A
licenseB
qualityD
maintenanceEnables AI assistants to access real-time US weather forecasts and alerts through the National Weather Service API.
2
5 npm
MIT
Weather MCP Server
by 00aimlds00
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 Serverwhat's the forecast for Austin, Texas?"
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 exposes weather tools — `get_forecast` and `get_alerts` — backed by the US National Weather Service API.
## Setup
uv sync
## Usage
Run standalone to verify it starts correctly:
uv run weather.py
Or connect to it from an MCP client, e.g. the companion [mcp-client](https://github.com/00aimlds00/mcp-client):
uv run client.py path/to/weather.py
## Tools
- **get_forecast(latitude, longitude)** — returns the weather forecast for a US location
- **get_alerts(state)** — returns active weather alerts for a US state (two-letter code)
## Note
Data is sourced from the US National Weather Service, so coverage is limited to US locations.
## Requirements
- Python (see `.python-version`)
## License
MITAvailable 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
v0.1.0- First observed
get_alerts - First observed
get_forecast
TDQS
B3.4/5.0
Scored across 2 tools
Disambiguation5/5
get_alerts and get_forecast have entirely distinct purposes: one retrieves weather alerts for a state, the other retrieves forecasts for coordinates. There is no overlap or potential confusion between them.
Naming Consistency5/5
Both tools follow the same get_noun pattern, making the naming scheme predictable and internally consistent. Even with just two tools, the convention is clear.
Tool Count3/5
Two tools falls into the borderline range for a weather service. While the tools are both useful, the count feels thin for a general-purpose weather server that would typically also include current conditions or location-based search.
Completeness3/5
The server covers alerts and forecasts, but lacks other common weather operations such as current conditions, hourly forecasts, or marine weather. These are notable gaps, though the two existing tools cover important requested functionality.
Maintenance
ActivityMaintained
ResponsivenessNo issues
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