AWS MCP Server

Retrieve comprehensive AWS cost and usage data with advanced filtering, grouping, and time-based analysis. This tool provides detailed cost analysis across AWS services, accounts, and custom dimensions. Essential for cost optimization, budgeting, chargeback reporting, and financial governance. Supports multiple granularities, cost metrics, and complex filtering for precise analysis. **Required Parameters:** - profile_name (str): AWS profile name from ~/.aws/credentials - region (str): AWS region (e.g., 'us-east-1') - Cost Explorer is global but requires region - start (str): Start date in YYYY-MM-DD format (e.g., '2024-01-01') - end (str): End date in YYYY-MM-DD format (e.g., '2024-01-31') * Maximum 12 months range for daily data * Maximum 12 months range for monthly data * Maximum 1 week range for hourly data **Optional Parameters:** - granularity (str): Time granularity for cost breakdown. Default: 'MONTHLY' * 'DAILY': Day-by-day cost breakdown (max 12 months) * 'MONTHLY': Month-by-month cost breakdown (max 12 months) * 'HOURLY': Hour-by-hour cost breakdown (max 1 week) - group_by (List[Dict[str, str]]): Grouping dimensions for cost analysis **Service Grouping:** [{'Type': 'DIMENSION', 'Key': 'SERVICE'}] - Group by AWS service **Account Grouping:** [{'Type': 'DIMENSION', 'Key': 'LINKED_ACCOUNT'}] - Group by AWS account **Geographic Grouping:** [{'Type': 'DIMENSION', 'Key': 'REGION'}] - Group by AWS region [{'Type': 'DIMENSION', 'Key': 'AVAILABILITY_ZONE'}] - Group by AZ **Resource Grouping:** [{'Type': 'DIMENSION', 'Key': 'INSTANCE_TYPE'}] - Group by EC2 instance type [{'Type': 'DIMENSION', 'Key': 'USAGE_TYPE'}] - Group by usage type [{'Type': 'DIMENSION', 'Key': 'OPERATION'}] - Group by operation **Tag-based Grouping:** [{'Type': 'TAG', 'Key': 'Environment'}] - Group by Environment tag [{'Type': 'TAG', 'Key': 'Project'}] - Group by Project tag [{'Type': 'TAG', 'Key': 'Owner'}] - Group by Owner tag **Multiple Grouping:** [{'Type': 'DIMENSION', 'Key': 'SERVICE'}, {'Type': 'TAG', 'Key': 'Environment'}] - metrics (List[str]): Cost metrics to retrieve. Default: ['BlendedCost'] * 'BlendedCost': Cost after applying Reserved Instance and Savings Plans discounts * 'UnblendedCost': On-demand cost without discounts * 'NetBlendedCost': BlendedCost minus credits and refunds * 'NetUnblendedCost': UnblendedCost minus credits and refunds * 'UsageQuantity': Usage amount (hours, GB, requests, etc.) * 'NormalizedUsageAmount': Usage normalized to equivalent units - filter_expression (Dict[str, Any]): Advanced filtering for targeted analysis **Service Filters:** {'Dimensions': {'Key': 'SERVICE', 'Values': ['Amazon Elastic Compute Cloud - Compute']}} **Account Filters:** {'Dimensions': {'Key': 'LINKED_ACCOUNT', 'Values': ['123456789012']}} **Region Filters:** {'Dimensions': {'Key': 'REGION', 'Values': ['us-east-1', 'us-west-2']}} **Tag Filters:** {'Tags': {'Key': 'Environment', 'Values': ['production', 'staging']}} **Complex Filters (AND/OR/NOT):** {'And': [{'Dimensions': {'Key': 'SERVICE', 'Values': ['EC2']}}, {'Tags': {'Key': 'Environment', 'Values': ['production']}}]} - next_page_token (str): Pagination token from previous response * Use NextPageToken from previous call for large datasets **Common Use Cases:** 1. **Monthly service breakdown:** granularity='MONTHLY', group_by=[{'Type': 'DIMENSION', 'Key': 'SERVICE'}] 2. **Daily cost trends:** granularity='DAILY', metrics=['BlendedCost'] 3. **Environment cost analysis:** group_by=[{'Type': 'TAG', 'Key': 'Environment'}] 4. **EC2 cost optimization:** filter_expression={'Dimensions': {'Key': 'SERVICE', 'Values': ['Amazon Elastic Compute Cloud - Compute']}} 5. **Multi-account analysis:** group_by=[{'Type': 'DIMENSION', 'Key': 'LINKED_ACCOUNT'}] 6. **Regional cost comparison:** group_by=[{'Type': 'DIMENSION', 'Key': 'REGION'}] **Response includes:** Time periods, cost amounts by specified metrics, grouping dimensions, and metadata for comprehensive cost analysis and reporting. **Best Practices:** - Use monthly granularity for trend analysis - Apply service filters to focus on specific cost areas - Combine dimension and tag grouping for detailed insights - Use pagination for large datasets - Consider NetBlendedCost for accurate cost reporting

