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Weather MCP Server

by isdaniel
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Weather MCP Server

mcp-name: io.github.isdaniel/mcp_weather_server

A Model Context Protocol (MCP) server that provides weather information using the Open-Meteo API. This server supports multiple transport modes: standard stdio, HTTP Server-Sent Events (SSE), and the new Streamable HTTP protocol for web-based integration.

Features

Weather & Air Quality

  • Get current weather information with comprehensive metrics:

    • Temperature, humidity, dew point

    • Wind speed, direction, and gusts

    • Precipitation (rain/snow) and probability

    • Atmospheric pressure and cloud cover

    • UV index and visibility

    • "Feels like" temperature

    • Sunrise and sunset times (local time at the location)

  • Get weather data for a date range with hourly details and daily sunrise/sunset times

  • Get air quality information including:

    • PM2.5 and PM10 particulate matter

    • Ozone, nitrogen dioxide, carbon monoxide

    • Sulfur dioxide, ammonia, dust

    • Aerosol optical depth

    • Health advisories and recommendations

Time & Timezone

  • Get current date/time in any timezone

  • Convert time between timezones

  • Get timezone information

Transport Modes

  • Multiple transport modes:

    • stdio - Standard MCP for desktop clients (Claude Desktop, etc.)

    • SSE - Server-Sent Events for web applications

    • streamable-http - Modern MCP Streamable HTTP protocol with stateful/stateless options

  • RESTful API endpoints via Starlette integration

Related MCP server: MCP Weather Server

Installation

Installing via Smithery

To install Weather MCP Server automatically via Smithery:

npx -y @smithery/cli install @isdaniel/mcp_weather_server

Standard Installation (for MCP clients like Claude Desktop)

This package can be installed using pip:

pip install mcp_weather_server

Manual Configuration for MCP Clients

This server is designed to be installed manually by adding its configuration to the cline_mcp_settings.json file.

  1. Add the following entry to the mcpServers object in your cline_mcp_settings.json file:

{
  "mcpServers": {
    "weather": {
      "command": "python",
      "args": [
        "-m",
        "mcp_weather_server"
      ],
      "disabled": false,
      "autoApprove": []
    }
  }
}

  1. Save the cline_mcp_settings.json file.

HTTP Server Installation (for web applications)

For HTTP SSE or Streamable HTTP support, you'll need additional dependencies:

pip install mcp_weather_server starlette uvicorn

Server Modes

This MCP server supports stdio, SSE, and streamable-http modes in a single unified server:

Mode Comparison

Feature

stdio

SSE

streamable-http

Use Case

Desktop MCP clients

Web applications (legacy)

Web applications (modern)

Protocol

Standard I/O streams

Server-Sent Events

MCP Streamable HTTP

Session Management

N/A

Stateful

Stateful or Stateless

Endpoints

N/A

/sse, /messages/

/mcp (single)

Best For

Claude Desktop, Cline

Browser-based apps

Modern web apps, APIs

State Options

N/A

Stateful only

Stateful or Stateless

1. Standard MCP Mode (Default)

The standard mode communicates via stdio and is compatible with MCP clients like Claude Desktop.

# Default mode (stdio)
python -m mcp_weather_server

# Explicitly specify stdio mode
python -m mcp_weather_server.server --mode stdio

2. HTTP SSE Mode (Web Applications)

The SSE mode runs an HTTP server that provides MCP functionality via Server-Sent Events, making it accessible to web applications.

# Start SSE server on default host/port (0.0.0.0:8080)
python -m mcp_weather_server --mode sse

# Specify custom host and port
python -m mcp_weather_server --mode sse --host localhost --port 3000

# Enable debug mode
python -m mcp_weather_server --mode sse --debug

SSE Endpoints:

  • GET /sse - SSE endpoint for MCP communication

  • POST /messages/ - Message endpoint for sending MCP requests

3. Streamable HTTP Mode (Modern MCP Protocol)

The streamable-http mode implements the new MCP Streamable HTTP protocol with a single /mcp endpoint. This mode supports both stateful (default) and stateless operations.

