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Weather API MCP Server

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TuanKiri

A lightweight Model Context Protocol (MCP) server that enables AI assistants like Claude to retrieve and interpret real-time weather data. Discuss on Hacker News:

PublisherTuanKiri
Repositoryweather-mcp-server
LanguageGo
Forks
18
Stars
244
Available tools
0
Transport typestdio, streamable-http
Categories
LicenseMIT
Links
  • Connect tools to AI workflows

    Weather API MCP Server exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    244 stars and 18 forks from the linked repository.

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A lightweight Model Context Protocol (MCP) server that enables AI assistants like Claude to retrieve and interpret real-time weather data.

Installing on Claude Desktop

To use your MCP server with Claude Desktop, add it to your Claude configuration:

1. Local mode

json
{
  "mcpServers": {
    "weather-mcp-server": {
      "command": "/path/to/weather-mcp-server",
      "env": {
        "WEATHER_API_KEY": "your-api-key"
      }
    }
  }
}

You can get an API key from your personal account on WeatherAPI.

2. Remote mode

json
{
  "mcpServers": {
    "weather-mcp-server": {
      "url": "http://host:port/sse"
    }
  }
}

Build from source

You can use go to build the binary in the cmd/github-mcp-server directory.

shell
go build -o weather-mcp-server ./cmd/weather-mcp-server

Using MCP with Docker Containers

1. Build the Docker Image:

shell
docker build -t weather-mcp-server .

2. Run the Docker Container:

shell
docker run -e WEATHER_API_KEY=your-api-key -d --name weather-mcp-server -p 8000:8000 weather-mcp-server

Replace your-api-key with your actual WeatherAPI API key.

Tools

  • current_weather - Gets the current weather for a city

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

Project Structure

The project is organized into several key directories:

shell
├── cmd
│   └── weather-mcp-server
├── internal
│   └── server
│       ├── handlers # MCP handlers
│       ├── services # Business logic layer
│       │   ├── core # Core application logic
│       │   └── mock # Mock services for testing
│       ├── tools # MCP tools
│       └── view # Templates for displaying messages
└── pkg

Testing

If you're adding new features, please make sure to include tests for them.

1. Install the mockgen tool:

shell
go install go.uber.org/mock/mockgen@latest

See the installation guide on go.uber.org/mock.

2. Use the following command to generate mock files:

shell
make generate-mocks

3. To run unit tests:

shell
make run-tests

Contributing

Feel free to open tickets or send pull requests with improvements. Thanks in advance for your help!

Please follow the contribution guidelines.

License

This MCP server is licensed under the MIT License.

Installation

TypingMind
Prerequisites:

Node.js 18+

{
  "mcpServers": {
    "tuankiri-weather-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "weather-mcp-server"
      ]
    }
  }
}

Use Weather API MCP Server MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once Weather API MCP Server is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. You can run MCP locally on your device or connect to a remote MCP server URL.

Option 1: Use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add Weather API MCP Server as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the Weather API MCP Server MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "tuankiri-weather-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "weather-mcp-server"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the Weather API MCP Server MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the Weather API MCP Server MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use Weather API MCP Server to help me with this task?
Weather API MCP Server
Sure. I read it.
Here is what I found using Weather API MCP Server.

Option 2: Add an MCP server URL

Use this when Weather API MCP Server is already hosted remotely or your team wants one shared connector that multiple users can access.

1

Open MCP connectors

In TypingMind, go to Plugins, open MCP connectors, then choose Add URL.

  1. Open TypingMind in your browser.
  2. Go to Plugins.
  3. Open MCP connectors.
  4. Click Add URL.
TypingMind Add Custom MCP Server URL form
2

Paste the server URL

Enter your server URL in the Server URL field. Add a connection name, description, icon, custom HTTP headers, or OAuth client settings if the server requires them.

  1. Paste your server URL into the Server URL field.
  2. Enter a connection name for Weather API MCP Server.
  3. Add a description and icon if you want it to be easier to identify.
  4. Add custom HTTP headers or OAuth client details if the server requires authentication.
3

Create the connection

Click Create connection, then return to the Plugins list and confirm the new MCP connection is active.

  1. Click Create connection.
  2. Return to the MCP connectors list.
  3. Confirm the Weather API MCP Server connection appears as active.
  4. Refresh the plugin list if the connection does not appear immediately.
4

Switch models without reconnecting

Start a chat with your preferred model, enable the Weather API MCP Server tools from Plugins, and switch to another model whenever needed. The MCP connection stays available to the TypingMind workspace.

  1. Start a new chat in TypingMind.
  2. Select the AI model you want to use.
  3. Enable the Weather API MCP Server tools from Plugins.
  4. Ask the model to use the tool when needed.
  5. Switch to another AI model and reuse the same MCP connection.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use Weather API MCP Server to help me with this task?
Weather API MCP Server
Sure. I read it.
Here is what I found using Weather API MCP Server.

Frequently asked questions

What is the Weather API MCP Server MCP server used for?

Weather API MCP Server is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use Weather API MCP Server MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use Weather API MCP Server with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use Weather API MCP Server MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With Weather API MCP Server connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect Weather API MCP Server MCP to TypingMind?

Weather API MCP Server can be connected in TypingMind with the local MCP connector or by adding a remote MCP server URL. Use the local connector when the server needs access to files, apps, or private resources on your device, and use a server URL when the MCP server is hosted remotely.

What tools does Weather API MCP Server MCP provide in TypingMind?

Weather API MCP Server exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use Weather API MCP Server MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If Weather API MCP Server requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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