OpenWeatherMap▌
by robertn702
OpenWeatherMap API offers current conditions, forecasts, and weather alerts for travel planning and weather-dependent ap
Integrates with OpenWeatherMap API to provide current conditions, forecasts, air quality monitoring, weather alerts, and location services through 11 specialized tools for weather-dependent applications and travel planning.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Weather-dependent applications and services
- / Travel planning and route optimization
- / Agricultural and outdoor activity planning
- / Emergency preparedness and alert systems
capabilities
- / Get current weather conditions for any location
- / Fetch 5-day forecasts with 3-hour intervals
- / Monitor air quality and pollution levels
- / Retrieve active weather alerts and warnings
- / Convert location names to coordinates
- / Access minute-by-minute precipitation forecasts
what it does
Connects to OpenWeatherMap API to fetch current weather, forecasts, air quality data, and weather alerts for any location. Provides comprehensive weather information through 11 specialized tools.
about
OpenWeatherMap is a community-built MCP server published by robertn702 that provides AI assistants with tools and capabilities via the Model Context Protocol. OpenWeatherMap API offers current conditions, forecasts, and weather alerts for travel planning and weather-dependent ap It is categorized under developer tools.
how to install
You can install OpenWeatherMap 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.
license
MIT
OpenWeatherMap is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
OpenWeatherMap MCP Server
A Model Context Protocol (MCP) server that provides comprehensive weather data and forecasts through the OpenWeatherMap API. This server enables AI assistants to access real-time weather information, forecasts, air quality data, and location services.
<a href="https://glama.ai/mcp/servers/@robertn702/mcp-openweathermap"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@robertn702/mcp-openweathermap/badge" alt="OpenWeatherMap Server MCP server" /> </a>Features
Weather Tools
- Current Weather - Get current conditions for any location
- Weather Forecast - 5-day weather forecast with 3-hour intervals
- Hourly Forecast - Detailed hourly forecasts for up to 48 hours
- Daily Forecast - Daily weather forecasts for up to 8 days with temperature ranges and astronomical data
- Minutely Forecast - Minute-by-minute precipitation forecasts for the next hour
- Weather Alerts - Active weather warnings and alerts with severity classification
Air Quality & Location
- Current Air Pollution - Real-time air quality index and pollutant measurements
- Location Info - Reverse geocoding to get location details from coordinates
- OneCall Weather - Comprehensive weather data combining multiple forecasts
- Air Pollution - Historical and forecast air quality data
- Geocoding - Convert location names to coordinates
Installation
Prerequisites
- Bun runtime
- OpenWeatherMap API key (free at openweathermap.org)
Setup
- Clone the repository:
git clone https://github.com/robertn702/mcp-openweathermap.git
cd mcp-openweathermap
- Install dependencies:
bun install
- Set up your environment variables:
cp .env.example .env
# Edit .env and add your OpenWeatherMap API key
Environment variables:
OPENWEATHER_API_KEY- Your OpenWeatherMap API key (required for stdio transport only)PORT- Server port for HTTP transport (default: 3000)MCP_TRANSPORT- Transport type:stdioorhttpStream(default: stdio)MCP_ENDPOINT- HTTP endpoint path (default: /stream)
Usage
Running the Server
Stdio Transport (default):
bun run src/main.ts
HTTP Stream Transport:
MCP_TRANSPORT=httpStream PORT=3000 bun run src/main.ts
Claude Desktop Configuration
Add this configuration to your Claude Desktop MCP settings:
{
"mcpServers": {
"openweathermap": {
"command": "npx",
"args": ["mcp-openweathermap"],
"env": {
"OPENWEATHER_API_KEY": "your-api-key-here"
}
}
}
}
API Tools
Weather Information
get-current-weather- Current weather conditionsget-weather-forecast- 5-day forecastget-hourly-forecast- Hourly forecasts (up to 48 hours)get-daily-forecast- Daily forecasts (up to 8 days)get-minutely-forecast- Minute-by-minute precipitation
Alerts & Air Quality
get-weather-alerts- Weather warnings and alertsget-current-air-pollution- Current air quality dataget-air-pollution- Air quality forecasts and history
Location Services
get-location-info- Reverse geocoding from coordinatesgeocode-location- Convert addresses to coordinatesget-onecall-weather- Comprehensive weather data
Development
Running in Development
bun run src/main.ts
Testing with MCP Inspector
bun run src/main.ts
Then connect the MCP Inspector to test the tools interactively.
Build
bun run build
Authentication
Stdio Transport: Requires OPENWEATHER_API_KEY environment variable.
HTTP Transport: The OpenWeatherMap API key is passed as a bearer token in the HTTP request headers. No environment variable needed.
Contributing
- Fork the repository
- Create a feature branch
- Make your changes
- Add tests if applicable
- Submit a pull request
License
This project is licensed under the MIT License - see the LICENSE file for details.
Support
- OpenWeatherMap API Documentation
- openweather-api-node Library - The underlying API client
- Model Context Protocol Documentation
- Issue Tracker
FAQ
- What is the OpenWeatherMap MCP server?
- OpenWeatherMap is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for OpenWeatherMap?
- This profile displays 43 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
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
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
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
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ 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.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.5★★★★★43 reviews- ★★★★★Chaitanya Patil· Dec 28, 2024
OpenWeatherMap is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Isabella Patel· Dec 28, 2024
OpenWeatherMap reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Li Sharma· Dec 24, 2024
Useful MCP listing: OpenWeatherMap is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Yusuf Abbas· Dec 20, 2024
According to our notes, OpenWeatherMap benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Pratham Ware· Dec 4, 2024
We wired OpenWeatherMap into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Piyush G· Nov 19, 2024
We evaluated OpenWeatherMap against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Evelyn Sharma· Nov 19, 2024
Useful MCP listing: OpenWeatherMap is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Xiao Chawla· Nov 15, 2024
According to our notes, OpenWeatherMap benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Daniel Farah· Nov 15, 2024
OpenWeatherMap reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Shikha Mishra· Oct 10, 2024
OpenWeatherMap has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
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