# Start streamable HTTP server on default host/port (0.0.0.0:8080)
python -m mcp_weather_server --mode streamable-http

# Specify custom host and port
python -m mcp_weather_server --mode streamable-http --host localhost --port 3000

# Enable stateless mode (creates fresh transport per request, no session tracking)
python -m mcp_weather_server --mode streamable-http --stateless

# Enable debug mode
python -m mcp_weather_server --mode streamable-http --debug

Streamable HTTP Features:

  • Stateful mode (default): Maintains session state across requests using session IDs

  • Stateless mode: Creates fresh transport per request with no session tracking

  • Single endpoint: All MCP communication happens through /mcp

  • Modern protocol: Implements the latest MCP Streamable HTTP specification

Streamable HTTP Endpoint:

  • POST /mcp - Single endpoint for all MCP communication (initialize, tools/list, tools/call, etc.)

Command Line Options:

--mode {stdio,sse,streamable-http}  Server mode: stdio (default), sse, or streamable-http
--host HOST                          Host to bind to (HTTP modes only, default: 0.0.0.0)
--port PORT                          Port to listen on (HTTP modes only, default: 8080)
--stateless                          Run in stateless mode (streamable-http only)
--debug                              Enable debug mode

Example SSE Usage:

// Connect to SSE endpoint
const eventSource = new EventSource('http://localhost:8080/sse');

// Send MCP tool request
fetch('http://localhost:8080/messages/', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({
    type: 'tool_call',
    tool: 'get_weather',
    arguments: { city: 'Tokyo' }
  })
});

Example Streamable HTTP Usage:

// Initialize session and call tool using Streamable HTTP protocol
async function callWeatherTool() {
  const response = await fetch('http://localhost:8080/mcp', {
    method: 'POST',
    headers: {
      'Content-Type': 'application/json'
    },
    body: JSON.stringify({
      jsonrpc: '2.0',
      method: 'tools/call',
      params: {
        name: 'get_current_weather',
        arguments: { city: 'Tokyo' }
      },
      id: 1
    })
  });

  const result = await response.json();
  console.log(result);
}

Configuration

This server does not require an API key. It uses the Open-Meteo API, which is free and open-source.

Usage

This server provides several tools for weather and time-related operations:

Available Tools

Weather Tools

  1. get_current_weather - Get current weather for a city with comprehensive metrics

  2. get_weather_by_datetime_range - Get weather data for a date range with hourly details

  3. get_weather_details - Get detailed weather information as structured JSON data

Air Quality Tools

  1. get_air_quality - Get air quality information with pollutant levels and health advice

  2. get_air_quality_details - Get detailed air quality data as structured JSON

Time & Timezone Tools

  1. get_current_datetime - Get current time in any timezone

  2. get_timezone_info - Get timezone information

  3. convert_time - Convert time between timezones

Tool Details

get_current_weather

Retrieves comprehensive current weather information for a given city with enhanced metrics.

Parameters:

  • city (string, required): The name of the city (English names only)

Returns: Detailed weather data including:

  • Temperature and "feels like" temperature

  • Humidity, dew point

  • Wind speed, direction (as compass direction), and gusts

  • Precipitation details (rain/snow) and probability

  • Atmospheric pressure and cloud cover

  • UV index with warning levels

  • Visibility

Example Response:

The weather in Tokyo is Mainly clear with a temperature of 22.5°C (feels like 21.0°C),
relative humidity at 65%, and dew point at 15.5°C. Wind is blowing from the NE at 12.5 km/h
with gusts up to 18.5 km/h. Atmospheric pressure is 1013.2 hPa with 25% cloud cover.
UV index is 5.5 (Moderate). Visibility is 10.0 km.

get_weather_by_datetime_range

Retrieves hourly weather information with comprehensive metrics for a specified city between start and end dates.

