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MCP Weather Server

by TJarriault
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JavaScript
Remote

MCP Weather Server

A streamable HTTP MCP (Model Context Protocol) server for getting weather data via the Open-Meteo API.

🚀 Features

  • Streamable HTTP Transport: Compatible with MCP 2025-03-26 specification

  • Session Management: Support for persistent sessions with unique IDs

  • Weather Tools: Three main tools for geolocation and weather data

  • REST API: Health endpoint for monitoring

  • Kubernetes Ready: Docker containerization and K8s deployment manifests

  • Local City Search: CSV-based local city database for offline search

📁 Project Structure

├── src/ # Source code TypeScript ├── build/ # Compiled JavaScript ├── static/ # CSV city data files ├── test/ # Test scripts and examples │ ├── test-k8s-deployment.sh # Kubernetes deployment tests │ ├── test_mcp.js # MCP functionality tests │ ├── example-client.js # Example MCP client │ └── README.md # Test documentation ├── claude-configuration/ # Claude Desktop configuration │ ├── claude_config*.json # Various Claude configs │ ├── install_claude_config.sh # Auto-installation script │ └── README.md # Configuration guide ├── k8s/ # Kubernetes manifests │ ├── deployment.yaml # K8s deployment │ ├── service.yaml # K8s service │ └── ingress.yaml # K8s ingress ├── Dockerfile # Multi-stage Docker build ├── k8s-all-in-one.yaml # Complete K8s deployment ├── build-deploy-container.sh # Automated deployment script └── KUBERNETES_DEPLOYMENT.md # Kubernetes deployment guide

📦 Requirement

cd flowise/kubernetes MINIP=`minikube ip` sed -i "s/CHANGEME/$MINIP/g" ingress-flowise.yaml kubectl apply -f .

You need to import on flowise a new agent "Agentflows"

📦 Installation

# Clone and install dependencies npm install # Compile TypeScript npm run build # Start the server npm start

🔧 Configuration

The server uses the following environment variables:

  • PORT: Listening port (default: 3000)

Example:

PORT=8080 npm start

🛠️ Available MCP Tools

1. search_location

Search for GPS coordinates of a city or location by name using the Open-Meteo geocoding API.

Parameters:

  • city_name (string): Name of the city or location to search for

  • country (string, optional): Country name to narrow the search

  • limit (number, optional): Maximum number of results to return (default: 5, max: 10)

Example response:

{ "query": "Paris", "country_filter": null, "total_results": 5, "locations": [ { "name": "Paris", "country": "France", "admin1": "Île-de-France", "latitude": 48.8566, "longitude": 2.3522, "timezone": "Europe/Paris", "population": 2161000, "elevation": 42 }, { "name": "Paris", "country": "United States", "admin1": "Texas", "latitude": 33.6609, "longitude": -95.5555, "timezone": "America/Chicago", "population": 25171, "elevation": 177 } ] }

2. search_local_cities

Search for cities in the local CSV database for offline functionality and faster local search.

Parameters:

  • city_name (string): Name of the city to search for (case insensitive partial match)

  • exact_match (boolean, optional): Whether to search for exact match or partial match (default: false)

  • limit (number, optional): Maximum number of results to return (default: 10, max: 50)

Example response:

{ "query": "Paris", "exact_match": false, "total_found": 3, "results_returned": 3, "cities": [ { "name": "Paris", "latitude": 48.8566, "longitude": 2.3522 }, { "name": "Paris-15e-Arrondissement", "latitude": 48.8421, "longitude": 2.3008 }, { "name": "Parisot", "latitude": 44.0625, "longitude": 1.7125 } ] }

3. get_weather

Get current weather information for a location.