Retrieve detailed AWS cost and usage data with individual resource-level granularity and identification. This tool provides the most granular cost analysis available, showing costs for individual AWS resources such as specific EC2 instances, RDS databases, and S3 buckets. Essential for detailed cost allocation, rightsizing analysis, and identifying cost optimization opportunities at the resource level. **Required Parameters:** - profile_name (str): AWS profile name from ~/.aws/credentials - region (str): AWS region (e.g., 'us-east-1') - Cost Explorer is global but requires region - start (str): Start date in YYYY-MM-DD format (e.g., '2024-01-01') - end (str): End date in YYYY-MM-DD format (e.g., '2024-01-31') * **Note:** Maximum 14 days range for resource-level data * Hourly granularity not supported for resource-level analysis **Optional Parameters:** - granularity (str): Time granularity for cost breakdown. Default: 'MONTHLY' * 'DAILY': Day-by-day resource cost breakdown (max 14 days) * 'MONTHLY': Month-by-month resource cost breakdown (max 14 days) * **Note:** HOURLY not supported for resource-level data - group_by (List[Dict[str, str]]): Grouping dimensions for resource analysis **Resource Grouping:** [{'Type': 'DIMENSION', 'Key': 'RESOURCE_ID'}] - Group by individual resources **Service + Resource:** [{'Type': 'DIMENSION', 'Key': 'SERVICE'}, {'Type': 'DIMENSION', 'Key': 'RESOURCE_ID'}] **Tag-based Resource Analysis:** [{'Type': 'TAG', 'Key': 'Name'}, {'Type': 'DIMENSION', 'Key': 'RESOURCE_ID'}] [{'Type': 'TAG', 'Key': 'Environment'}, {'Type': 'DIMENSION', 'Key': 'RESOURCE_ID'}] - metrics (List[str]): Cost metrics to retrieve. Default: ['BlendedCost'] * 'BlendedCost': Cost after applying Reserved Instance and Savings Plans discounts * 'UnblendedCost': On-demand cost without discounts * 'NetBlendedCost': BlendedCost minus credits and refunds * 'NetUnblendedCost': UnblendedCost minus credits and refunds * 'UsageQuantity': Resource usage amount (hours, GB, requests, etc.) * 'NormalizedUsageAmount': Usage normalized to equivalent units - filter_expression (Dict[str, Any]): Advanced filtering for targeted resource analysis **Service Filters:** {'Dimensions': {'Key': 'SERVICE', 'Values': ['Amazon Elastic Compute Cloud - Compute']}} **Resource Type Filters:** {'Dimensions': {'Key': 'INSTANCE_TYPE', 'Values': ['t3.micro', 'm5.large']}} **Tag-based Resource Filters:** {'Tags': {'Key': 'Environment', 'Values': ['production']}} {'Tags': {'Key': 'Owner', 'Values': ['team-a', 'team-b']}} **Complex Resource Filters:** {'And': [{'Dimensions': {'Key': 'SERVICE', 'Values': ['EC2']}}, {'Tags': {'Key': 'Environment', 'Values': ['production']}}]} - next_page_token (str): Pagination token from previous response * Essential for resource-level data due to large result sets **Common Use Cases:** 1. **EC2 instance cost analysis:** filter_expression={'Dimensions': {'Key': 'SERVICE', 'Values': ['Amazon Elastic Compute Cloud - Compute']}} group_by=[{'Type': 'DIMENSION', 'Key': 'RESOURCE_ID'}] 2. **RDS database cost breakdown:** filter_expression={'Dimensions': {'Key': 'SERVICE', 'Values': ['Amazon Relational Database Service']}} group_by=[{'Type': 'DIMENSION', 'Key': 'RESOURCE_ID'}] 3. **S3 bucket cost analysis:** filter_expression={'Dimensions': {'Key': 'SERVICE', 'Values': ['Amazon Simple Storage Service']}} group_by=[{'Type': 'DIMENSION', 'Key': 'RESOURCE_ID'}] 4. **Team-based resource costs:** filter_expression={'Tags': {'Key': 'Team', 'Values': ['backend', 'frontend']}} group_by=[{'Type': 'TAG', 'Key': 'Team'}, {'Type': 'DIMENSION', 'Key': 'RESOURCE_ID'}] 5. **Environment resource breakdown:** filter_expression={'Tags': {'Key': 'Environment', 'Values': ['production']}} group_by=[{'Type': 'DIMENSION', 'Key': 'RESOURCE_ID'}] **Response includes:** Time periods, individual resource identifiers, cost amounts, resource metadata, and grouping dimensions for granular cost analysis. **Important Limitations:** - Maximum 14-day date range (AWS limitation for resource-level data) - Large result sets require pagination - Not all services provide resource-level cost data - Higher API costs compared to standard cost analysis **Best Practices:** - Use specific service filters to reduce data volume - Implement pagination for comprehensive analysis - Focus on high-cost services for optimization - Combine with tagging strategies for better insights - Use for detailed cost allocation and chargeback reporting

