Weather Service MCP
A learning project demonstrating how to build MCP servers with Python, featuring weather query tools that showcase custom tool creation, configuration, and integration with AI assistants.
README
MCP Learning Project 2025 ๐
A hands-on project to demonstrate building and deploying Model Context Protocol (MCP) servers. Learn how to create custom MCP tools, configure them for AI assistants, and integrate them with Claude Desktop, Continue, and other MCP-compatible applications.
๐ฏ What You'll Learn
- ๐ ๏ธ Build custom MCP servers from scratch
- ๐ Integrate MCP tools with AI assistants
- ๐งช Test and debug using MCP Inspector
- ๐ฆ Manage dependencies with UV or pip
- ๐ Deploy production-ready MCP servers
- ๐จ Create type-safe tools with Pydantic
๐๏ธ Tech Stack
| Category | Technology | Purpose |
|---|---|---|
| Language | Python 3.13+ | Core programming language |
| Protocol | MCP (Model Context Protocol) | Standardized AI-tool communication |
| Framework | FastMCP | Rapid MCP server development |
| Package Manager | UV or pip + venv | Dependency management |
| Validation | Pydantic | Data validation and type safety |
| Server | Uvicorn | ASGI server for MCP |
๐ Prerequisites
Before diving in, make sure you have:
- โ Python 3.13+ installed on your system
- โ UV (recommended) or pip + venv for package management
- โ VS Code (optional but recommended for MCP configuration)
- โ Git for version control
- โ Terminal access (PowerShell, CMD, or Bash)
๐ Installation
<table> <tr> <th width="50%">Using UV (Recommended)</th> <th width="50%">Using pip + venv</th> </tr> <tr> <td>
1. Install UV:
# Windows (PowerShell)
powershell -c "irm https://astral.sh/uv/install.ps1 | iex"
2. Initialize project:
# Create new project
uv init learn-mcp-2025
cd learn-mcp-2025
# Or in existing directory
uv init
3. Add MCP dependencies:
# Add MCP with CLI tools
uv add "mcp[cli]"
# This creates/updates:
# - pyproject.toml
# - uv.lock
4. Install all dependencies:
uv sync
</td> <td>
1. Navigate to project:
cd learn-mcp-2025
2. Create virtual environment:
python -m venv .venv
3. Activate virtual environment:
# Windows (PowerShell)
.venv\Scripts\Activate.ps1
# Windows (CMD)
.venv\Scripts\activate.bat
4. Install dependencies:
# From requirements.txt
pip install -r requirements.txt
# Or install package in editable mode
pip install -e .
</td> </tr> </table>
Generated Files
| UV | pip + venv |
|---|---|
pyproject.toml - Project metadata and dependencies |
requirements.txt - Pinned dependencies |
uv.lock - Locked dependency versions |
.venv/ - Virtual environment directory |
โ๏ธ MCP Server Configuration
To integrate your MCP server with AI clients (like Claude Desktop), create a configuration file:
Create .vscode/mcp.json
{
"servers": {
"weather-service": {
"command": "python",
"args": ["weather.py"],
"env": {}
}
}
}
Multi-Server Configuration
{
"servers": {
"weather-service": {
"command": "python",
"args": ["weather.py"],
"env": {}
},
"winget-mcp": {
"type": "stdio",
"command": "C:\\Users\\YourUser\\AppData\\Local\\Microsoft\\WindowsApps\\...\\WindowsPackageManagerMCPServer.exe"
}
}
}
Configuration Options
| Field | Description | Example |
|---|---|---|
command |
Executable to run | python, node, uv |
args |
Arguments passed to command | ["weather.py"], ["run", "server.py"] |
env |
Environment variables | {"API_KEY": "value"} |
type |
Communication type | stdio (default) |
๐ฎ Running the MCP Server
Method 1: Quick Testing โก (Direct Function Call)
Test individual functions without starting the full MCP server:
<table> <tr> <th width="50%">Using UV</th> <th width="50%">Using pip + venv</th> </tr> <tr> <td>
uv run python -c "from weather import get_weather; print(get_weather('London'))"
Output:
The current weather in London is sunny with a temperature of 25ยฐC.
</td> <td>
# Activate venv first
.venv\Scripts\Activate.ps1
# Then run
python -c "from weather import get_weather; print(get_weather('London'))"
Output:
The current weather in London is sunny with a temperature of 25ยฐC.
</td> </tr> </table>
When to use:
- โ Fast iteration during development
- โ Unit testing individual tools
- โ Debugging function logic
- โ Won't work with MCP clients
Method 2: Production Mode ๐ (Full MCP Server)
Run as a complete MCP server for AI assistant integration:
<table> <tr> <th width="50%">Using UV</th> <th width="50%">Using pip + venv</th> </tr> <tr> <td>
# Start MCP server
uv run python weather.py
# The server will start and listen for MCP requests
</td> <td>
# Activate venv first
.venv\Scripts\Activate.ps1
# Start MCP server
python weather.py
</td> </tr> </table>
When to use:
- โ Integration with AI assistants (Claude, Continue, etc.)
