JWeather offers real-time conditions & forecasts via an asyncio Python server, integrating with top weather services. Au
Add new capabilities to Claude beyond text generation
Example: Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example: Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example: Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Time estimate: 15-60 minutes depending on server complexity
Prerequisites
n8n
n8n offers conversational workflow automation, enabling seamless software workflow creation and management without platf
Linear
MCP server for Linear — enables Claude to interact with Linear data and workflows.
WhatsApp MCP
Send and receive WhatsApp messages directly from Claude and other AI assistants. Search conversations, manage contacts,
Windows MCP
MCP server for full computer use on Windows. Control mouse, keyboard, take screenshots, manage windows, and automate des
Claude Context
Claude Context offers semantic code search and indexing with vector embeddings and AST-based code splitting. Natural lan
I recommend JWeather for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
We wired JWeather into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
JWeather is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
We evaluated JWeather against two servers with overlapping tools; this profile had the clearer scope statement.
JWeather is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
JWeather has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Useful MCP listing: JWeather is the kind of server we cite when onboarding engineers to host + tool permissions.
I recommend JWeather for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
JWeather reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Useful MCP listing: JWeather is the kind of server we cite when onboarding engineers to host + tool permissions.
showing 1-10 of 26
Share your MCP server with the developer community
Select a client to integrate this server.
Claude Desktop configuration
{
"mcpServers": {
"jweather-mcp-server": {
"command": "uvx",
"args": [
"jweather-mcp-server"
],
"env": {
"JUHE_WEATHER_API_KEY": "your_api_key"
}
}
}
}Provides real-time weather data and forecasts through a Python-based MCP server that integrates with weather APIs.
JWeather is a community-built MCP server published by juhemcp that provides AI assistants with tools and capabilities via the Model Context Protocol. JWeather offers real-time conditions & forecasts via an asyncio Python server, integrating with top weather services. Au It is categorized under developer tools.
You can install JWeather in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
一个提供全国天气预报查询功能的模型上下文协议(Model Context Protocol)服务器。该服务器使大型语言模型(LLMs)能够获取全国城市、地区的天气预报情况。
服务器实现了一个工具:
async def query_weather(
city: str = Field(description="查询的城市名称,如北京、上海、广州、深圳、泰顺等;城市或区县或地区名使用简写,严格按照规范填写,否则会导致查询失败")
) -> list[types.TextContent | types.ImageContent | types.EmbeddedResource]:
This server requires Python 3.10 or higher. Install dependencies using uv (recommended) or pip
When using uv no specific installation is needed. We will use uvx to directly run jweather-mcp-server.
uvx jweather-mcp-server
Alternatively you can install jweather-mcp-server via pip:
pip install jweather-mcp-server
After installation, you can run it as a script using:
python -m jweather_mcp_server
JUHE_WEATHER_API_KEY: 聚合数据的天气预报查询API密钥。获取:https://www.juhe.cn/docs/api/id/73
JUHE_WEATHER_API_KEY=your_api_key
"mcpServers": {
"jweather-mcp-server": {
"command": "uvx",
"args": [
"jweather-mcp-server"
],
"env": {
"JUHE_WEATHER_API_KEY": "your_api_key"
}
}
}
</details>
<details>
<summary>Using pip installation</summary>
"mcpServers": {
"jweather-mcp-server": {
"command": "python",
"args": [
"-m",
"jmobile_location_mcp_server"
],
"env": {
"JUHE_WEATHER_API_KEY": "your_api_key"
}
}
}
</details>
You can use the MCP inspector to debug the server. For uvx installations:
npx @modelcontextprotocol/inspector uvx jweather-mcp-server
Or if you've installed the package in a specific directory or are developing on it:
cd path/to/servers/src/jweather-mcp-server
npx @modelcontextprotocol/inspector uv run jweather-mcp-server
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Datadog
MCP server for Datadog — enables Claude to interact with Datadog data and workflows.