# Guidance For Vibe Coding With Aws Mcp Servers > Hands-on guidance for AI-accelerated AWS development using AWS MCP Servers. Learn to leverage AI coding assistants to enhance your development workflows with AWS best practices. - **Type:** MCP server - **Install:** `agentstack add mcp-aws-solutions-library-samples-guidance-for-vibe-coding-with-aws-mcp-servers` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [aws-solutions-library-samples](https://agentstack.voostack.com/s/aws-solutions-library-samples) - **Installs:** 0 - **Category:** [Cloud & Infrastructure](https://agentstack.voostack.com/c/cloud-infrastructure) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [aws-solutions-library-samples](https://github.com/aws-solutions-library-samples) - **Source:** https://github.com/aws-solutions-library-samples/guidance-for-vibe-coding-with-aws-mcp-servers ## Install ```sh agentstack add mcp-aws-solutions-library-samples-guidance-for-vibe-coding-with-aws-mcp-servers ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # Guidance for Vibe Coding AI Agents with AWS MCP Servers ## Table of Contents - [Guidance for Vibe Coding AI Agents with AWS MCP Servers](#guidance-for-vibe-coding-ai-agents-with-aws-mcp-servers) - [Table of Contents](#table-of-contents) - [Overview](#overview) - [AWS MCP Servers](#aws-mcp-servers) - [Architecture](#architecture) - [Cost](#cost) - [Sample Cost Table](#sample-cost-table) - [Deployment Options](#deployment-options) - [Option 1: AWS Workshop Studio (Recommended for Workshop Participants)](#option-1-aws-workshop-studio-recommended-for-workshop-participants) - [Option 2: Self-Deployment in Your Own AWS Account](#option-2-self-deployment-in-your-own-aws-account) - [Repository Structure](#repository-structure) - [System Components](#system-components) - [Prerequisites](#prerequisites) - [Workshop Studio Users](#workshop-studio-users) - [Self-Deployment Users](#self-deployment-users) - [Operating System](#operating-system) - [Deployment Steps](#deployment-steps) - [Step 1: Clone the Repository](#step-1-clone-the-repository) - [Step 2: Install Dependencies and Start Workshop Documentation](#step-2-install-dependencies-and-start-workshop-documentation) - [Deployment Validation](#deployment-validation) - [Running the Guidance](#running-the-guidance) - [Next Steps](#next-steps) - [Cleanup](#cleanup) - [FAQ and Known Issues](#faq-and-known-issues) - [Notices](#notices) - [Authors](#authors) ## Overview This Guidance demonstrates how to build AI-powered development workflows using Amazon Bedrock AgentCore and the Model Context Protocol (MCP). It provides a complete, deployable hotel booking agent system that showcases "vibe coding" techniques - an AI-assisted development approach that accelerates software development through intelligent code generation, discovery, and problem-solving. The Guidance is designed as an interactive workshop where participants learn to: - Use AI tools to understand and navigate complex codebases quickly - Generate, enhance, and debug code efficiently with AI assistance - Leverage AI for architecture analysis, optimization, and testing - Rapidly prototype and iterate on ideas using AI-powered development tools Participants deploy a realistic hotel booking agent using Amazon Bedrock AgentCore and gain hands-on experience with AI development tools including Kiro, Amazon Q, and AWS MCP Servers. The skills learned can be immediately applied to production projects and shared across development teams. ### AWS MCP Servers This workshop leverages [AWS MCP Servers](https://github.com/awslabs/mcp), specialized MCP servers that enhance foundation model capabilities through the Model Context Protocol (MCP). MCP is an open protocol that enables seamless integration between LLM applications and external data sources and tools. The workshop demonstrates these capabilities across three practical scenarios: - **Discovery & Analysis**: Automated architecture visualization and service expertise - **Frontend Development**: Modern React applications with AWS Amplify integration - **Production Readiness**: Real-time cost analysis and security assessment ### Architecture The solution implements a multi-tier architecture combining Amazon Bedrock AgentCore with serverless AWS services: **Architecture Flow:** - **User Interaction** - Users interact with the AgentCore agent through natural language conversations - **Agent Orchestration** - Amazon Bedrock AgentCore processes requests and determines required actions - **MCP Server Bridge** - Model Context Protocol server translates agent actions into API calls - **Backend Services** - Three specialized APIs handle hotel search, reservations, and content moderation - **Data Storage** - Amazon DynamoDB stores hotel and reservation data **Key Components:** - **Amazon Bedrock AgentCore** - Intelligent conversational agent with natural language understanding - **MCP Server** - Protocol bridge connecting agent to backend APIs - **Property Resolution API** (AWS Lambda + API Gateway) - Hotel search powered by Amazon Location Service - **Reservations API** (AWS Lambda + API Gateway) - Booking management and CRUD operations - **Toxicity Detection API** (AWS Lambda + API Gateway) - Content moderation using Amazon Comprehend - **Amazon DynamoDB** - NoSQL database for hotels and reservations ### Cost You are responsible for the cost of the AWS services used while running this Guidance. As of October 2025, the cost for running this Guidance with the default settings in the US West (Oregon) Region is estimated at approximately **$258 per month** for continuous 24/7 operation. **Note:** This estimate assumes continuous 24/7 usage with a moderately active workload. Actual costs will vary based on your specific usage patterns, interaction frequency, and data volumes. We recommend creating a [Budget](https://docs.aws.amazon.com/cost-management/latest/userguide/budgets-managing-costs.html) through [AWS Cost Explorer](https://aws.amazon.com/aws-cost-management/aws-cost-explorer/) to help manage costs. Prices are subject to change. For full details, refer to the pricing webpage for each AWS service used in this Guidance. ### Sample Cost Table The following table provides a sample cost breakdown for deploying this Guidance with the default parameters in the US West (Oregon) Region. | AWS Service | Purpose | Monthly Cost | Note | | ------------------------ | ---------------------------------- | ------------ | --------------------------------------------------------- | | Amazon Bedrock | Agent model invocation | $129.60 | 10K input, 10K output per hour assumption | | Amazon Bedrock AgentCore | Hotel booking agent and MCP Server | $114.91 | 0.5 vCPU, 1 GB, 100 events per hour for short term memory | | Amazon Comprehend | Toxicity detection API | $1.44 | Optional challenge (20 requests per hour) | | AWS DynamoDB | Mock APIs | $1.83 | | | AWS Lambda | Mock APIs | $0.07 | | | Amazon ECR | AgentCore image | $0.10 | 1 GB Container Image storage | | Amazon CloudWatch | Monitoring and logs | $10.00 | 20 GB log storage | | **Total** | | **$257.96** | | ## Deployment Options This Guidance can be deployed in two ways: ### Option 1: AWS Workshop Studio (Recommended for Workshop Participants) If you're participating in an AWS-hosted workshop event, use Workshop Studio for a pre-configured environment with all prerequisites and infrastructure already set up. **Access the Workshop**: [Vibe Coding AI Agents with AWS MCP Servers](https://catalog.us-east-1.prod.workshops.aws/workshops/dd13f372-393c-4015-b082-a42f2abaf77a/en-US) The Workshop Studio environment includes: - Pre-installed development tools and prerequisites - Pre-deployed AWS infrastructure (APIs, Agent, MCP Server) - Ready-to-use development environment Simply follow the on-screen instructions in Workshop Studio to access your temporary AWS account and begin the workshop activities. ### Option 2: Self-Deployment in Your Own AWS Account If you want to deploy this Guidance in your own AWS account, continue with the sections below: - [Prerequisites](#prerequisites) - Install required tools - [Deployment Steps](#deployment-steps) - Deploy the infrastructure - [Deployment Validation](#deployment-validation) - Verify your deployment ## Repository Structure This