AWS MCP Server: Let AI Manage Your Cloud Infrastructure

# AWS MCP Server: Let AI Manage Your Cloud Infrastructure

AWS has hundreds of services and thousands of API calls. When you're debugging a deployment, investigating costs, or checking resource status, you're constantly switching between your editor and the AWS Console. MCP bridges that gap.

With DataFaucet, you can create an AWS MCP server that gives Claude, Cursor, and other AI tools direct access to your AWS account through the console's own APIs.

What Your AI Can Do With AWS Access

Once connected, your AI tools can:

• Check CloudWatch metrics and alarms across services
• List EC2 instances with status, type, and tags
• Query cost explorer for spending breakdowns
• Check Lambda invocations and error rates
• List S3 buckets and object counts
• View ECS/EKS cluster status and task health
• Check RDS instance metrics and connection counts
• List recent CloudTrail events for audit

How It Works

DataFaucet opens the AWS Console in a cloud browser where you're already logged in. As you navigate dashboards, check metrics, and list resources, it captures the underlying API calls the console makes to AWS services.

1. Enter console.aws.amazon.com in DataFaucet
2. Navigate to CloudWatch, EC2, Cost Explorer, or any service
3. DataFaucet captures the console's API traffic
4. Deploy as a hosted MCP server

Connect from any AI tool:

claude mcp add aws https://datafaucet.dev/api/mcp/YOUR_SERVER_ID

Example Prompts After Connecting

• "Are any CloudWatch alarms firing right now?"
• "What's my AWS spend this month compared to last month?"
• "List all EC2 instances in us-east-1 and their status"
• "Show me Lambda errors in the last hour for the payment function"
• "How many connections are open to the production RDS instance?"
• "What was the last CloudTrail event from the deploy role?"

Why MCP Instead of AWS CLI?

The AWS CLI is powerful but requires knowing exact command syntax. MCP gives your AI structured tools:

| Approach | AI Experience |

|----------|---------------|

| Raw CLI access | Must know exact aws commands, parse JSON output |

| DataFaucet server | Typed tools with clear parameters and structured responses |

Your AI doesn't need to remember aws cloudwatch get-metric-statistics --namespace AWS/EC2 --metric-name CPUUtilization --dimensions Name=InstanceId,Value=i-1234. It calls a tool named get_cpu_metrics with an instance ID parameter.

Common Workflows

Incident response: "CloudWatch alarm triggered on the API gateway. Pull the 5xx error count, check if any Lambda functions are timing out, and show me the most recent deploy event."

Cost investigation: "My AWS bill jumped 30% this month. Break down the cost increase by service and show me which resources are new since last month."

Deployment validation: "I just deployed to ECS. Check the task health, pull CloudWatch error metrics for the last 15 minutes, and compare to the pre-deploy baseline."

Capacity check: "Show me all EC2 instances above 80% CPU in the last hour. Are any auto-scaling groups at max capacity?"

Security audit: "List CloudTrail events from IAM in the last 24 hours. Were any new roles or policies created?"

Security Best Practices

• Use a read-only IAM role for the AWS Console session you capture with
• Avoid capturing write operations unless specifically needed
• Scope the session to specific services (only browse CloudWatch + EC2, not IAM)
• Rotate the MCP server API key regularly
• Consider using a dedicated AWS account for monitoring (not production admin)

AWS vs DataFaucet: Complementary Tools

AWS recently launched their own Agent Toolkit with official MCP servers for some services. Use the official toolkit when you need deep integration with a specific AWS service and fine-grained IAM policies. Use DataFaucet when:

• You want quick access across multiple services from one capture session
• The official toolkit doesn't cover your use case yet
• You need console-level access (some APIs are console-only)
• You want zero setup beyond browsing the console

Works With Every MCP Client

Your AWS MCP server works with Claude Desktop, Cursor, Windsurf, Codex, and any MCP-compatible client. Debug infrastructure in Cursor, investigate costs in Claude, automate reports in Codex.

Get Started

Create your AWS MCP server in 60 seconds. Free tier includes 3 servers, no credit card required.

Related: Datadog MCP Server for monitoring, GitHub MCP Server for repos, PostgreSQL MCP Server for databases.