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mcp-meteoblue

by unixfox
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JavaScript
Remote

mcp-meteoblue

An MCP server for the meteoblue Weather API, written in JavaScript. It lets MCP clients search for locations, fetch forecasts using packages available through the Free Weather API, and request forecast meteogram images.

Tools

  • search_locations resolves cities, postal codes, and IATA/ICAO airport codes with meteoblue Location Search.

  • get_forecast accepts either a place name or coordinates and returns forecast JSON. It defaults to current, hourly, and daily weather.

  • get_forecast_image accepts either a place name or coordinates and returns a forecast image directly to the MCP client.

Place names passed to forecast or image tools are always resolved through the official meteoblue Location Search API. Forecast package inputs are restricted to the packages listed in the Free Weather API documentation.

get_forecast can restrict hourly output to a local time range. For example, tomorrow from 14:00 through 16:00 (inclusive):

{
  "location": "Paris",
  "forecastDays": 2,
  "dayOffset": 1,
  "startHour": "14:00",
  "endHour": "16:00"
}

You can use an explicit date such as 2026-08-24 instead of dayOffset. An end time earlier than the start time represents an overnight range. When a range is specified, the server requests basic-1h automatically and returns only the hourly data inside that range.

NOTE

meteoblue's current Free Weather API documentation says that images require a higher access level. The image tool is included for keys with an Image API entitlement and will return a clear authorization error otherwise.

Related MCP server: OpenWeatherMap MCP Server

Requirements

Keep the key private. This server reads it from METEOBLUE_API_KEY; it is never part of the package or MCP tool arguments.

Run from npm

Add this stdio server to your MCP client configuration:

{
  "mcpServers": {
    "meteoblue": {
      "command": "npx",
      "args": ["-y", "mcp-meteoblue"],
      "env": {
        "METEOBLUE_API_KEY": "your_api_key_here"
      }
    }
  }
}

Or run it directly:

METEOBLUE_API_KEY=your_api_key_here npx -y mcp-meteoblue

The server uses stdio, so it intentionally produces no normal terminal output while it waits for an MCP client.

Docker

Build the image locally:

docker build -t mcp-meteoblue .

Configure a Docker-based stdio server in your MCP client:

{
  "mcpServers": {
    "meteoblue": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "--env",
        "METEOBLUE_API_KEY",
        "mcp-meteoblue"
      ],
      "env": {
        "METEOBLUE_API_KEY": "your_api_key_here"
      }
    }
  }
}

The container runs as the unprivileged node user. Keep stdin open with -i because MCP communication uses stdio.

Develop locally

npm install
npm test
METEOBLUE_API_KEY=your_api_key_here npm start

Point an MCP client at node /absolute/path/to/mcp-meteoblue/src/index.js and set the environment variable in that client's configuration.

Releases

GitHub Actions runs the test suite and validates the npm tarball on Node.js 20, 22, 24, and 26 for every push and pull request. Dependabot checks npm and GitHub Actions dependencies weekly.

Pushing a v* Git tag triggers .github/workflows/publish.yml. The workflow uses npm trusted publishing (OIDC) and automatically attaches provenance. Configure the npm trusted publisher with:

  • GitHub owner: unixfox

  • Repository: mcp-meteoblue

  • Workflow: publish.yml

  • Environment: npm

No npm token is stored in GitHub when trusted publishing is configured.

API scope

The server calls only:

  • https://www.meteoblue.com/{language}/server/search/query3

  • https://my.meteoblue.com/packages/{packages}

  • https://my.meteoblue.com/images/{forecast-image-type}

It does not expose meteoblue History, Dataset, Maps, Measurements, or other APIs.

License

MIT

Available Tools

3 tools
get_forecastGet meteoblue weather forecastA

Get meteoblue forecast JSON by place name or coordinates. Place names are resolved through the Location Search API. Only packages documented for the Free Weather API are accepted.

ParametersJSON Schema
NameRequiredDescriptionDefault
languageNoen
latitudeNoWGS84 latitude; required with longitude when location is omitted
locationNoPlace name, postal code, IATA, or ICAO code; resolved with meteoblue Location Search
packagesNo
timezoneNoIANA timezone such as Europe/Paris; auto-detected when omitted
elevationNoElevation above sea level in metres
longitudeNoWGS84 longitude; required with latitude when location is omitted
countryCodeNo
historyDaysNo
forecastDaysNo
windSpeedUnitNokm/h
temperatureUnitNoC
precipitationUnitNometric

TDQS

A3.8/5.0
Behavior3/5

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

Since no annotations are given, the description carries the full burden. It discloses that place names are resolved internally and that only packages documented for the Free Weather API are accepted, but it omits rate limits, authentication expectations, potential errors, and the structure of the returned forecast JSON.

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 short, focused sentences: the first states core purpose, the second clarifies place-name behavior, and the third restricts acceptable package inputs. There is no filler or repetition.

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?

This is a 13-parameter tool with no annotations and no output schema, yet the description only covers the location and free-package constraints. It leaves important operational details—such as what package names mean, how forecastDays/historyDays interact, and what the resulting forecast JSON looks like—entirely implicit, making it hard for an agent to call correctly for varied user requests.