- โ Production deployments
- โ Multi-tool servers
- โ Standardized MCP protocol communication
Method 3: MCP Inspector ๐ (Development & Debugging)
Use the MCP Inspector to interactively test your server with a web UI:
<table> <tr> <th width="50%">Using Python MCP CLI</th> <th width="50%">Using Node.js npx (Recommended)</th> </tr> <tr> <td>
With UV:
# Start MCP dev mode
uv run mcp dev weather.py
With pip + venv:
# Activate venv first
.venv\Scripts\Activate.ps1
# Start MCP dev mode
mcp dev weather.py
Features:
- Terminal-based debugging
- Log output in console
- Quick server validation
- โ No web UI
</td> <td>
With UV:
# No installation needed - npx downloads temporarily
npx @modelcontextprotocol/inspector uv run weather.py
With pip + venv:
# Activate venv first
.venv\Scripts\Activate.ps1
# Run inspector with Python
npx @modelcontextprotocol/inspector python weather.py
Features:
- โ Interactive web UI
- โ Visual tool explorer
- โ Request/response inspection
- โ Real-time testing
- โ Always latest version
</td> </tr> </table>
MCP Inspector Features:
- ๐ Interactive tool testing in browser
- ๐ Request/response inspection
- ๐ Real-time debugging
- ๐ Schema validation
- ๐จ Visual interface for all MCP tools
Access Inspector:
Open browser: http://localhost:5173
Example Output:
$ npx @modelcontextprotocol/inspector uv run weather.py
MCP Inspector running at http://localhost:5173
Server: Weather Service
Tools available: get_weather
๐ Project Structure
learn-mcp-2025/
โโโ .vscode/
โ โโโ mcp.json # MCP server configuration for VS Code
โโโ .venv/ # Virtual environment (pip only)
โโโ weather.py # Main MCP server implementation
โโโ pyproject.toml # Project metadata & dependencies (UV)
โโโ requirements.txt # Pinned dependencies (pip)
โโโ uv.lock # Locked dependency versions (UV)
โโโ .python-version # Python version specification
โโโ .gitignore # Git ignore rules
โโโ README.md # This file
Key Files Explained
| File | Purpose |
|---|---|
weather.py |
MCP server with tools decorated with @mcp.tool() |
pyproject.toml |
Modern Python project configuration (PEP 621) |
requirements.txt |
Traditional pip dependency list |
uv.lock |
UV's deterministic dependency lock file |
.vscode/mcp.json |
MCP client configuration for VS Code |
๐ Quick Command Reference
UV Commands ๐ฎ
| Command | Description |
|---|---|
uv init |
Initialize new Python project |
uv add <package> |
Add dependency to project |
uv remove <package> |
Remove dependency |
uv sync |
Install/sync all dependencies |
uv run <command> |
Run command in project environment |
uv pip list |
List installed packages |
uv pip show <package> |
Show package details |
uv lock |
Update lock file |
uv python install <ver> |
Install Python version |
uv python list |
List available Python versions |
pip + venv Commands ๐
| Command | Description |
|---|---|
python -m venv .venv |
Create virtual environment |
.venv\Scripts\Activate.ps1 |
Activate venv (PowerShell) |
.venv\Scripts\activate.bat |
Activate venv (CMD) |
pip install -r requirements.txt |
Install dependencies |
pip install -e . |
Install package in editable mode |
pip install <package> |
Install single package |
pip uninstall <package> |
Remove package |
pip list |
List installed packages |
pip show <package> |
Show package details |
pip freeze > requirements.txt |
Export dependencies |
deactivate |
Deactivate virtual environment |
MCP Commands ๐ง
| Command | Description |
|---|---|
mcp dev <file> |
Start MCP Inspector for development |
mcp --version |
Check MCP CLI version |
python <file>.py |
Start MCP server in production |
๐ก Development Examples
Example 1: Adding a New Weather Tool ๐ค๏ธ
Edit weather.py:
from mcp.server.fastmcp import FastMCP
mcp = FastMCP("Weather Service")
@mcp.tool()
def get_weather(location: str) -> str:
"""Get current weather for a location."""
return f"The current weather in {location} is sunny with a temperature of 25ยฐC."
@mcp.tool()
def get_forecast(location: str, days: int = 7) -> str:
"""Get weather forecast for the next N days."""
return f"Forecast for {location} for the next {days} days: Mostly sunny"
@mcp.tool()
def get_temperature(location: str, unit: str = "celsius") -> str:
"""Get current temperature in specified unit."""
temp = 25 if unit == "celsius" else 77
return f"Temperature in {location}: {temp}ยฐ{unit[0].upper()}"
if __name__ == "__main__":
mcp.run()
Example 2: Testing New Tools โ
# Test with UV
uv run python -c "from weather import get_forecast; print(get_forecast('Paris', 5))"
# Test with pip/venv
python -c "from weather import get_forecast; print(get_forecast('Paris', 5))"
Example 3: Adding Type Safety ๐
from typing import Literal
from mcp.server.fastmcp import FastMCP
mcp = FastMCP("Weather Service")
@mcp.tool()
def get_temperature(
location: str,
unit: Literal["celsius", "fahrenheit"] = "celsius"
) -> str:
"""Get temperature with validated unit parameter."""
temp = 25 if unit == "celsius" else 77
return f"Temperature in {location}: {temp}ยฐ{unit[0].upper()}"
Example 4: Debugging & Verification ๐
# List all tools in your server
uv run python -c "from weather import mcp; print(mcp.list_tools())"
# Check Python version
uv run python --version
# Verify MCP package
uv pip show mcp
# Test imports
uv run python -c "from weather import mcp; print('MCP initialized successfully')"
๐ค Contributing
This is a learning project! Feel free to:
- ๐ Report bugs or issues
- ๐ก Suggest new MCP tools
- ๐ Improve documentation
- ๐ Submit pull requests
๐ License
This project is for learning purposes.
<div align="center">
Built with โค๏ธ for learning MCP
โญ Star this repo if you found it helpful!
๐ GitHub โข ๐ MCP Docs โข ๐ง FastMCP
</div>
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
E2B
Using MCP to run code via e2b.
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Neon Database
MCP server for interacting with Neon Management API and databases