| Name | axians-mcp JSON |
| Version |
1.2.2
JSON |
| download |
| home_page | None |
| Summary | MCP server providing tools for weather and iceland |
| upload_time | 2025-07-30 14:35:19 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.10 |
| license | MIT |
| keywords |
mcp
server
tools
weather
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
Axians MCP Server
A Model Context Protocol (MCP) server that provides weather information tools using the National Weather Service API.
Features
🌦️ Weather Alerts: Get active weather alerts for any US state
📊 Weather Forecast: Get detailed weather forecasts for any location (latitude/longitude)
🚀 FastMCP Framework: Built on the efficient FastMCP framework
🔧 Multiple Transports: Supports stdio, SSE, and streamable HTTP transports
Installation
Using uvx (Recommended)
bash
uvx axians-mcp --transport=stdio
Using pip
bash
pip install axians-mcp
axians-mcp --transport=stdio
Development Installation
bash
git clone <repository-url>
cd axians-mcp
uv pip install -e .
Usage
Basic Usage
bash
# Start the MCP server with stdio transport
axians-mcp --transport=stdio
# Start with verbose logging
axians-mcp --verbose --transport=stdio
# Start with custom environment file
axians-mcp --env-file=.env.custom --transport=stdio
Available Transports
stdio: Standard input/output (default, recommended for MCP clients)
sse: Server-Sent Events
streamable-http: HTTP streaming
Environment Configuration
Create a .env file in your project directory:
env
TRANSPORT=stdio
LOG_LEVEL=INFO
Tools Available
Weather Alerts
Get active weather alerts for a US state:
python
# Example usage in MCP client
await call_tool("get_alerts", {"state": "CA"})
Parameters:
state (string): Two-letter US state code (e.g., "CA", "NY", "TX")
Weather Forecast
Get detailed weather forecast for a specific location:
python
# Example usage in MCP client
await call_tool("get_forecast", {
"latitude": 37.7749,
"longitude": -122.4194
})
Parameters:
latitude (float): Latitude coordinate
longitude (float): Longitude coordinate
Command Line Options
Usage: axians-mcp [OPTIONS]
Options:
-v, --verbose Increase verbosity (can be used multiple times)
--env-file PATH Path to .env file
--transport [stdio|sse|streamable-http]
Transport type (default: stdio)
--help Show this message and exit
Examples
Getting Weather Alerts for California
bash
# Start the server
axians-mcp --transport=stdio
# In your MCP client, call:
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "get_alerts",
"arguments": {
"state": "CA"
}
}
}
Getting Forecast for San Francisco
bash
# In your MCP client, call:
{
"jsonrpc": "2.0",
"id": 2,
"method": "tools/call",
"params": {
"name": "get_forecast",
"arguments": {
"latitude": 37.7749,
"longitude": -122.4194
}
}
}
Integration with MCP Clients
This server is compatible with any MCP client, including:
Claude Desktop: Add to your MCP configuration
Custom Applications: Use the MCP protocol to integrate weather data
Development Tools: Great for testing and development workflows
Claude Desktop Configuration
Add to your MCP settings:
json
{
"mcpServers": {
"axians-weather": {
"command": "uvx",
"args": ["axians-mcp", "--transport=stdio"]
}
}
}
API Data Source
This server uses the National Weather Service (NWS) API, which provides:
Real-time weather alerts
Detailed forecasts
High-quality, government-sourced weather data
Free access (no API key required)
All data is sourced from https://api.weather.gov and follows NWS API guidelines.
Development
Project Structure
src/axians_mcp/
├── __init__.py # CLI entry point and main configuration
├── servers/
│ ├── __init__.py # Server exports
│ ├── main.py # FastMCP server setup
│ └── weather.py # Weather tools implementation
Running Tests
bash
# Install development dependencies
uv pip install -e ".[dev]"
# Run tests (when available)
pytest
Building the Package
bash
uv run python -m build
Contributing
Fork the repository
Create a feature branch (git checkout -b feature/amazing-feature)
Commit your changes (git commit -m 'Add amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request
Requirements
Python 3.10+
Internet connection (for NWS API access)
Dependencies
fastmcp>=2.3.4: FastMCP framework
httpx>=0.28.0: HTTP client for API requests
click>=8.1.7: Command-line interface
python-dotenv>=1.0.1: Environment variable management
pydantic>=2.10.6: Data validation
License
This project is licensed under the MIT License - see the LICENSE file for details.
