People use AI-powered tools for various purposes - from simple text completion to writing full reports. But what if your AI assistant could do more? What if it could check your calendar, get weather updates, or connect to your business systems?
The answer is: Using MCP to connect to external tools like weather APIs and calendars can empower your AI assistant to do whatever you like!
About This Product
In this week’s blog series, we highlight practical, real‑world applications that you can put into use immediately. We'll build a complete set of AI-powered productivity tools:
| Tool | What It Does | Key Features |
|---|---|---|
| Smart Communicator | Performs advanced math/statistics operations | Understands natural language, handles complex data analyses |
| Calendar Assistant | Manages your schedule intelligently | Detects conflicts, suggests optimal meeting times |
| Weather Advisor | Provides smart weather forecasts | Recommends activities based on conditions |
| Bring Your Own MCP (BYOM) Server | Custom functionality you design | Build tools specific to your needs |
All integrated into a pre-built React application - so we can focus on building the intelligence, not the UI! "UI is Ready, Focus on the Intelligence" - A complete frontend is provided in advance so we can focus on building the AI-powered backend tools that make a real difference in productivity. In the end, we'll have built multiple MCP servers with hands-on experience, production-ready code we can use daily, and practical patterns for building real-world AI applications.
Environment Overview
Pre-Installed Tools
| Tool | Purpose | Version |
|---|---|---|
| Python | Backend development | 3.11+ |
| Node.js | Frontend dependencies | 18+ |
| AWS CLI | AWS service access | Latest |
| Git | Version control | Latest |
AWS Services Configured
Our environment has access to:
- Amazon Bedrock: AI model access (Amazon Nova, Anthropic Claude)
- CloudWatch: Logging and monitoring
- Secrets Manager: Secure credential storage
- EC2: Compute resources
- VPC: Networking
Frontend (React)
- Modern chat interface
- Real-time message streaming
- Token usage tracking
- Session history
Backend (FastAPI)
- Strands Agents integration
- MCP server management
- Bedrock model access
- WebSocket support
Launching Application
This is the application...
Left Navigation Panel
On the left side, we have a navigation panel where we can choose the foundation model and and turn on/off MCP servers.
Chat Interface
In the center of the application, we have a chat interface where we can type and see responses from the foundation model.
Server logs
On the right side, we have a panel with the server logs. We have the ability to filter through the different type of logs generated by our server.
Accessing the Application
Once started, we can access the application at:
Frontend: CloudFront URL + /proxy/3000/ (e.g., https://abc123.cloudfront.net/proxy/3000/)
Backend API: CloudFront URL + /proxy/8000/ (e.g., https://abc123.cloudfront.net/proxy/8000/)
We can find the CloudFront URL under the PORTS tab. Then, click on the globe icon next to the URL to open the page directly in the browser.
Troubleshooting Common Issues
Important: Only use the following commands when you are facing an issue.
| Issue | Solution |
|---|---|
| Port already in use | Run `pkill -f "python\ |
| Permission denied | Run {% raw %}chmod +x start.sh
|
| Module not found | Activate virtual environment: source .venv/bin/activate
|
| AWS access denied | Environment should be pre-configured, contact instructor |
Verification
Once our environment is running:
- Verify Application: Access the frontend using CloudFront URL + /proxy/3000/
- Test Chat Interface: Send a simple message
- Check Backend: Ensure API responds at CloudFront URL + /proxy/8000/
- Review Code Structure: Explore the ui/backend/mcp_servers/ directory
Environment Ready: Our development environment is configured and ready for building MCP servers!
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