repository contains a complete Amazon Bedrock AgentCore hotel booking system with workshop materials: ```text ├── packages/ # Core application packages │ ├── agentcore-agents/ # Amazon Bedrock AgentCore agents │ │ └── hotel-booking-agent/ # Intelligent hotel booking assistant │ ├── agentcore-mcp-servers/ # Model Context Protocol servers │ │ └── hotel-booking/ # Hotel booking MCP server │ └── cdk-infra-python/ # AWS CDK infrastructure │ ├── src/stacks/ # CDK stack definitions │ └── app.py # CDK application entry point └── docs/ # Workshop documentation └── astro-docs/ # Participant documentation site ``` ### System Components - **AgentCore Agent** - Intelligent conversational agent that understands natural language and orchestrates hotel booking operations - **MCP Server** - Protocol server that bridges the agent with hotel booking APIs (Property Resolution, Reservations, Toxicity Detection) - **Mock APIs** - Three production-like services for hotel search, booking management, and content moderation - **CDK Infrastructure** - Complete AWS deployment including Lambda functions, API Gateway, DynamoDB, and IAM resources ## Prerequisites ### Workshop Studio Users Your environment is **completely pre-configured** with all tools, dependencies, and infrastructure already deployed. Simply run `pnpm docs:init` to access the workshop documentation. ### Self-Deployment Users **Minimum requirements to get started:** - **Node.js** (v20.18.1+) and **pnpm** - Required to run documentation ```bash npm install -g pnpm ``` - **An AWS account** with appropriate IAM permissions **After running `pnpm docs:init`**, follow the comprehensive [Prerequisites Guide](http://localhost:4321/intro/prerequisites) for step-by-step installation of: - Python, uv, AWS CLI, AWS CDK CLI, Docker, Graphviz - AI Assistant tools (Amazon Q Developer, Cline, Kiro, etc.) - **at least one required** - All other required development tools ### Operating System These deployment instructions are optimized to work on **macOS, Linux, and Windows** operating systems. > **Note:** Amazon Bedrock AgentCore requires ARM64 container images ([AWS Documentation](https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/runtime-troubleshooting.html#troubleshoot-runtime-requirements)). Docker Desktop includes built-in ARM64 emulation. For Docker Engine users, run `docker run --privileged --rm tonistiigi/binfmt --install all` to enable ARM64 support. ## Deployment Steps ### Step 1: Clone the Repository ```bash git clone https://github.com/aws-solutions-library-samples/guidance-for-vibe-coding-with-aws-mcp-servers.git ``` ### Step 2: Install Dependencies and Start Workshop Documentation Install project dependencies and start the workshop documentation locally: ```bash # Install all dependencies pnpm install # Build and serve documentation locally (opens on localhost) pnpm docs:init ``` The documentation will be available at `http://localhost:4321`. **Open this URL and follow the detailed setup instructions** in the participant guide. **Important:** After starting the documentation server, navigate to: 1. **"Prerequisites"** - Complete installation of all required tools (Python, uv, AWS CLI, CDK CLI, Docker, AI assistants, etc.) 2. **"Setup your own development environment"** - Deploy AWS infrastructure (Mock APIs, AgentCore Agent, MCP Server) 3. **"Setup up your IDE Extensions"** - Configure your AI development tools and MCP servers These sections provide comprehensive step-by-step guidance for prerequisites installation, infrastructure deployment, and environment configuration. Once complete, you'll be ready to begin the workshop activities. ## Deployment Validation Verify your deployment was successful: 1. **Check CloudFormation Stacks** ```bash # List all deployed stacks aws cloudformation list-stacks --stack-status-filter CREATE_COMPLETE UPDATE_COMPLETE ``` You should see these stacks: - `VibeCodingWorkshopMockApis` - `VibeCodingWorkshopBookingAgent` - `VibeCodingWorkshopMcpServer` 2. **Verify API Endpoints** ```bash # Get stack outputs (API URLs and keys) aws cloudformation describe-stacks \ --stack-name VibeCodingWorkshopMockApis \ --query 'Stacks[0].Outputs[*].