DynamoDB MCP Server: Give AI Agents Access to NoSQL Tables and Indexes

Why Give AI Access to DynamoDB?

AWS DynamoDB stores session data, user profiles, IoT events, and application state across millions of tables. When queries slow down, capacity gets throttled, or GSIs lag behind, debugging means navigating the DynamoDB console, running DescribeTable calls, checking CloudWatch metrics, and correlating partition key distribution.

An MCP server for DynamoDB lets your AI agent query items, check table capacity, inspect GSI status, and monitor throttling directly from Claude, Cursor, or Windsurf through DataFaucet.

What Becomes Possible

Once your AI agent has DynamoDB access:

• "How many items are in the users table?"
• "Is the orders table getting throttled right now?"
• "What's the provisioned vs consumed capacity for the events table?"
• "Show me the GSI status for the product-catalog table"
• "Query the sessions table for user ID abc123"
• "Which tables have on-demand capacity vs provisioned?"

How It Works

1. Go to DataFaucet and enter your DynamoDB console URL or management dashboard
2. Authenticate with your AWS credentials
3. Browse tables, run queries, check capacity metrics as you normally would
4. Each API call becomes an MCP tool your AI can invoke
5. Deploy and connect to Claude, Cursor, or Windsurf

The AI agent uses whatever DynamoDB permissions your IAM role has.

Security Best Practices

• Read-only IAM policy — use AmazonDynamoDBReadOnlyAccess managed policy
• No PutItem, UpdateItem, or DeleteItem — prevent AI from modifying data
• Table-scoped resources — restrict to specific table ARNs in IAM policy
• No CreateTable or DeleteTable — block schema-changing operations
• Condition keys for leading key — limit Query to specific partition key prefixes
• CloudTrail logging — all DynamoDB API calls are audited automatically

Use Cases by Role

Backend developers: Query debugging. "Why is this scan slow? What's the item count and key distribution?" while staying in the editor.

SRE/DevOps: Capacity monitoring. "Is the table throttling? What's consumed vs provisioned read capacity?" during incidents.

Data engineers: Migration planning. "How many items and what size is each table? Which ones are on-demand?" for cost optimization.

Security engineers: Access audit. "Which tables store PII? What encryption settings are configured?" for compliance reviews.

DynamoDB Console vs AI Agent

Getting Started

Set up read-only access for your AI agent:

1. Create an IAM policy with read-only DynamoDB actions:

```json

{

"Effect": "Allow",

"Action": ["dynamodb:GetItem", "dynamodb:Query", "dynamodb:Scan",

"dynamodb:DescribeTable", "dynamodb:ListTables",

"dynamodb:DescribeGlobalTable"],

"Resource": "arn:aws:dynamodb:*:*:table/*"

}

```

1. Create an IAM user or role with this policy
2. Point DataFaucet at the DynamoDB console or your preferred management UI
3. Authenticate with the read-only credentials

Then your AI agent can query table state, check capacity, and inspect indexes as structured MCP tools without risking writes to production data.