcp-server
# Create and activate virtual environment
uv venv
source .venv/bin/activate
# Install dependencies
uv add "mcp[cli]" httpx
⚙️ Configuration
1. Open your Claude Desktop configuration file
Open your Claude for Desktop App configuration at ~/Library/Application Support/Claude/claude_desktop_config.json
in a text editor. Make sure to create the file if it doesn’t exist.
2. Update your Claude Desktop configuration file
{
"mcpServers": {
"weather": {
"command": "/ABSOLUTE/PATH/TO/PARENT/FOLDER/uv",
"args": [
"--directory",
"/ABSOLUTE/PATH/TO/PARENT/FOLDER/weather",
"run",
"weather.py"
]
}
}
}
This tells Claude for Desktop:
a. There’s an MCP server named “weather”
b. To launch it by running uv --directory /ABSOLUTE/PATH/TO/PARENT/FOLDER/weather run weather.py
3. Save the file and restart Claude for Desktop
📖 Usage
1. Ask Claude "What’s the weather in Sacramento?"
2. Ask Claude "What are the active weather alerts in Texas?"
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Reviews

user_Xbjx4F1C
I've been using the mcp-server by gabrieldsguilherme and it's been a game-changer for my applications. The server is intuitive and reliable, making integration seamless. The documentation on the GitHub page is thorough and easy to follow, which significantly shortened my setup time. It's clear that a lot of thought went into creating this tool. Highly recommend!