Parameters:

  • latitude (number): Latitude in decimal degrees (-90 to 90)

  • longitude (number): Longitude in decimal degrees (-180 to 180)

  • location_name (string, optional): Optional location name for display

Example response:

{ "location": "Paris", "weather": { "current_weather": { "temperature": 15.2, "windspeed": 10.5, "winddirection": 230, "weathercode": 1, "is_day": 1, "time": "2024-01-15T14:00" }, "current_units": { "temperature": "°C", "windspeed": "km/h", "winddirection": "°", "weathercode": "wmo code", "is_day": "", "time": "iso8601" } }, "lastUpdate": "2024-01-15T14:05:30.123Z" }

4. stream_weather

Start streaming weather data with periodic updates.

Parameters:

  • latitude (number): Latitude in decimal degrees (-90 to 90)

  • longitude (number): Longitude in decimal degrees (-180 to 180)

  • location_name (string, optional): Optional location name for display

  • interval_seconds (number, default: 60): Update interval in seconds

🌐 HTTP Endpoints

Server Health

GET /health

Returns server status:

{ "status": "OK", "timestamp": "2024-01-15T14:05:30.123Z" }

MCP Endpoint

POST /mcp GET /mcp DELETE /mcp

Main endpoint for MCP communications. Supports:

  • POST: Initialization and request sending

  • GET: SSE stream establishment for responses

  • DELETE: Session termination

📋 Usage Example with MCP Client

1. Session Initialization

const initRequest = { jsonrpc: '2.0', id: 1, method: 'initialize', params: { protocolVersion: '2024-11-05', capabilities: { tools: {} }, clientInfo: { name: 'weather-client', version: '1.0.0' } } }; const response = await fetch('http://localhost:8080/mcp', { method: 'POST', headers: { 'Content-Type': 'application/json', 'Accept': 'application/json, text/event-stream' }, body: JSON.stringify(initRequest) }); const sessionId = response.headers.get('mcp-session-id');

2. List Available Tools

const listToolsRequest = { jsonrpc: '2.0', id: 2, method: 'tools/list', params: {} }; const response = await fetch('http://localhost:8080/mcp', { method: 'POST', headers: { 'Content-Type': 'application/json', 'Accept': 'application/json, text/event-stream', 'mcp-session-id': sessionId }, body: JSON.stringify(listToolsRequest) });

3. Call Weather Tool

const weatherRequest = { jsonrpc: '2.0', id: 3, method: 'tools/call', params: { name: 'get_weather', arguments: { latitude: 48.8566, longitude: 2.3522, location_name: 'Paris' } } }; const response = await fetch('http://localhost:8080/mcp', { method: 'POST', headers: { 'Content-Type': 'application/json', 'Accept': 'application/json, text/event-stream', 'mcp-session-id': sessionId }, body: JSON.stringify(weatherRequest) });

🧪 Testing

Quick Testing

# Start the server PORT=8080 npm start # Test the health endpoint curl http://localhost:8080/health

Comprehensive Testing

The project includes various test scripts organized in the test/ directory:

# Run MCP functionality tests cd test && node test_mcp.js # Test local city search cd test && node test_local_cities.js # Test location search cd test && node test_search_location.js # Test Kubernetes deployment (requires K8s cluster) ./test/test-k8s-deployment.sh

For more testing options, see test/README.md.

🐳 Container Build & Kubernetes Deployment

This section describes how to containerize the MCP Weather Sample application and deploy it to a Kubernetes cluster.

📦 Containerization Overview

The application uses a multi-stage Docker build approach for optimal production deployment:

  1. Build Stage: Compiles TypeScript source code

  2. Production Stage: Creates minimal runtime image with only production dependencies

  3. Security: Runs as non-root user with minimal privileges

  4. Health Checks: Built-in container health monitoring

🏗️ Docker Build Process

Automated Build & Deployment

# Complete build and deployment pipeline ./build-deploy-container.sh all # Individual steps ./build-deploy-container.sh build # Build Docker image only ./build-deploy-container.sh deploy # Deploy to Kubernetes only ./build-deploy-container.sh cleanup # Remove deployment