Parameters:

  • city (string, required): The name of the city (English names only)

  • start_date (string, required): Start date in format YYYY-MM-DD (ISO 8601)

  • end_date (string, required): End date in format YYYY-MM-DD (ISO 8601)

Returns: Comprehensive weather analysis including:

  • Hourly weather data with all enhanced metrics

  • Temperature trends (highs, lows, averages)

  • Precipitation patterns and probabilities

  • Wind conditions assessment

  • UV index trends

  • Weather warnings and recommendations

Example Response:

[Analysis of weather trends over 2024-01-01 to 2024-01-07]
- Temperature ranges from 5°C to 15°C
- Precipitation expected on Jan 3rd and 5th (60% probability)
- Wind speeds averaging 15 km/h from SW direction
- UV index moderate (3-5) throughout the period
- Recommendation: Umbrella needed for midweek

get_weather_details

Get detailed weather information for a specified city as structured JSON data for programmatic use.

Parameters:

  • city (string, required): The name of the city (English names only)

Returns: Raw JSON data with all weather metrics suitable for processing and analysis

get_air_quality

Get current air quality information for a specified city with pollutant levels and health advisories.

Parameters:

  • city (string, required): The name of the city (English names only)

  • variables (array, optional): Specific pollutants to retrieve. Options:

    • pm10 - Particulate matter ≤10μm

    • pm2_5 - Particulate matter ≤2.5μm

    • carbon_monoxide - CO levels

    • nitrogen_dioxide - NO2 levels

    • ozone - O3 levels

    • sulphur_dioxide - SO2 levels

    • ammonia - NH3 levels

    • dust - Dust particle levels

    • aerosol_optical_depth - Atmospheric turbidity

Returns: Comprehensive air quality report including:

  • Current pollutant levels with units

  • Air quality classification (Good/Moderate/Unhealthy/Hazardous)

  • Health recommendations for general population

  • Specific warnings for sensitive groups

  • Comparison with WHO and EPA standards

Example Response:

Air quality in Beijing (lat: 39.90, lon: 116.41):
PM2.5: 45.3 μg/m³ (Unhealthy for Sensitive Groups)
PM10: 89.2 μg/m³ (Moderate)
Ozone (O3): 52.1 μg/m³
Nitrogen Dioxide (NO2): 38.5 μg/m³
Carbon Monoxide (CO): 420.0 μg/m³

Health Advice: Sensitive groups (children, elderly, people with respiratory conditions)
should limit outdoor activities.

get_air_quality_details

Get detailed air quality information as structured JSON data for programmatic analysis.

Parameters:

  • city (string, required): The name of the city (English names only)

  • variables (array, optional): Specific pollutants to retrieve (same options as get_air_quality)

Returns: Raw JSON data with complete air quality metrics and hourly data

get_current_datetime

Retrieves the current time in a specified timezone.

Parameters:

  • timezone_name (string, required): IANA timezone name (e.g., 'America/New_York', 'Europe/London'). Use UTC if no timezone provided.

Returns: Current date and time in the specified timezone

Example:

{
  "timezone": "America/New_York",
  "current_time": "2024-01-15T14:30:00-05:00",
  "utc_time": "2024-01-15T19:30:00Z"
}

get_timezone_info

Get information about a specific timezone.

Parameters:

  • timezone_name (string, required): IANA timezone name

Returns: Timezone details including offset and DST information

convert_time

Convert time from one timezone to another.

