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AWS Athena MCP: Optimize Queries & Auto-Scale Seamlessly - MCP Implementation

AWS Athena MCP: Optimize Queries & Auto-Scale Seamlessly

Effortlessly run and optimize AWS Athena queries with our MCP server – seamless scaling, robust performance, and cost efficiency guaranteed.

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About AWS Athena MCP

What is AWS Athena MCP: Optimize Queries & Auto-Scale Seamlessly?

AWS Athena MCP is a purpose-built server that bridges AI assistants with AWS Athena, enabling seamless execution of SQL queries against your data lakes. Designed for efficiency and scalability, it optimizes query performance while handling automatic scaling needs, ensuring your analytics workflows run smoothly without manual intervention.

How to Use AWS Athena MCP: Optimize Queries & Auto-Scale Seamlessly?

Getting started is straightforward: first, configure your AWS credentials and set up an S3 bucket for results. Next, integrate the MCP server into your environment by following three core steps: 1) Install dependencies, 2) Configure server parameters, and 3) Initiate query workflows using standardized API calls. The system automatically scales resources based on query load, eliminating manual resource management.

AWS Athena MCP Features

Key Features of AWS Athena MCP

  • Query Optimization Engine: Dynamically tunes SQL execution paths for faster results
  • Auto-Scaling: Automatically provisions resources during peak loads and scales down during idle periods
  • Fail-Safe Execution: Built-in retries and error handling for mission-critical analytics tasks
  • Configurable Limits: Adjust timeout thresholds, concurrency levels, and result caching strategies
  • Seamless Integration: Works natively with existing AWS IAM roles and security groups

Use Cases of AWS Athena MCP

Common scenarios include:

  • Real-time analytics dashboards feeding live data from petabyte-scale datasets
  • Automated ETL processes requiring consistent query performance
  • Machine learning pipelines needing rapid data exploration
  • Compliance reporting with automatic cost optimization for infrequent queries

AWS Athena MCP FAQ

FAQ from AWS Athena MCP

Q: Does it support serverless architectures?
A: Fully serverless - no infrastructure management required

Q: Can I customize query timeout values?
A: Yes, through configurable parameters in server.config.js

Q: How does scaling work under heavy load?
A: Automatically provisions additional workers using AWS Auto Scaling groups

Explore the GitHub repository for implementation details and advanced configurations

Content

@lishenxydlgzs/aws-athena-mcp

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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.

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)
  1. 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
        "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

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
}

Requirements

  • Node.js >= 16
  • AWS credentials with appropriate Athena permissions
  • S3 bucket for query results

License

MIT

Repository

GitHub Repository

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