Click on "Install 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., "@my-weather-server-0706 What's the weather in Tokyo?"
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.
MCP server for querying current weather by city. It uses Open-Meteo geocoding and forecast APIs, and exposes one MCP tool: get_weather.
get_weatherGet current weather for a city.
Input:
{
"city": "上海"
}Output:
通过 my-weather-server-0706 返回：上海 当前天气是：阴天
定位：上海，上海市，中国
温度：...
体感温度：...
湿度：...
降水：...
云量：...
风速：...
风向：...
更新时间：...Related MCP server: mcp-multi-weather
From GitHub:
npx -y github:yangvue/my-weather-server-0706From npm, once published:
npx -y open-meteo-mcp-weather-serverFrom this repository:
npm install
npm startUse this config to run from GitHub:
{
"mcpServers": {
"my-weather-server-0706": {
"command": "npx",
"args": ["-y", "github:yangvue/my-weather-server-0706"]
}
}
}Use this config after the package is published to npm:
{
"mcpServers": {
"my-weather-server-0706": {
"command": "npx",
"args": ["-y", "open-meteo-mcp-weather-server"]
}
}
}Use this config when running from a local checkout:
{
"mcpServers": {
"my-weather-server-0706": {
"command": "node",
"args": ["/absolute/path/to/my-mcp-server/index.js"]
}
}
}Geocoding: Open-Meteo Geocoding API
Weather: Open-Meteo Forecast API
No API key is required.
MIT
通过 my-weather-server-0706 获取指定城市的当前真实天气
| Name | Required | Description | Default |
|---|---|---|---|
| city | Yes | 城市名称 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. However, it only states the basic function and gives no information about side effects (though likely none), return format, error behavior, or server constraints. The mention of 'my-weather-server-0706' adds little transparency about how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is concise and front-loaded with the core action. It contains no fluff or redundant information beyond the necessary, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (one parameter, no output schema), so the description covers the basic purpose. However, since there is no output schema, the description should ideally mention what 'current real weather' returns (e.g., temperature, conditions) to fully inform the agent, but it does not. This leaves a moderate gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents the 'city' parameter with a description ('城市名称'). The description only repeats this by saying '指定城市' and adds no additional meaning about parameter format, allowed values, or defaults. With 100% schema coverage, the baseline is 3, and the description does not elevate it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: '获取指定城市的当前真实天气' (get current real weather for a specified city). It uses a specific verb ('获取') and resource ('当前真实天气'), making the purpose unambiguous. Although there are no sibling tools to differentiate from, the description is precise and actionable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage ('use this to get weather for a city') but provides no explicit when-to-use guidance, exclusions, or alternatives. For a simple tool this may be sufficient, but the description does not state any prerequisites or conditions beyond having a city name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v1.1.0get_weatherOnly one tool exists, so there is no possibility of confusing it with another. The purpose is clearly scoped to fetching current weather.
The single tool name follows a clear verb_noun pattern (get_weather), and there are no other tools to deviate from this convention.
With just one tool, the server feels thin for a general 'weather' service, as it only covers a single operation. However, it is a borderline case, not extreme.
The tool provides current weather, but obvious gaps like forecasts or historical data are missing, making the surface incomplete for a full weather server. Still, the core get-weather operation is present.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
Hosted MCP server for Xweather weather data: conditions, forecasts, alerts, and more.
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Open-Meteo MCP — weather forecast + historical reanalysis + sister APIs
MCP server for weather with reasoning — umbrella advice, outdoor checks, city comparisons.
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curl -X GET 'https://glama.ai/api/mcp/v1/servers/yangvue/my-weather-server-0706'
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