Parameters:

  • time_str (string, required): Time to convert (ISO format)

  • from_timezone (string, required): Source timezone

  • to_timezone (string, required): Target timezone

Returns: Converted time in target timezone

MCP Client Usage Examples

Using with Claude Desktop or MCP Clients

<use_mcp_tool>
<server_name>weather</server_name>
<tool_name>get_current_weather</tool_name>
<arguments>
{
  "city": "Tokyo"
}
</arguments>
</use_mcp_tool>
<use_mcp_tool>
<server_name>weather</server_name>
<tool_name>get_weather_by_datetime_range</tool_name>
<arguments>
{
  "city": "Paris",
  "start_date": "2024-01-01",
  "end_date": "2024-01-07"
}
</arguments>
</use_mcp_tool>
<use_mcp_tool>
<server_name>weather</server_name>
<tool_name>get_current_datetime</tool_name>
<arguments>
{
  "timezone_name": "Europe/Paris"
}
</arguments>
</use_mcp_tool>
<use_mcp_tool>
<server_name>weather</server_name>
<tool_name>get_air_quality</tool_name>
<arguments>
{
  "city": "Beijing"
}
</arguments>
</use_mcp_tool>
<use_mcp_tool>
<server_name>weather</server_name>
<tool_name>get_air_quality</tool_name>
<arguments>
{
  "city": "Los Angeles",
  "variables": ["pm2_5", "pm10", "ozone"]
}
</arguments>
</use_mcp_tool>

Web Integration (SSE Mode)

When running in SSE mode, you can integrate the weather server with web applications:

HTML/JavaScript Example

<!DOCTYPE html>
<html>
<head>
    <title>Weather MCP Client</title>
</head>
<body>
    <div id="weather-data"></div>
    <script>
        // Connect to SSE endpoint
        const eventSource = new EventSource('http://localhost:8080/sse');

        eventSource.onmessage = function(event) {
            const data = JSON.parse(event.data);
            document.getElementById('weather-data').innerHTML = JSON.stringify(data, null, 2);
        };

        // Function to get weather
        async function getWeather(city) {
            const response = await fetch('http://localhost:8080/messages/', {
                method: 'POST',
                headers: { 'Content-Type': 'application/json' },
                body: JSON.stringify({
                    jsonrpc: '2.0',
                    method: 'tools/call',
                    params: {
                        name: 'get_current_weather',
                        arguments: { city: city }
                    },
                    id: 1
                })
            });
        }

        // Example: Get weather for Tokyo
        getWeather('Tokyo');

        // Example: Get air quality
        async function getAirQuality(city) {
            const response = await fetch('http://localhost:8080/messages/', {
                method: 'POST',
                headers: { 'Content-Type': 'application/json' },
                body: JSON.stringify({
                    jsonrpc: '2.0',
                    method: 'tools/call',
                    params: {
                        name: 'get_air_quality',
                        arguments: { city: city }
                    },
                    id: 2
                })
            });
        }

        getAirQuality('Beijing');
    </script>
</body>
</html>

Docker Deployment

The project is available as a Docker image on Docker Hub and includes configurations for easy deployment.

Quick Start with Docker Hub

Pull and run the latest image directly from Docker Hub:

# Pull the latest image
docker pull dog830228/mcp_weather_server:latest

# Run in stdio mode (default)
docker run dog830228/mcp_weather_server:latest

# Run in SSE mode on port 8080
docker run -p 8080:8080 dog830228/mcp_weather_server:latest --mode sse

# Run in streamable-http mode on port 8080
docker run -p 8080:8080 dog830228/mcp_weather_server:latest --mode streamable-http

# Pull a specific version
docker pull dog830228/mcp_weather_server:0.5.0
docker run -p 8080:8080 dog830228/mcp_weather_server:0.5.0 --mode sse

Available Docker Images

  • Latest: dog830228/mcp_weather_server:latest

  • Versioned: dog830228/mcp_weather_server:<version> (e.g., 0.5.0)

Images are automatically built and published when new versions are released.

Building from Source

If you want to build the Docker image yourself:

Standard Build

# Build
docker build -t mcp-weather-server:sse .

# Run (port will be read from PORT env var, defaults to 8081)
docker run -p 8081:8081 mcp-weather-server:sse

# Run with custom port
docker run -p 8080:8080 mcp-weather-server:local --mode sse

Streamable HTTP Build

# Build using streamable-http Dockerfile
docker build -f Dockerfile.streamable-http -t mcp-weather-server:streamable-http .

