F
licenseNot graded
qualityD
maintenanceProvides weather forecast and alert data for US locations through the National Weather Service API, enabling access to real-time weather alerts by state and detailed forecasts by coordinates.
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Weather MCP Server
by Zachwitte21
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Weather MCP Serverget alerts for California"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Weather MCP Server
An MCP (Model Context Protocol) server that provides weather information tools using the National Weather Service (NWS) API.
Features
This MCP server exposes two tools for accessing weather data:
get_alerts: Get active weather alerts for any US stateget_forecast: Get detailed weather forecast for a specific location (latitude/longitude)
Related MCP server: Weather MCP Server
Requirements
Python >= 3.14
uv (recommended for dependency management)
Setup
Clone this repository or download the source code
Install dependencies using uv:
uv syncRunning the Server
The server runs using stdio transport for MCP communication:
uv run weather.pyUsing with MCP Clients
To use this server with an MCP client (like Claude Desktop), add it to your MCP client configuration:
{
"mcpServers": {
"weather": {
"command": "uv",
"args": [
"--directory",
"c:\\Users\\Zachary\\Dev\\weather",
"run",
"weather.py"
]
}
}
}Available Tools
get_alerts
Get active weather alerts for a US state.
Parameters:
state(string): Two-letter US state code (e.g., "CA", "NY", "TX")
Example:
get_alerts(state="CA")get_forecast
Get weather forecast for a specific location.
Parameters:
latitude(float): Latitude of the locationlongitude(float): Longitude of the location
Example:
get_forecast(latitude=37.7749, longitude=-122.4194)Data Source
This server uses the National Weather Service API, which provides free weather data for US locations.
License
Add your license information here.
Available Tools
2 toolsget_alertsA
Get weather alerts for a US state.
Args: state: Two-letter US state code (e.g. CA, NY)
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| state | Yes |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
A4.4/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. 'Get' implies a read-only operation, but the description does not explicitly state side-effect-free behavior or any caveats about alert types or data source. It is not misleading, but it adds minimal behavioral context beyond what the name implies.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, with a front-loaded purpose statement followed by a compact Args block. Every sentence earns its place and there is no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With a single well-documented parameter, an output schema, and no siblings, the description plus schema fully covers what an agent needs to invoke the tool correctly. No missing context for this simple operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description fully compensates by specifying the parameter format ('Two-letter US state code') and providing concrete examples ('CA, NY'). This adds real meaning beyond the raw schema type string.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Get'), a clear resource ('weather alerts'), and a clear scope ('US state'). It is unambiguous and leaves no doubt about what the tool does, even without siblings to differentiate from.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There are no sibling tools, so explicit routing guidance is unnecessary. The description clearly implies usage: when you need weather alerts for a US state. It lacks explicit exclusions, but nothing is misleading or missing for a tool of this simplicity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_forecastC
Get weather forecast for a location.
Args: latitude: Latitude of the location longitude: Longitude of the location
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| latitude | Yes | ||
| longitude | Yes |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
C2.8/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description must carry behavioral context. It only says 'get' a forecast and gives no indication of units, time range, coordinate format, or whether this is a read-only operation. Nothing contradicts annotations, but little is disclosed beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and the core purpose is front-loaded. The Args block is somewhat redundant with the schema but does not add significant bloat, keeping the overall entry compact.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description provides the essential call requirements (latitude and longitude) and the presence of an output schema reduces the need to document return values. However, it omits practical context like expected coordinate units, available forecast periods, and why an agent would choose this over get_alerts.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The Args section repeats the parameter names with minimal glosses ('Latitude of the location'), adding almost no meaning beyond the schema titles. Since schema description coverage is 0%, the description should compensate with coordinate format or range details, but it does not.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a clear verb and resource: 'Get weather forecast for a location'. It does not explicitly mention the sibling get_alerts, but the forecast-vs-alerts distinction is clear enough from the domain.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given about when to use this tool instead of get_alerts, nor are any exclusions or alternative conditions provided. The intended usage is only implied by the tool name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
2 tool updates
- First observed
get_alerts - First observed
get_forecast
TDQS
B3.1/5.0
Scored across 2 tools
Disambiguation5/5
The two tools have completely distinct purposes: get_alerts retrieves weather alerts for US states, while get_forecast provides forecasts for geographic coordinates. There is no overlap in functionality or target data, making them easily distinguishable.
Naming Consistency5/5
Both tools follow a consistent verb_noun pattern with 'get_' prefix (get_alerts, get_forecast). The naming is perfectly uniform and predictable across the tool set.
Tool Count2/5
With only two tools, this server feels severely under-scoped for a weather domain. A weather server should ideally include tools for current conditions, historical data, radar, or multiple forecast types, making this minimal set inadequate for comprehensive weather interactions.
Completeness2/5
The tool surface is highly incomplete for a weather server. It lacks fundamental operations like getting current conditions, historical weather, radar imagery, or air quality data. Agents will face significant gaps when trying to perform common weather-related tasks.
Maintenance
ActivityInactive
ResponsivenessNo issues
Related MCP Connectors
Get US weather forecasts, active alerts, and current observations.
US weather alerts (NWS): warnings, watches. $0.01/query. Register in-session — free testnet funds.
US weather & geo for AI agents: forecasts, alerts, earthquakes, elevation, geocoding. No keys.
US weather & geo for AI agents: forecasts, alerts, earthquakes, elevation, geocoding. No keys.
Related MCP Servers
- AlicenseNot gradedqualityDmaintenanceProvides access to National Weather Service (NWS) data, enabling users to retrieve active weather alerts for US states and weather forecasts for specific geographic coordinates.55MIT
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