Manual Docker Operations

# Build the Docker image docker build -t mcp-weather-sample:latest . # Run container locally for testing docker run -p 8080:8080 mcp-weather-sample:latest # Check container health curl http://localhost:8080/health # View container logs docker logs <container-id>

Docker Image Details

  • Base Image: node:20-alpine (lightweight Linux distribution)

  • Final Size: ~150MB (optimized with multi-stage build)

  • Port: 8080 (configurable via PORT environment variable)

  • Health Check: Built-in HTTP health endpoint monitoring

  • User: Non-root user (nextjs:nodejs) for security

⚓ Kubernetes Deployment Architecture

Deployment Components

The Kubernetes deployment includes:

  • Deployment: 3 replicas with rolling updates

  • Service: ClusterIP service exposing port 80→8080

  • ConfigMap: Environment configuration management

  • Ingress: External traffic routing with CORS support

  • Health Probes: Startup, liveness, and readiness checks

Resource Configuration

resources: requests: memory: "128Mi" # Minimum memory allocation cpu: "100m" # Minimum CPU allocation (0.1 core) limits: memory: "512Mi" # Maximum memory limit cpu: "500m" # Maximum CPU limit (0.5 core)

High Availability Features

  • 3 Replicas: Ensures service availability during pod failures

  • Rolling Updates: Zero-downtime deployments

  • Health Checks: Automatic pod restart on failure

  • Resource Limits: Prevents resource exhaustion

  • CORS Configuration: Proper header handling for MCP sessions

🚀 Deployment Options

Option 1: All-in-One Deployment

# Deploy everything with single command kubectl apply -f k8s-all-in-one.yaml # Monitor deployment progress kubectl rollout status deployment/mcp-weather-app # Check pod status kubectl get pods -l app=mcp-weather-app

Option 2: Component-by-Component

# Deploy individual components kubectl apply -f k8s/configmap.yaml kubectl apply -f k8s/deployment.yaml kubectl apply -f k8s/service.yaml kubectl apply -f k8s/ingress.yaml

Option 3: Automated Script

# Use the provided deployment script ./build-deploy-container.sh all # Script features: # - Validates kubectl connectivity # - Builds Docker image # - Applies Kubernetes manifests # - Waits for deployment readiness # - Provides access instructions

🔧 Configuration Management

Environment Variables

Configure the application through the ConfigMap:

apiVersion: v1 kind: ConfigMap metadata: name: mcp-weather-config data: NODE_ENV: "production" PORT: "8080" LOG_LEVEL: "info"

Ingress Configuration

# Custom domain configuration spec: rules: - host: mcp-weather.your-domain.com # Replace with your domain http: paths: - path: / pathType: Prefix backend: service: name: mcp-weather-service port: number: 80

🧪 Testing Deployment

Quick Validation

# Test deployment health ./test/test-k8s-deployment.sh # Manual health check via port-forward kubectl port-forward service/mcp-weather-service 8080:8080 curl http://localhost:8080/health # Debug kubectl exec -it pods/$(kubectl get pods --no-headers -o custom-columns=":metadata.name" | grep 'flowise'|head -1) sh

Comprehensive Testing

# Test all endpoints and functionality ./test/test-k8s-deployment.sh local # Test via ingress (requires domain configuration) ./test/test-k8s-deployment.sh ingress your-domain.com

📊 Monitoring & Troubleshooting

Checking Deployment Status

# Pod status and logs kubectl get pods -l app=mcp-weather-app kubectl logs -l app=mcp-weather-app -f # Service endpoints kubectl get endpoints mcp-weather-service kubectl describe service mcp-weather-service # Ingress status kubectl get ingress mcp-weather-ingress kubectl describe ingress mcp-weather-ingress

Common Troubleshooting

# Pod not starting kubectl describe pod <pod-name> kubectl logs <pod-name> --previous # Service not accessible kubectl port-forward service/mcp-weather-service 8080:80 curl http://localhost:8080/health # Image pull issues kubectl describe pod <pod-name> | grep -A 5 "Events:"

