aws-athena-mcp 1.0.0

A simple, clean MCP server for AWS Athena integration

AWS Athena MCP Server

A simple, clean MCP (Model Context Protocol) server for AWS Athena integration. Execute SQL queries, discover schemas, and manage query executions through a standardized interface.

✨ Features

• Simple Setup - Get running in under 5 minutes
• Clean Architecture - Modular, well-tested, easy to understand
• Essential Tools - Query execution and schema discovery
• Type Safe - Full type hints and Pydantic models
• Async Support - Built for performance with async/await
• Good Defaults - Works out of the box with minimal configuration

🚀 Quick Start

1. Install

# From PyPI with uvx (recommended for Claude Desktop)
uvx install aws-athena-mcp

# From PyPI with pip
pip install aws-athena-mcp

# Or from source
git clone https://github.com/ColeMurray/aws-athena-mcp
cd aws-athena-mcp
pip install -e .

2. Configure

Set the required environment variables:

# Required
export ATHENA_S3_OUTPUT_LOCATION=s3://your-bucket/athena-results/

# Optional (with defaults)
export AWS_REGION=us-east-1
export ATHENA_WORKGROUP=primary
export ATHENA_TIMEOUT_SECONDS=60

3. Run

# Start the MCP server
aws-athena-mcp

# Or run directly
python -m athena_mcp.server

That's it! The server is now running and ready to accept MCP connections.

🤖 Claude Desktop Integration

To use this MCP server with Claude Desktop:

1. Install Claude Desktop

Download and install Claude Desktop if you haven't already.

2. Configure Claude Desktop

Add the following configuration to your claude_desktop_config.json:

Location of config file:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json

Configuration:

{
  "mcpServers": {
    "aws-athena-mcp": {
      "command": "uvx",
      "args": [
        "aws-athena-mcp"
      ],
      "env": {
        "ATHENA_S3_OUTPUT_LOCATION": "s3://your-bucket/athena-results/",
        "AWS_REGION": "us-east-1",
        "ATHENA_WORKGROUP": "primary",
        "ATHENA_TIMEOUT_SECONDS": "60"
      }
    }
  }
}

3. Set AWS Credentials

Configure your AWS credentials using one of these methods:

# Method 1: Environment variables (add to your shell profile)
export AWS_ACCESS_KEY_ID=your-access-key
export AWS_SECRET_ACCESS_KEY=your-secret-key

# Method 2: AWS CLI
aws configure

# Method 3: AWS Profile
export AWS_PROFILE=your-profile

4. Restart Claude Desktop

Restart Claude Desktop to load the new MCP server configuration.

5. Verify Connection

In Claude Desktop, you should now be able to:

• Execute SQL queries against your Athena databases
• List tables and describe schemas
• Get query results and status

Example conversation:

You: "List all tables in my 'analytics' database"
Claude: I'll help you list the tables in your analytics database using the Athena MCP server.
[Uses list_tables tool]

🛠️ Automated Setup (Alternative)

For easier setup, you can use the included setup script:

# Clone the repository
git clone https://github.com/ColeMurray/aws-athena-mcp
cd aws-athena-mcp

# Run the setup script
python scripts/setup_claude_desktop.py

The script will:

• Check if uvx is installed
• Guide you through configuration
• Update your Claude Desktop config file
• Verify AWS credentials
• Provide next steps

You can also copy the example configuration:

cp examples/claude_desktop_config.json ~/Library/Application\ Support/Claude/claude_desktop_config.json
# Then edit the file to add your S3 bucket and AWS settings

🔧 Configuration

The server uses environment variables for configuration:

Variable	Required	Default	Description
ATHENA_S3_OUTPUT_LOCATION	✅	-	S3 path for query results
AWS_REGION	❌	us-east-1	AWS region
ATHENA_WORKGROUP	❌	None	Athena workgroup
ATHENA_TIMEOUT_SECONDS	❌	60	Query timeout

AWS Credentials

Configure AWS credentials using any of these methods:

# Method 1: Environment variables
export AWS_ACCESS_KEY_ID=your-access-key
export AWS_SECRET_ACCESS_KEY=your-secret-key

# Method 2: AWS CLI
aws configure

# Method 3: AWS Profile
export AWS_PROFILE=your-profile

# Method 4: IAM roles (for EC2/Lambda)
# No configuration needed

🔒 Security

Environment Variables

⚠️ NEVER commit credentials to version control!

Use the provided example file to set up your environment:

# Copy the example file
cp examples/environment_variables.example .env

# Edit with your values
nano .env

# Make sure .env is in .gitignore (it already is)
echo ".env" >> .gitignore

AWS Credentials Best Practices

1. Use IAM Roles (recommended for production):

   # No credentials needed - uses instance/container role
   export ATHENA_S3_OUTPUT_LOCATION=s3://your-bucket/results/
   

2. Use AWS CLI profiles (recommended for development):

   aws configure --profile athena-mcp
   export AWS_PROFILE=athena-mcp
   

3. Use temporary credentials when possible:

   aws sts assume-role --role-arn arn:aws:iam::123456789012:role/AthenaRole \
     --role-session-name athena-mcp-session
   

