AWS MCP Server

Retrieve CloudWatch metric statistics with full configurability for monitoring AWS resources. This tool fetches time-series data points for CloudWatch metrics, supporting custom statistics, dimensions, and time ranges. Essential for monitoring EC2 instances, RDS databases, Lambda functions, and other AWS services. **Required Parameters:** - profile_name (str): AWS profile name from ~/.aws/credentials - region (str): AWS region (e.g., 'us-east-1', 'eu-west-1') - metric_name (str): CloudWatch metric name (e.g., 'CPUUtilization', 'NetworkIn', 'DatabaseConnections') - namespace (str): AWS service namespace (e.g., 'AWS/EC2', 'AWS/RDS', 'AWS/Lambda') - start_time (str): Start time in ISO 8601 format (e.g., '2024-01-01T00:00:00Z') - end_time (str): End time in ISO 8601 format (e.g., '2024-01-02T00:00:00Z') - period (int): Data point interval in seconds (60, 300, 3600, etc. - must align with metric resolution) **Optional Parameters:** - statistics (List[str]): Standard statistics to calculate. Default: ['Average'] Options: 'Average', 'Sum', 'SampleCount', 'Maximum', 'Minimum' Example: ['Average', 'Maximum'] for CPU utilization trends - extended_statistics (List[str]): Percentile statistics for detailed analysis Format: 'p{percentile}' (e.g., 'p99', 'p95', 'p90', 'p50') Example: ['p99', 'p95'] for latency analysis - dimensions (List[Dict[str, str]]): Filter metrics by specific resource attributes Common dimension examples: * EC2: [{'Name': 'InstanceId', 'Value': 'i-1234567890abcdef0'}] * RDS: [{'Name': 'DBInstanceIdentifier', 'Value': 'mydb-instance'}] * Lambda: [{'Name': 'FunctionName', 'Value': 'my-function'}] * ELB: [{'Name': 'LoadBalancerName', 'Value': 'my-load-balancer'}] - unit (str): Expected unit of measurement for validation Common units: 'Seconds', 'Percent', 'Count', 'Bytes', 'Bits/Second' **Common Use Cases:** 1. Monitor EC2 CPU: namespace='AWS/EC2', metric_name='CPUUtilization', statistics=['Average', 'Maximum'] 2. Track RDS connections: namespace='AWS/RDS', metric_name='DatabaseConnections', statistics=['Average'] 3. Lambda duration analysis: namespace='AWS/Lambda', metric_name='Duration', extended_statistics=['p99', 'p95'] 4. ELB response times: namespace='AWS/ELB', metric_name='Latency', extended_statistics=['p95', 'p99'] **Time Range Guidelines:** - For high-resolution metrics: Use 60-second periods, max 3 hours of data - For standard metrics: Use 300-second periods, up to 15 days of data - For long-term analysis: Use 3600-second periods, up to 455 days of data Returns detailed metric data points with timestamps, values, and units for analysis and alerting.