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.
- 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
# From PyPI with uv (recommended for Claude Desktop)
uv tool 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 .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# Start the MCP server (if installed with uv tool install)
aws-athena-mcp
# Or run directly with uv (without installing)
uv tool run aws-athena-mcp
# Or run directly with uvx (without installing)
uvx aws-athena-mcp
# Or run directly with Python
python -m athena_mcp.serverThat's it! The server is now running and ready to accept MCP connections.
To use this MCP server with Claude Desktop:
Download and install Claude Desktop if you haven't already.
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 (Option 1 - Using uvx - Recommended):
{
"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"
}
}
}
}Configuration (Option 2 - Using installed tool):
{
"mcpServers": {
"aws-athena-mcp": {
"command": "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"
}
}
}
}Configuration (Option 3 - Using uv tool run):
{
"mcpServers": {
"aws-athena-mcp": {
"command": "uv",
"args": [
"tool",
"run",
"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"
}
}
}
}Recommended approach: Use Option 1 (uvx) for the most common MCP setup pattern. Option 2 (installed tool) offers better performance as it avoids package resolution on each startup.
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-profileRestart Claude Desktop to load the new MCP server configuration.
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]
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.pyThe script will:
- Check if uv 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 settingsThe server uses environment variables for configuration:
| Variable | Required | Default | Description |
|---|---|---|---|
ATHENA_S3_OUTPUT_LOCATION |
β | - | S3 path for query results |
AWS_REGION |
β | us-east-1 |
AWS region |
ATHENA_WORKGROUP |
β | None |
Athena workgroup |
ATHENA_TIMEOUT_SECONDS |
β | 60 |
Query timeout |
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 neededUse 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-
Use IAM Roles (recommended for production):
# No credentials needed - uses instance/container role export ATHENA_S3_OUTPUT_LOCATION=s3://your-bucket/results/
-
Use AWS CLI profiles (recommended for development):
aws configure --profile athena-mcp export AWS_PROFILE=athena-mcp -
Use temporary credentials when possible:
aws sts assume-role --role-arn arn:aws:iam::123456789012:role/AthenaRole \ --role-session-name athena-mcp-session
-
Avoid long-term access keys in environment variables
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": "*"
}
]
}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
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
Enable CloudTrail logging for Athena:
{
"eventVersion": "1.05",
"userIdentity": {...},
"eventTime": "2024-01-01T12:00:00Z",
"eventSource": "athena.amazonaws.com",
"eventName": "StartQueryExecution",
"resources": [...]
}The server provides these MCP tools:
run_query- Execute SQL queries against Athenaget_status- Check query execution statusget_result- Get results for completed queries
list_tables- List all tables in a databasedescribe_table- Get detailed table schema
# 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
})# 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"
})# 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"]
})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# 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 srcaws-athena-mcp/
βββ src/athena_mcp/ # Main package
β βββ server.py # MCP server
β βββ athena.py # AWS Athena client
β βββ config.py # Configuration
β βββ models.py # Data models
βββ src/tools/ # MCP tools
β βββ query.py # Query tools
β βββ schema.py # Schema tools
βββ tests/ # Test suite
βββ examples/ # Usage examples
βββ scripts/ # Utility scripts
βββ docs/ # Documentation
- Create tool functions in
src/tools/ - Register them in the appropriate module
- Add tests in
tests/ - 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 resultConfiguration Error
β 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
β AWS credentials error: AWS credentials not found
Solution: Configure AWS credentials (see Configuration section)
Permission Denied
β AWS credentials error: AWS credentials are invalid or insufficient permissions
Solution: Ensure your AWS credentials have these permissions:
athena:StartQueryExecutionathena:GetQueryExecutionathena:GetQueryResultsathena:ListWorkGroupss3:GetObject,s3:PutObjecton your S3 bucket
Enable debug logging:
export PYTHONPATH=src
python -c "
import logging
logging.basicConfig(level=logging.DEBUG)
from athena_mcp.server import main
main()
"MIT License - see LICENSE file for details.
Contributions welcome! Please read our contributing guidelines and:
- Fork the repository
- Create a feature branch
- Make your changes
- Add tests
- Submit a pull request
- Issues: GitHub Issues
- Discussions: GitHub Discussions
- Documentation: docs/
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