Support
For issues and questions:
Check the Issues page
Create a new issue with detailed information
Include logs and configuration details
Changelog
v0.1.0
Initial release
Weather alerts tool
Weather forecast tool
Multiple transport support
FastMCP integration
Raw data
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"description": "Axians MCP Server\nA Model Context Protocol (MCP) server that provides weather information tools using the National Weather Service API.\n\nFeatures\n\ud83c\udf26\ufe0f Weather Alerts: Get active weather alerts for any US state\n\ud83d\udcca Weather Forecast: Get detailed weather forecasts for any location (latitude/longitude)\n\ud83d\ude80 FastMCP Framework: Built on the efficient FastMCP framework\n\ud83d\udd27 Multiple Transports: Supports stdio, SSE, and streamable HTTP transports\nInstallation\nUsing uvx (Recommended)\nbash\nuvx axians-mcp --transport=stdio\nUsing pip\nbash\npip install axians-mcp\naxians-mcp --transport=stdio\nDevelopment Installation\nbash\ngit clone <repository-url>\ncd axians-mcp\nuv pip install -e .\nUsage\nBasic Usage\nbash\n# Start the MCP server with stdio transport\naxians-mcp --transport=stdio\n\n# Start with verbose logging\naxians-mcp --verbose --transport=stdio\n\n# Start with custom environment file\naxians-mcp --env-file=.env.custom --transport=stdio\nAvailable Transports\nstdio: Standard input/output (default, recommended for MCP clients)\nsse: Server-Sent Events\nstreamable-http: HTTP streaming\nEnvironment Configuration\nCreate a .env file in your project directory:\n\nenv\nTRANSPORT=stdio\nLOG_LEVEL=INFO\nTools Available\nWeather Alerts\nGet active weather alerts for a US state:\n\npython\n# Example usage in MCP client\nawait call_tool(\"get_alerts\", {\"state\": \"CA\"})\nParameters:\n\nstate (string): Two-letter US state code (e.g., \"CA\", \"NY\", \"TX\")\nWeather Forecast\nGet detailed weather forecast for a specific location:\n\npython\n# Example usage in MCP client\nawait call_tool(\"get_forecast\", {\n \"latitude\": 37.7749,\n \"longitude\": -122.4194\n})\nParameters:\n\nlatitude (float): Latitude coordinate\nlongitude (float): Longitude coordinate\nCommand Line Options\nUsage: axians-mcp [OPTIONS]\n\nOptions:\n -v, --verbose Increase verbosity (can be used multiple times)\n --env-file PATH Path to .env file\n --transport [stdio|sse|streamable-http]\n Transport type (default: stdio)\n --help Show this message and exit\nExamples\nGetting Weather Alerts for California\nbash\n# Start the server\naxians-mcp --transport=stdio\n\n# In your MCP client, call:\n{\n \"jsonrpc\": \"2.0\",\n \"id\": 1,\n \"method\": \"tools/call\",\n \"params\": {\n \"name\": \"get_alerts\",\n \"arguments\": {\n \"state\": \"CA\"\n }\n }\n}\nGetting Forecast for San Francisco\nbash\n# In your MCP client, call:\n{\n \"jsonrpc\": \"2.0\",\n \"id\": 2,\n \"method\": \"tools/call\",\n \"params\": {\n \"name\": \"get_forecast\",\n \"arguments\": {\n \"latitude\": 37.7749,\n \"longitude\": -122.4194\n }\n }\n}\nIntegration with MCP Clients\nThis server is compatible with any MCP client, including:\n\nClaude Desktop: Add to your MCP configuration\nCustom Applications: Use the MCP protocol to integrate weather data\nDevelopment Tools: Great for testing and development workflows\nClaude Desktop Configuration\nAdd to your MCP settings:\n\njson\n{\n \"mcpServers\": {\n \"axians-weather\": {\n \"command\": \"uvx\",\n \"args\": [\"axians-mcp\", \"--transport=stdio\"]\n }\n }\n}\nAPI Data Source\nThis server uses the National Weather Service (NWS) API, which provides:\n\nReal-time weather alerts\nDetailed forecasts\nHigh-quality, government-sourced weather data\nFree access (no API key required)\nAll data is sourced from https://api.weather.gov and follows NWS API guidelines.\n\nDevelopment\nProject Structure\nsrc/axians_mcp/\n\u251c\u2500\u2500 __init__.py # CLI entry point and main configuration\n\u251c\u2500\u2500 servers/\n\u2502 \u251c\u2500\u2500 __init__.py # Server exports\n\u2502 \u251c\u2500\u2500 main.py # FastMCP server setup\n\u2502 \u2514\u2500\u2500 weather.py # Weather tools implementation\nRunning Tests\nbash\n# Install development dependencies\nuv pip install -e \".[dev]\"\n\n# Run tests (when available)\npytest\nBuilding the Package\nbash\nuv run python -m build\nContributing\nFork the repository\nCreate a feature branch (git checkout -b feature/amazing-feature)\nCommit your changes (git commit -m 'Add amazing feature')\nPush to the branch (git push origin feature/amazing-feature)\nOpen a Pull Request\nRequirements\nPython 3.10+\nInternet connection (for NWS API access)\nDependencies\nfastmcp>=2.3.4: FastMCP framework\nhttpx>=0.28.0: HTTP client for API requests\nclick>=8.1.7: Command-line interface\npython-dotenv>=1.0.1: Environment variable management\npydantic>=2.10.6: Data validation\nLicense\nThis project is licensed under the MIT License - see the LICENSE file for details.\n\nSupport\nFor issues and questions:\n\nCheck the Issues page\nCreate a new issue with detailed information\nInclude logs and configuration details\nChangelog\nv0.1.0\nInitial release\nWeather alerts tool\nWeather forecast tool\nMultiple transport support\nFastMCP integration\n",
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