databasescloud-infrastructure

AWS Athena

by lishenxydlgzs

AWS Athena connector lets you run SQL on AWS data lakes via Athena in AWS, empowering rapid, large-scale business intell

Integrates with AWS SDK to execute SQL queries against Athena databases, enabling large-scale data analysis and business intelligence for AWS data lakes.

github stars

40

Built-in retry logic with configurable timeoutsSupports multiple AWS credential methods

best for

  • / Data analysts working with AWS data lakes
  • / Business intelligence teams using AWS infrastructure
  • / Backend developers building data-driven applications

capabilities

  • / Execute SQL queries on AWS Athena databases
  • / Retrieve query results from data lake sources
  • / Configure custom workgroups and query timeouts
  • / Handle large-scale data analysis queries

what it does

Execute SQL queries against AWS Athena databases to analyze large-scale data in AWS data lakes. Requires AWS credentials and S3 bucket for query results.

about

AWS Athena is a community-built MCP server published by lishenxydlgzs that provides AI assistants with tools and capabilities via the Model Context Protocol. AWS Athena connector lets you run SQL on AWS data lakes via Athena in AWS, empowering rapid, large-scale business intell It is categorized under databases, cloud infrastructure.

how to install

You can install AWS Athena in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

AWS Athena is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

@lishenxydlgzs/aws-athena-mcp

smithery badge

A Model Context Protocol (MCP) server for running AWS Athena queries. This server enables AI assistants to execute SQL queries against your AWS Athena databases and retrieve results.

<a href="https://glama.ai/mcp/servers/0i7dhkex6t"> <img width="380" height="200" src="https://glama.ai/mcp/servers/0i7dhkex6t/badge" alt="aws-athena-mcp MCP server" /> </a>

Usage

  1. Configure AWS credentials using one of the following methods:

    • AWS CLI configuration
    • Environment variables (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY)
    • IAM role (if running on AWS)
  2. Add the server to your MCP configuration:

{
  "mcpServers": {
    "athena": {
      "command": "npx",
      "args": ["-y", "@lishenxydlgzs/aws-athena-mcp"],
      "env": {
        // Required
        "OUTPUT_S3_PATH": "s3://your-bucket/athena-results/",
        
        // Optional AWS configuration
        "AWS_REGION": "us-east-1",                    // Default: AWS CLI default region
        "AWS_PROFILE": "default",                     // Default: 'default' profile
        "AWS_ACCESS_KEY_ID": "",                      // Optional: AWS access key
        "AWS_SECRET_ACCESS_KEY": "",                  // Optional: AWS secret key
        "AWS_SESSION_TOKEN": "",                      // Optional: AWS session token
        
        // Optional server configuration
        "ATHENA_WORKGROUP": "default_workgroup",      // Optional: specify the Athena WorkGroup
        "QUERY_TIMEOUT_MS": "300000",                 // Default: 5 minutes (300000ms)
        "MAX_RETRIES": "100",                         // Default: 100 attempts
        "RETRY_DELAY_MS": "500"                       // Default: 500ms between retries
      }
    }
  }
}
  1. The server provides the following tools:
  • run_query: Execute a SQL query using AWS Athena

    • Parameters:
      • database: The Athena database to query
      • query: SQL query to execute
      • maxRows: Maximum number of rows to return (default: 1000, max: 10000)
    • Returns:
      • If query completes within timeout: Full query results
      • If timeout reached: Only the queryExecutionId for later retrieval
  • get_status: Check the status of a query execution

    • Parameters:
      • queryExecutionId: The ID returned from run_query
    • Returns:
      • state: Query state (QUEUED, RUNNING, SUCCEEDED, FAILED, or CANCELLED)
      • stateChangeReason: Reason for state change (if any)
      • submissionDateTime: When the query was submitted
      • completionDateTime: When the query completed (if finished)
      • statistics: Query execution statistics (if available)
  • get_result: Retrieve results for a completed query

    • Parameters:
      • queryExecutionId: The ID returned from run_query
      • maxRows: Maximum number of rows to return (default: 1000, max: 10000)
    • Returns:
      • Full query results if the query has completed successfully
      • Error if query failed or is still running
  • list_saved_queries: List all saved (named) queries in Athena.

  • Returns:

    • An array of saved queries with id, name, and optional description
    • Queries are returned from the configured ATHENA_WORKGROUP and AWS_REGION
  • run_saved_query: Run a previously saved query by its ID.

  • Parameters:

    • namedQueryId: ID of the saved query
    • databaseOverride: Optional override of the saved query's default database
    • maxRows: Maximum number of rows to return (default: 1000)
    • timeoutMs: Timeout in milliseconds (default: 60000)
  • Returns:

    • Same behavior as run_query: full results or execution ID

Usage Examples

Show All Databases

Message to AI Assistant: List all databases in Athena

MCP parameter:

{
  "database": "default",
  "query": "SHOW DATABASES"
}

List Tables in a Database

Message to AI Assistant: Show me all tables in the default database

MCP parameter:

{
  "database": "default",
  "query": "SHOW TABLES"
}

Get Table Schema

Message to AI Assistant: What's the schema of the asin_sitebestimg table?

MCP parameter:

{
  "database": "default",
  "query": "DESCRIBE default.asin_sitebestimg"
}

Table Rows Preview

Message to AI Assistant: Show some rows from my_database.mytable

MCP parameter:

{
  "database": "my_database",
  "query": "SELECT * FROM my_table LIMIT 10",
  "maxRows": 10
}

Advanced Query with Filtering and Aggregation

Message to AI Assistant: Find the average price by category for in-stock products

MCP parameter:

{
  "database": "my_database",
  "query": "SELECT category, COUNT(*) as count, AVG(price) as avg_price FROM products WHERE in_stock = true GROUP BY category ORDER BY count DESC",
  "maxRows": 100
}

Checking Query Status

{
  "queryExecutionId": "12345-67890-abcdef"
}

Getting Results for a Completed Query

{
  "queryExecutionId": "12345-67890-abcdef",
  "maxRows": 10
}

Listing Saved Queries

{
  "name": "list_saved_queries",
  "arguments": {}
}

Running a Saved Query

{
  "name": "run_saved_query",
  "arguments": {
    "namedQueryId": "abcd-1234-efgh-5678",
    "maxRows": 100
  }
}

Requirements

  • Node.js >= 16
  • AWS credentials with appropriate Athena and S3 permissions
  • S3 bucket for query results
  • Named queries (optional) must exist in the specified ATHENA_WORKGROUP and AWS_REGION

License

MIT

Repository

GitHub Repository