# Run in stateful mode
docker run -p 8080:8080 mcp-weather-server:streamable-http

# Run in stateless mode
docker run -p 8080:8080 -e STATELESS=true mcp-weather-server:streamable-http

Development

Project Structure

mcp_weather_server/
├── src/
│   └── mcp_weather_server/
│       ├── __init__.py
│       ├── __main__.py          # Main MCP server entry point
│       ├── server.py            # Unified server (stdio, SSE, streamable-http)
│       ├── utils.py             # Utility functions
│       └── tools/               # Tool implementations
│           ├── __init__.py
│           ├── toolhandler.py   # Base tool handler
│           ├── tools_weather.py # Weather-related tools
│           ├── tools_time.py    # Time-related tools
│           ├── tools_air_quality.py # Air quality tools
│           ├── weather_service.py   # Weather API service
│           └── air_quality_service.py # Air quality API service
├── tests/
├── Dockerfile                   # Docker configuration for SSE mode
├── Dockerfile.streamable-http   # Docker configuration for streamable-http mode
├── pyproject.toml
├── requirements.txt
└── README.md

Running for Development

Standard MCP Mode (stdio)

# From project root
python -m mcp_weather_server

# Or with PYTHONPATH
export PYTHONPATH="/path/to/mcp_weather_server/src"
python -m mcp_weather_server

SSE Server Mode

# From project root
python -m mcp_weather_server --mode sse --host 0.0.0.0 --port 8080

# With custom host/port
python -m mcp_weather_server --mode sse --host localhost --port 3000

Streamable HTTP Mode

# Stateful mode (default)
python -m mcp_weather_server --mode streamable-http --host 0.0.0.0 --port 8080

# With debug logging
python -m mcp_weather_server --mode streamable-http --debug

Adding New Tools

To add new weather or time-related tools:

  1. Create a new tool handler in the appropriate file under tools/

  2. Inherit from the ToolHandler base class

  3. Implement the required methods (get_name, get_description, call)

  4. Register the tool in server.py

Dependencies

Core Dependencies

  • mcp>=1.0.0 - Model Context Protocol implementation

  • httpx>=0.28.1 - HTTP client for API requests

  • python-dateutil>=2.8.2 - Date/time parsing utilities

SSE Server Dependencies

  • starlette - ASGI web framework

  • uvicorn - ASGI server

Development Dependencies

  • pytest - Testing framework

API Data Sources

This server uses free and open-source APIs:

Weather Data: Open-Meteo Weather API

  • Free and open-source

  • No API key required

  • Provides accurate weather forecasts

  • Supports global locations

  • Historical and current weather data

  • Comprehensive metrics (wind, precipitation, UV, visibility)

Air Quality Data:

  • Free and open-source

  • No API key required

  • Real-time air quality data

  • Multiple pollutant measurements (PM2.5, PM10, O3, NO2, CO, SO2)

  • Global coverage

  • Health-based air quality indices

Troubleshooting

Common Issues

1. City not found

  • Ensure city names are in English

  • Try using the full city name or include country (e.g., "Paris, France")

  • Check spelling of city names

2. HTTP Server not accessible (SSE or Streamable HTTP)

  • Verify the server is running with the correct mode:

    • SSE: python -m mcp_weather_server --mode sse

    • Streamable HTTP: python -m mcp_weather_server --mode streamable-http

  • Check firewall settings for the specified port

  • Ensure all dependencies are installed: pip install starlette uvicorn

  • Verify the correct endpoint:

    • SSE: http://localhost:8080/sse and http://localhost:8080/messages/

    • Streamable HTTP: http://localhost:8080/mcp

3. MCP Client connection issues

  • Verify Python path in MCP client configuration

  • Check that mcp_weather_server package is installed

  • Ensure Python environment has required dependencies

4. Date format errors

  • Use ISO 8601 format for dates: YYYY-MM-DD

  • Ensure start_date is before end_date

  • Check that dates are not too far in the future

Error Responses

The server returns structured error messages:

{
  "error": "Could not retrieve coordinates for InvalidCity."
}

Available Tools

8 tools
convert_timeB

Convert time from one timezone to another.

