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Amann001

Weather MCP Server

by Amann001
OverviewSchemaSourceRelated ServersScoreDiscussionsAdmin
Python
Remote

Weather MCP Server

A mini project demonstrating how to build and use a Model Context Protocol (MCP) server with Python.

Features

  • Weather Alerts Tool

  • Weather Forecast Tool

  • SSE Transport

  • STDIO Transport

  • MCP Client Integration

  • Docker Support

  • Async Python Implementation

Related MCP server: Weather MCP Server

Project Structure

mcpcrashcourse/
│
├── server/
│   └── mcpserver/
│       ├── server.py
│       ├── client-sse.py
│       ├── client-stdio.py
│       ├── Dockerfile
│       └── requirements.txt
│
├── weather.py
├── weather.json
├── client.py
├── README.md
├── pyproject.toml
└── uv.lock

Tools

get_alerts

Returns active weather alerts for a US state.

Example:

get_alerts("CA")

get_forecast

Returns forecast information based on latitude and longitude.

Example:

get_forecast(
    latitude=37.7749,
    longitude=-122.4194
)

Transports

STDIO

Used for local MCP communication.

SSE

Used for remote communication through HTTP.

Running the Server

STDIO

uv run server/mcpserver/server.py

SSE

Configure transport as:

mcp.run(transport="sse")

Then:

uv run server/mcpserver/server.py

Running Clients

SSE Client

uv run server/mcpserver/client-sse.py

STDIO Client

uv run server/mcpserver/client-stdio.py

Docker

Build:

docker build -t weather-mcp .

Run:

docker run weather-mcp

Technologies Used

  • Python

  • MCP

  • FastMCP

  • HTTPX

  • AsyncIO

  • Docker

  • SSE

  • STDIO

Learning Outcomes

  • Building MCP tools

  • Creating MCP servers

  • Working with MCP clients

  • Using SSE transport

  • Using STDIO transport

  • Tool invocation

  • Agent-tool communication

  • Dockerizing MCP applications

Available Tools

2 tools
get_alertsA

Get weather alerts for a US state.

Args: state: Two-letter US state code (e.g. CA, NY)

ParametersJSON Schema
NameRequiredDescriptionDefault
stateYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

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
NameRequiredDescriptionDefault
latitudeYes
longitudeYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

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.

  1. 2 tool updatesv0.1.0
    • First observedget_alerts
    • First observedget_forecast
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TDQS

A3.5/5.0

Scored across 2 tools

Disambiguation5/5

The two tools have clearly distinct purposes: one retrieves alerts by state, the other provides forecasts by coordinates. There is no functional overlap or ambiguity.

Naming Consistency5/5

Both tools follow a consistent 'get_noun' pattern with snake_case, making the names predictable and easy to understand.

Tool Count4/5

With only two tools, the server is minimal but still covers two core weather functionalities. It feels slightly thin but is acceptable for a focused server.

Completeness3/5

The server covers alerts and forecasts but lacks current conditions, historical data, or other common weather endpoints. Notable gaps exist, but the core stated purpose is partially met.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Connectors

Related MCP Servers

  • Weather MCP Server

    cemremengu
    F
    license
    Not graded
    quality
    D
    maintenance
    Provides weather information tools based on the National Weather Service APIs through an SSE-based MCP server that can run as a standalone process or Docker container.
    -

  • Weather MCP Server

    ajayamal
    A
    license
    Not graded
    quality
    D
    maintenance
    Provides weather forecasts and active alerts for US locations using the National Weather Service API. It supports both local stdio and remote HTTP/SSE transport modes for flexible integration with MCP clients.
    36
    GPL 3.0