🔄 Scaling & Updates

Horizontal Scaling

# Scale to 5 replicas kubectl scale deployment mcp-weather-app --replicas=5 # Verify scaling kubectl get pods -l app=mcp-weather-app

Rolling Updates

# Update image version kubectl set image deployment/mcp-weather-app \ mcp-weather-app=mcp-weather-sample:v2.0.0 # Monitor rollout kubectl rollout status deployment/mcp-weather-app # Rollback if needed kubectl rollout undo deployment/mcp-weather-app

For complete deployment instructions and advanced configurations, see KUBERNETES_DEPLOYMENT.md.

⚙️ Claude Desktop Integration

The project includes pre-configured Claude Desktop configurations in the claude-configuration/ directory:

# Auto-install Claude configuration cd claude-configuration && ./install_claude_config.sh # Validate HTTP configuration cd claude-configuration && ./validate_claude_http.sh

Available configurations:

  • Basic: claude_config.json - Minimal setup

  • Detailed: claude_config_detailed.json - Full options

  • HTTP: claude_config_http.json - HTTP transport specific

For detailed setup instructions, see claude-configuration/README.md.

🔍 Using MCP Inspector

You can use the official MCP Inspector to visually explore and test your weather server tools in a user-friendly interface.

Installation and Setup

  1. Install MCP Inspector (requires Node.js):

    npx @modelcontextprotocol/inspector

  2. Start your weather server:

    PORT=8080 npm start

  3. Configure MCP Inspector:

    • Server URL: http://localhost:8080/mcp

    • Transport: HTTP (Streamable)

    • Protocol Version: 2024-11-05

Visual Interface Features

MCP Inspector Example

The MCP Inspector provides:

  • 🛠️ Tools Explorer: Browse all available tools (search_location, get_weather, stream_weather)

  • 📝 Interactive Forms: Easy-to-use forms for entering tool parameters

  • 🎯 Real-time Testing: Execute tools and see live responses

  • 📊 Response Viewer: JSON-formatted results with syntax highlighting

  • 🔄 Session Management: Visual session state and connection status

  • 📈 Request/Response History: Track all your API interactions

Example Workflow

  1. Connect to your server using the Inspector

  2. Explore the three available weather tools

  3. Test location search:

    • Tool: search_location

    • Parameters: city_name: "Paris"

  4. Get weather data:

    • Tool: get_weather

    • Parameters: Use coordinates from previous search

  5. Monitor streaming:

    • Tool: stream_weather

    • Watch real-time weather updates

Benefits

  • No coding required: Test your MCP server without writing client code

  • Visual debugging: See exactly what data flows between client and server

  • Tool validation: Verify parameter schemas and response formats

  • Rapid prototyping: Quickly iterate on your MCP server implementation

The Inspector is particularly useful during development to ensure your weather server works correctly before integrating it into larger applications.

🏗️ Architecture

  • Express.js: HTTP server

  • MCP SDK: MCP protocol implementation with StreamableHTTPServerTransport

  • Open-Meteo API: Weather data source

  • TypeScript: Development language with compilation to JavaScript

Integrate MCP server on flowise (lowcode GenAI tool)

  1. On flowise initialise an agentflow alt text

  2. Retrieve MCP configuration through MCP inspector alt text Copy/Paste form "Server Entry" on Inspector interface

  3. Configure a "MCP Custom" tool and add exposed toolexposed by the MCP server on flowise add MCP configuration specifciation copied from Inspector

alt text

📄 Specifications

  • MCP Protocol: Version 2024-11-05 and 2025-03-26

  • Transport: Streamable HTTP with SSE support

  • Data Format: JSON-RPC 2.0

  • Weather API: Open-Meteo

🔗 Useful Links

📝 License

This project is a demonstration example based on open-meteo-mcp.

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