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Servers/Cloud Platforms/AWS CloudTrail
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AWS CloudTrail

This AWS Labs Model Context Protocol (MCP) server for CloudTrail enables your AI agents to query AWS account activity for security investigations, compliance auditing, and operational troubleshooting.

9.6k starsUpdated Aug 28, 2026
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Overview

This AWS Labs Model Context Protocol (MCP) server for CloudTrail enables your AI agents to query AWS account activity for security investigations, compliance auditing, and operational troubleshooting. It provides comprehensive access to CloudTrail events and CloudTrail Lake analytics, allowing agents to track API calls, analyze user activity, and perform advanced security analysis. This server gives AI agents seamless access to CloudTrail data through standardized MCP interfaces, eliminating the need for custom API integrations and enabling powerful security insights and audit capabilities.

Installation

uvx awslabs.cloudtrail-mcp-server@latest

Configuration

{
  "mcpServers": {
    "awslabs.cloudtrail-mcp-server": {
      "autoApprove": [],
      "disabled": false,
      "command": "uvx",
      "args": [
        "awslabs.cloudtrail-mcp-server@latest"
      ],
      "env": {
        "AWS_PROFILE": "[The AWS Profile Name to use for AWS access]",
        "FASTMCP_LOG_LEVEL": "ERROR"
      },
      "transportType": "stdio"
    }
  }
}

Capabilities

  • Look up recent CloudTrail events

    Search the last 90 days of management events by username, event name, or resource with `lookup_events`.

  • Run SQL analytics on CloudTrail Lake

    Execute Trino-compatible SQL queries against event data stores using `lake_query` for aggregation and filtering.

  • List available event data stores

    Discover configured CloudTrail Lake data stores and their capabilities via `list_event_data_stores`.

  • Monitor long-running Lake queries

    Check the status of submitted queries with `get_query_status` and retrieve paginated results with `get_query_results`.

Tags

  • aws
  • cloud-infrastructure
  • security
  • compliance
  • monitoring

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