4. Avoid long-term access keys in environment variables

Required AWS Permissions

Your AWS credentials need these minimum permissions:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": [
        "athena:StartQueryExecution",
        "athena:GetQueryExecution", 
        "athena:GetQueryResults",
        "athena:ListWorkGroups",
        "athena:GetWorkGroup"
      ],
      "Resource": "*"
    },
    {
      "Effect": "Allow",
      "Action": [
        "s3:GetObject",
        "s3:PutObject",
        "s3:DeleteObject"
      ],
      "Resource": "arn:aws:s3:::your-bucket/athena-results/*"
    },
    {
      "Effect": "Allow",
      "Action": [
        "s3:ListBucket"
      ],
      "Resource": "arn:aws:s3:::your-bucket"
    },
    {
      "Effect": "Allow",
      "Action": [
        "glue:GetDatabase",
        "glue:GetDatabases",
        "glue:GetTable",
        "glue:GetTables"
      ],
      "Resource": "*"
    }
  ]
}

SQL Injection Protection

The server includes built-in SQL injection protection:

• Query validation - Dangerous patterns are blocked
• Input sanitization - Database/table names are validated
• Query size limits - Prevents resource exhaustion
• Parameterized queries - When possible

Network Security

For production deployments:

• Use VPC endpoints for AWS services
• Restrict network access to the MCP server
• Use TLS for all communications
• Monitor and log all queries

Monitoring and Auditing

Enable CloudTrail logging for Athena:

{
  "eventVersion": "1.05",
  "userIdentity": {...},
  "eventTime": "2024-01-01T12:00:00Z",
  "eventSource": "athena.amazonaws.com",
  "eventName": "StartQueryExecution",
  "resources": [...]
}

🛠️ Available Tools

The server provides these MCP tools:

Query Execution

• run_query - Execute SQL queries against Athena
• get_status - Check query execution status
• get_result - Get results for completed queries

Schema Discovery

• list_tables - List all tables in a database
• describe_table - Get detailed table schema

📖 Usage Examples

Basic Query Execution

# Using the MCP client (pseudo-code)
result = await mcp_client.call_tool("run_query", {
    "database": "default",
    "query": "SELECT * FROM my_table LIMIT 10",
    "max_rows": 10
})

Schema Discovery

# List tables
tables = await mcp_client.call_tool("list_tables", {
    "database": "default"
})

# Describe a table
schema = await mcp_client.call_tool("describe_table", {
    "database": "default",
    "table_name": "my_table"
})

Handling Timeouts

# Long-running query
result = await mcp_client.call_tool("run_query", {
    "database": "default",
    "query": "SELECT COUNT(*) FROM large_table"
})

if "query_execution_id" in result:
    # Query timed out, check status later
    status = await mcp_client.call_tool("get_status", {
        "query_execution_id": result["query_execution_id"]
    })

🧪 Testing

Test your configuration:

# Test configuration and AWS connection
python scripts/test_connection.py

# Run the test suite
pytest

# Run with coverage
pytest --cov=athena_mcp

🏗️ Development

Setup Development Environment

# Clone and install in development mode
git clone https://github.com/ColeMurray/aws-athena-mcp
cd aws-athena-mcp
pip install -e ".[dev]"

# Run tests
pytest

# Format code
black src tests
isort src tests

# Type checking
mypy src

Project Structure

aws-athena-mcp/
├── src/athena_mcp/          # Main package
│   ├── server.py            # MCP server
│   ├── athena.py            # AWS Athena client
│   ├── config.py            # Configuration
│   └── models.py            # Data models
├── src/tools/               # MCP tools
│   ├── query.py             # Query tools
│   └── schema.py            # Schema tools
├── tests/                   # Test suite
├── examples/                # Usage examples
├── scripts/                 # Utility scripts
└── docs/                    # Documentation

Adding New Tools

1. Create tool functions in src/tools/
2. Register them in the appropriate module
3. Add tests in tests/
4. Update documentation

Example:

# In src/tools/query.py
def register_query_tools(mcp, athena_client):
    @mcp.tool()
    async def my_new_tool(param: str) -> str:
        """My new tool description."""
        # Implementation here
        return result

🔍 Troubleshooting

Common Issues

Configuration Error

❌ Configuration error: ATHENA_S3_OUTPUT_LOCATION environment variable is required

Solution: Set the required environment variable:

export ATHENA_S3_OUTPUT_LOCATION=s3://your-bucket/results/

AWS Credentials Error

❌ AWS credentials error: AWS credentials not found

Solution: Configure AWS credentials (see Configuration section)

Permission Denied

❌ AWS credentials error: AWS credentials are invalid or insufficient permissions

Solution: Ensure your AWS credentials have these permissions:

• athena:StartQueryExecution
• athena:GetQueryExecution
• athena:GetQueryResults
• athena:ListWorkGroups
• s3:GetObject, s3:PutObject on your S3 bucket

Debug Mode

Enable debug logging:

export PYTHONPATH=src
python -c "
import logging
logging.basicConfig(level=logging.DEBUG)
from athena_mcp.server import main
main()
"

📄 License

MIT License - see LICENSE file for details.

🤝 Contributing

Contributions welcome! Please read our contributing guidelines and:

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests
5. Submit a pull request

📞 Support

• Issues: GitHub Issues
• Discussions: GitHub Discussions
• Documentation: docs/

---

Made with ❤️ for the MCP community