ParametersJSON Schema
NameRequiredDescriptionDefault
datetime_strYesDateTime string in ISO format (e.g., '2024-01-15T14:30:00') or 'now' for current time
from_timezoneYesSource timezone (IANA timezone name)
to_timezoneYesTarget timezone (IANA timezone name)

TDQS

B3.4/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, and the description gives minimal behavioral info. It does not disclose return values, error handling, or edge cases like DST or invalid timezones.

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 a single sentence with no wasted words, effectively communicating the core purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Missing key context like return format and error handling, given no output schema. The description is too brief for a conversion tool that may need to clarify behavior.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions for all parameters. The description adds no additional meaning beyond what the schema already provides.

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 clearly states the tool converts time between timezones, which is a specific verb+resource. It distinguishes from sibling tools like get_current_datetime and get_timezone_info.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not explicitly state when to use this tool vs alternatives. Context from siblings implies usage, but no clear when-not-to-use or alternative mentions are provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_air_qualityA

Get air quality information for a specified city including PM2.5, PM10, ozone, nitrogen dioxide, carbon monoxide, and other pollutants. Provides health advisories based on current air quality levels.

ParametersJSON Schema
NameRequiredDescriptionDefault
cityYesThe name of the city to fetch air quality information for, PLEASE NOTE English name only, if the parameter city isn't English please translate to English before invoking this function.
variablesNoAir quality variables to retrieve. If not specified, defaults to pm10, pm2_5, ozone, nitrogen_dioxide, and carbon_monoxide.

TDQS

A4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description bears the full burden. It lists the pollutants returned and mentions health advisories, but does not disclose any behavioral traits such as data freshness, units, potential errors, or rate limits. It is adequate but lacks depth.

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 two sentences, front-loaded with the purpose, and contains no unnecessary words. Every sentence adds value and is well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simple parameter set (2 params) and no output schema, the description is fairly complete. It explains available variables and default behavior. It could be improved by mentioning the output format or example usage, but it is sufficient for a basic retrieval tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% coverage with descriptions for both parameters. The description adds crucial context: for the 'city' parameter, it instructs to translate non-English names to English, and for 'variables', it specifies the defaults. This goes beyond the schema definitions.

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 clearly states the tool's function: getting air quality information for a specified city, including specific pollutants and health advisories. It distinguishes itself from sibling tools like 'get_air_quality_details' and weather/time tools by focusing on air quality data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a clear context for when to use the tool (to get air quality info) but does not explicitly state when not to use it or how it differs from the sibling 'get_air_quality_details'. No exclusions or alternatives are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_air_quality_detailsB

Get detailed air quality information for a specified city as structured JSON data. This tool provides raw air quality data for programmatic analysis and processing.

ParametersJSON Schema
NameRequiredDescriptionDefault
cityYesThe name of the city to fetch air quality information for, PLEASE NOTE English name only, if the parameter city isn't English please translate to English before invoking this function.
variablesNoAir quality variables to retrieve

TDQS

B3.4/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided; description only says it provides raw data. Does not disclose any behavioral traits such as rate limits, authentication requirements, or data freshness. For a read-only tool this is minimal.

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?

Two concise sentences with a clear statement of purpose and usage context. Some whitespace formatting but no unnecessary content.

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?

Given the tool has only two parameters and no output schema, the description covers the basic purpose and output format. However, it could specify data freshness or whether it returns current or historical data.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers 100% of parameters with descriptions. The description does not add significant meaning beyond schema, aside from reinforcing the 'English name only' hint already present in the city parameter.