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 low (38%). The description contributes some meaning by framing place name and coordinates as alternative input modes, and it adds a constraint about acceptable packages. However, it does not compensate for the many undocumented parameters like historyDays, forecastDays, or the unit parameters, which are left to the schema's enum/default values only.

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 specifies a verb and resource ('Get meteoblue forecast JSON'), the output format (JSON), and the two main input modes. The word 'JSON' also immediately separates it from the image-returning sibling get_forecast_image.

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?

It clearly indicates that place names can be passed directly and are resolved via the Location Search API, which tells an agent it does not need a separate lookup first. The mention of JSON implies this is for raw data, not images, though the description does not explicitly name an alternative for those cases.

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

get_forecast_imageGet meteoblue forecast imageA

Generate a meteoblue forecast meteogram by place name or coordinates. Returns the PNG directly. Image access depends on the API key's meteoblue entitlement.

ParametersJSON Schema
NameRequiredDescriptionDefault
typeNometeogram
optionsNoImage-specific meteoblue query parameters
languageNoen
latitudeNoWGS84 latitude; required with longitude when location is omitted
locationNoPlace name, postal code, IATA, or ICAO code; resolved with meteoblue Location Search
elevationNoElevation above sea level in metres
longitudeNoWGS84 longitude; required with latitude when location is omitted
countryCodeNo

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It does usefully disclose that the response is a PNG and that access depends on the API key's meteoblue entitlement. However, it does not mention error conditions, how invalid locations are handled, or any other side effects or restrictions.

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 brief, direct, and front-loaded: a clear generation statement, the input style, the exact output format, and the access caveat. No sparse or irrelevant content is present.

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 8 parameters, no annotations, and no output schema, the description covers the essential purpose and output but misses important contextual detail: how the type/options parameters interact, whether coordinate and location inputs are mutually exclusive, and when to prefer this tool over get_forecast. It is sufficient to start, but not fully complete for an agent navigating the full tool landscape.

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 description adds a small amount of parameter meaning by saying the image can be generated by place name or coordinates, which maps to location or latitude/longitude. The schema already covers those semantics well, and the description does not explain the type enum, options object, language, countryCode, or elevation parameters, which remain somewhat ambiguous despite partial schema descriptions.

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 identifies the operation: generate a meteoblue forecast meteogram by place name or coordinates, and explicitly states the output is a PNG. This distinguishes the tool from siblings like get_forecast and search_locations, which serve different purposes.

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?

The description gives no guidance on when to use this tool over get_forecast or search_locations. It does not state whether this is the image counterpart to get_forecast, when to use it with coordinates, or whether search_locations should be called first. Only the very purpose implies an image deliverable.

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

search_locationsSearch meteoblue locationsB

Resolve a city, place, postal code, IATA code, or ICAO code to coordinates and elevation using the meteoblue Location Search API.

ParametersJSON Schema
NameRequiredDescriptionDefault
pageNo
limitNo
queryYesLocation search text
languageNoTwo-letter result languageen
countryCodeNoOptional ISO 3166-1 alpha-2 country filter

TDQS

B3.4/5.0
Behavior2/5

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

With no annotations, the description must fully disclose behavior, but it only states what the tool resolves. It does not disclose that the response likely contains multiple possible location matches, how results are ordered, or how pagination behaves. The agent cannot anticipate the reply structure before invoking the tool.

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, tightly worded sentence that front-loads the tool's purpose, accepted inputs, and output. There is no repetitive fluff, and the sentence earns its place.

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?

The tool has no output schema and no annotations, so the description should clarify result shape and usage context. It omits that the response is likely a list of candidates, how to choose between them, or how pagination works, leaving unclear behavior for an agent trying to invoke and interpret the result.

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 description adds real semantic detail for the query parameter by listing accepted input forms (city, place, postal, IATA, ICAO) beyond the schema's generic 'Location search text'. However, page and limit are undocumented in the schema and the description does not compensate for those, so the parameter semantics are only partially complete.

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 uses a specific verb ('Resolve') and resource, and clearly enumerates accepted inputs (city, place, postal code, IATA code, ICAO code) and outputs (coordinates and elevation). This makes the tool's scope unmistakable and it is clearly distinct from the forecast-based sibling tools.

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 that this tool is the location-lookup step before forecast retrieval, but it does not explicitly say when to use it versus the get_forecast siblings or when not to use it. An agent can infer the use case from the context, but the guidance is not explicit.

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. 3 tool updatesv1.0.1
    • First observedget_forecast
    • First observedget_forecast_image
    • First observedsearch_locations
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TDQS

A3.9/5.0

Scored across 3 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: location resolution, raw forecast data, and forecast image generation. The two forecast tools are differentiated by output format (JSON vs PNG), so there is no practical ambiguity.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern: search_locations, get_forecast, get_forecast_image. The naming clearly communicates both the action and the target.

Tool Count5/5

Three tools is well-scoped for a small weather API server: one for geocoding, one for data, one for imagery. Each tool serves a distinct step in the core location-to-forecast workflow.

Completeness4/5

The surface covers the essential meteorology workflow: resolve a location, retrieve forecast data, and generate a forecast image. A minor gap is the lack of separate current-conditions or historical-weather tools, but forecasts likely include current data and the core purpose is well covered.

Maintenance

ActivityMaintained
ResponsivenessNo issues

Resources

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