[OutputKey,OutputValue]' \ --output table ``` 3. **Test APIs with Bruno CLI** ```bash # Run API tests pnpm test:apis:reservations pnpm test:apis:toxicity ``` All tests should pass, confirming the APIs are functioning correctly. 4. **Verify AgentCore Deployments** Check the AWS Console to confirm the Agent and MCP Server are listed in Amazon Bedrock AgentCore. ## Running the Guidance Once deployed, follow the workshop documentation for detailed activities: 1. **Access Workshop Documentation** If you closed the documentation server, restart it with: ```bash pnpm docs:init ``` Then open `http://localhost:4321` in your browser. 2. **Configure Your AI Development Tool** Follow the workshop documentation to configure your preferred AI tool (Kiro, Amazon Q Developer, VS Code + Cline, etc.) to connect to the deployed MCP server. 3. **Workshop Phases** The workshop is organized into three phases: - **Phase 1:** Understanding the codebase and architecture - **Phase 2:** Enhancing the agent with new capabilities - **Phase 3:** Testing, debugging, and optimization 4. **Interact with the Agent** Use your configured AI tool to interact with the hotel booking agent through natural language conversations. The agent can: - Search for hotels by location - Create and manage reservations - Moderate user-generated content - Maintain conversation context ## Next Steps After completing the workshop, consider these enhancements: - **Add New APIs** - Integrate additional services (payment processing, loyalty programs, reviews) - **Enhance Agent Capabilities** - Add multi-language support, price comparison, or recommendation features - **Implement Production Features** - Add monitoring, logging, error handling, and rate limiting - **Explore Other MCP Servers** - Integrate AWS MCP Servers for documentation access and best practices - **Scale the Solution** - Implement caching, optimize Lambda functions, add CDN for static assets - **Security Hardening** - Implement WAF rules, enhance IAM policies, add encryption at rest ## Cleanup To avoid ongoing charges, delete all deployed resources: **Delete CDK Stacks** ```bash # Delete all stacks in reverse order pnpm cdk destroy VibeCodingWorkshopMcpServer pnpm cdk destroy VibeCodingWorkshopBookingAgent pnpm cdk destroy VibeCodingWorkshopMockApis ``` For detailed cleanup instructions including CodeBuild cleanup, ECR cleanup, verification steps, and local environment cleanup, see the [Cleanup Guide](http://localhost:4321/dev-env/cleanup). ## FAQ and Known Issues **Q: Which AWS regions are supported?** A: This Guidance has been tested in us-west-2 (Oregon) and us-east-1 (N. Virginia). Other regions may work but are not officially supported. **Q: What are the estimated costs?** A: Cost estimates are pending. See the [Cost](#cost) section for details. Most workshop activities can be completed within AWS Free Tier limits. **Q: Can I use this in production?** A: This Guidance is designed as a workshop and learning tool. Not intended for production use. **Known Issues:** 1. **Python Interpreter Permission Errors** - **Problem:** `Permission denied` error when running CDK commands - **Solution:** Recreate the uv virtual environment: ```bash cd packages/cdk-infra-python rm -rf .venv uv sync cd ../.. ``` 2. **Stack Does Not Exist Error** - **Problem:** Getting "Stack does not exist" when running CloudFormation commands - **Solution:** Verify you're using the correct AWS profile … ## Source & license This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [aws-solutions-library-samples](https://github.com/aws-solutions-library-samples) - **Source:** [aws-solutions-library-samples/guidance-for-vibe-coding-with-aws-mcp-servers](https://github.com/aws-solutions-library-samples/guidance-for-vibe-coding-with-aws-mcp-servers) - **License:** MIT Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/mcp-aws-solutions-library-samples-guidance-for-vibe-coding-with-aws-mcp-servers - Seller: https://agentstack.voostack.com/s/aws-solutions-library-samples - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. 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