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?

Clearly states verb 'Get' and resource 'detailed air quality information' with output format 'structured JSON data'. Distinguishes from sibling 'get_air_quality' which likely provides simpler data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Indicates it provides raw data for programmatic use, but does not explicitly differentiate from 'get_air_quality' or specify when to use this tool over others.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_current_datetimeA

Get current time in specified timezone.

ParametersJSON Schema
NameRequiredDescriptionDefault
timezone_nameYesIANA timezone name (e.g., 'America/New_York', 'Europe/London'). Use UTC timezone if no timezone provided by the user.

TDQS

A3.6/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must disclose behavior. It states the tool returns the current time, but does not specify that it relies on server time, that it's read-only, or any other behavioral traits. For a simple read operation, this is adequate but minimal.

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 a single, concise sentence that immediately conveys the tool's purpose. No redundant information, and it is front-loaded with the primary action.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (one parameter, no output schema), the description is largely complete. It could benefit from a slight elaboration to differentiate from sibling tools, but it sufficiently covers the core functionality.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description does not add meaning beyond the schema, which already provides an example and fallback instruction. The tool description itself is too brief to enhance parameter understanding.

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 clearly states the tool gets the current time in a specified timezone. However, it doesn't differentiate from sibling tools like 'convert_time' or 'get_timezone_info', which could be used for related purposes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for obtaining current time in a timezone but provides no explicit guidance on when to use this tool versus alternatives like 'get_timezone_info' or 'convert_time'. No exclusion criteria are given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_current_weatherA

Get current weather information for a specified city. It extracts the current hour's temperature and weather code, maps the weather code to a human-readable description, and returns a formatted summary.

ParametersJSON Schema
NameRequiredDescriptionDefault
cityYesThe name of the city to fetch weather information for, PLEASE NOTE English name only, if the parameter city isn't English please translate to English before invoking this function.

TDQS

A4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Describes the processing steps (extracting current hour's temperature, mapping weather code) and the return format. Without annotations, this provides adequate behavioral transparency.

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?

Three lines, front-loaded with the core purpose, no waste. Efficiently communicates functionality.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple one-parameter tool without output schema, the description covers the essential behavior and output format. Lacks details on error handling or unavailable cities, but acceptable.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool description itself does not discuss the city parameter; the input schema's parameter description already provides full guidance (including translation note). Baseline 3 due to 100% schema coverage.

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?

Clearly states it gets current weather for a city and describes the output (temperature, weather code, summary). Differentiates from sibling tools like get_weather_details or get_weather_byDateTimeRange.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implies use for current weather but does not explicitly state when to use versus alternatives or provide exclusions (e.g., historical data, forecasts).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_timezone_infoA

Get information about a specific timezone including current time and UTC offset.

ParametersJSON Schema
NameRequiredDescriptionDefault
timezone_nameYesIANA timezone name (e.g., 'America/New_York', 'Europe/London')

TDQS

A3.7/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. It mentions return of current time and offset, but doesn't discuss error handling, behavior on invalid timezone names, or any other side effects. Adequate but not comprehensive.

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?

Single sentence, efficient, no redundant content. Could be slightly more informative without increasing length, but remains appropriately concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given a single parameter and no output schema, the description fully explains purpose and return content. However, specifying output format (e.g., JSON fields) would enhance completeness. Overall, sufficient for a simple tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema coverage and a single parameter already described, the description adds minimal value beyond restating 'including current time and UTC offset'. It does not elaborate on parameter format or constraints.

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 clearly states the tool gets information about a specific timezone including current time and UTC offset. It uses a specific verb 'Get' and resource 'timezone info', distinguishing it from sibling tools like convert_time or get_current_datetime.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when timezone info is needed, but lacks explicit when-to-use, when-not-to-use, or references to alternatives. No guidance on when to prefer this over sibling tools like convert_time.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_weather_byDateTimeRangeB

Get weather information for a specified city between start and end dates.

ParametersJSON Schema
NameRequiredDescriptionDefault
cityYesThe name of the city to fetch weather information for, PLEASE NOTE English name only, if the parameter city isn't English please translate to English before invoking this function.
start_dateYesStart date in format YYYY-MM-DD, please follow ISO 8601 format
end_dateYesEnd date in format YYYY-MM-DD , please follow ISO 8601 format

TDQS

B3.3/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full behavioral burden but only states the basic function. No disclosure of traits like data source, update frequency, error handling, or what happens if dates span gaps. Minimal value beyond the name.

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?

A single sentence of 11 words that is efficient and front-loads the purpose. Every word earns its place; no redundancy or fluff.

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?

Given the low complexity of a date-range weather tool with no output schema, the description is minimally adequate. However, it could mention the return format (e.g., temperature, conditions) or that it covers the full range. Lacks completeness but not severely.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters. The description does not add meaning beyond the schema; it merely restates the overall purpose. Baseline 3 is appropriate.

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 clearly states the action (Get), the resource (weather information), and the scope (for a specified city between start and end dates). It distinguishes itself from siblings like get_current_weather and get_weather_details by specifying a date range.

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 on when to use this tool vs alternatives (e.g., get_current_weather for current conditions, get_weather_details for more detail). The description does not provide when-not-to-use or mention any prerequisites or limitations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_weather_detailsB

Get detailed weather information for a specified city as structured JSON data. This tool provides raw weather data for programmatic analysis and processing.

ParametersJSON Schema
NameRequiredDescriptionDefault
cityYesThe name of the city to fetch weather information for, PLEASE NOTE English name only, if the parameter city isn't English please translate to English before invoking this function.
include_forecastNoWhether to include forecast data (next 24 hours)

TDQS

B3.4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description alone must convey behavior. It indicates the output is structured JSON and intended for analysis, but does not disclose specifics like data fields, potential errors, or rate limits. The lack of behavioral details leaves the agent with incomplete expectations.

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 concise with only two sentences, front-loading the core purpose. Every sentence serves a clear purpose without redundancy or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with two well-documented parameters and no output schema, the description is complete enough for basic usage. It would benefit from mentioning output structure (e.g., JSON fields) but is not critically lacking given the schema's thoroughness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema provides complete descriptions for both parameters (city and include_forecast) with 100% coverage. The description adds no additional semantic value beyond what the schema already offers, so a baseline score of 3 is appropriate.

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 clearly states the tool provides detailed weather information as structured JSON data, using specific verbs ('get', 'provides') and specifying the resource (weather data). However, it does not explicitly distinguish itself from sibling tools like 'get_current_weather', which may also return weather data.

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 provided on when to use this tool versus alternatives like 'get_current_weather' or 'get_weather_byDateTimeRange'. The description implies it is for programmatic analysis but does not state exclusions or context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.5/5.0
Disambiguation3/5

Some tools have overlapping purposes, such as get_current_weather vs get_weather_details and get_air_quality vs get_air_quality_details, which differ only in output format. Time-related tools (convert_time, get_current_datetime, get_timezone_info) also overlap in functionality, potentially confusing an agent.

Naming Consistency3/5

Most tools follow a `get_<resource>` pattern in snake_case, but `get_weather_byDateTimeRange` mixes casing (DateTime) and deviates from the pure snake_case convention. This inconsistency partially undermines naming predictability.

Tool Count4/5

With 8 tools covering weather, air quality, and time operations, the count is appropriate for the server's scope. It is neither too sparse nor overly large, though some tools could be consolidated.

Completeness4/5

The tool set covers current weather, weather over a date range, air quality (both summary and details), and time-related features. Missing forecast-specific tools are partially addressed by the date range tool, making it fairly complete for a weather/time server.

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