Retrieve detailed information about EC2 instances with advanced filtering and pagination. This tool provides comprehensive instance data including state, type, networking, tags, and configuration. Essential for inventory management, monitoring, and troubleshooting EC2 infrastructure. **Required Parameters:** - profile_name (str): AWS profile name from ~/.aws/credentials - region (str): AWS region (e.g., 'us-east-1', 'eu-west-1') **Optional Parameters:** - instance_ids (List[str]): Specific instance IDs to retrieve Example: ['i-1234567890abcdef0', 'i-0987654321fedcba0'] - filters (Dict[str, Any]): Advanced filtering options **Instance State Filters:** - 'instance-state-name': ['pending', 'running', 'shutting-down', 'terminated', 'stopping', 'stopped'] **Instance Type Filters:** - 'instance-type': ['t2.micro', 't3.small', 'm5.large', 'c5.xlarge'] **Network Filters:** - 'vpc-id': ['vpc-12345678'] - Filter by VPC - 'subnet-id': ['subnet-12345678'] - Filter by subnet - 'private-ip-address': ['10.0.1.100'] - Filter by private IP - 'public-ip-address': ['54.123.45.67'] - Filter by public IP **Tag Filters:** - 'tag:Name': ['web-server', 'database'] - Filter by Name tag - 'tag:Environment': ['production', 'staging'] - Filter by Environment tag - 'tag-key': ['Owner'] - Filter by tag key existence **Security and Compliance:** - 'security-group-id': ['sg-12345678'] - Filter by security group - 'key-name': ['my-key-pair'] - Filter by key pair - 'monitoring-state': ['enabled', 'disabled'] - Filter by detailed monitoring **Architecture Filters:** - 'architecture': ['i386', 'x86_64', 'arm64'] - Filter by architecture - 'root-device-type': ['ebs', 'instance-store'] - Filter by root device type - 'virtualization-type': ['hvm', 'paravirtual'] - Filter by virtualization - max_results (int): Limit results (1-1000). Default: no limit - next_token (str): Pagination token from previous request **Common Use Cases:** 1. List all running instances: filters={'instance-state-name': ['running']} 2. Find instances by tag: filters={'tag:Environment': ['production']} 3. Get instances in specific VPC: filters={'vpc-id': ['vpc-12345678']} 4. Find instances by type: filters={'instance-type': ['t3.micro', 't3.small']} 5. Security audit: filters={'security-group-id': ['sg-12345678']} **Response includes:** Instance ID, state, type, AMI ID, key name, launch time, networking details, security groups, tags, monitoring state, and more. Use pagination with max_results and next_token for large environments.

Retrieve detailed security group information with comprehensive filtering for network security analysis. This tool provides complete security group data including ingress/egress rules, associated resources, and tags. Critical for security auditing, compliance checking, and network troubleshooting. **Required Parameters:** - profile_name (str): AWS profile name from ~/.aws/credentials - region (str): AWS region (e.g., 'us-east-1', 'eu-west-1') **Optional Parameters:** - group_ids (List[str]): Specific security group IDs to retrieve Example: ['sg-12345678', 'sg-87654321'] - group_names (List[str]): Security group names (VPC security groups use IDs, not names) Example: ['web-server-sg', 'database-sg'] - filters (Dict[str, Any]): Advanced filtering options **Basic Filters:** - 'group-name': ['web-server-sg', 'database-sg'] - Filter by name - 'group-id': ['sg-12345678'] - Filter by ID - 'description': ['Web server security group'] - Filter by description **Network Filters:** - 'vpc-id': ['vpc-12345678'] - Filter by VPC (most common) - 'owner-id': ['123456789012'] - Filter by AWS account ID **Rule-based Filters:** - 'ip-protocol': ['tcp', 'udp', 'icmp'] - Filter by protocol - 'from-port': [22, 80, 443] - Filter by port range start - 'to-port': [22, 80, 443] - Filter by port range end - 'cidr': ['10.0.0.0/16', '0.0.0.0/0'] - Filter by CIDR block **Tag Filters:** - 'tag:Name': ['web-tier', 'db-tier'] - Filter by Name tag - 'tag:Environment': ['production', 'staging'] - Filter by Environment tag - 'tag-key': ['Owner'] - Filter by tag key existence - max_results (int): Limit results (5-1000). Default: no limit - next_token (str): Pagination token from previous request **Common Use Cases:** 1. Audit VPC security groups: filters={'vpc-id': ['vpc-12345678']} 2. Find groups allowing SSH: filters={'from-port': [22], 'to-port': [22]} 3. Security compliance check: filters={'cidr': ['0.0.0.0/0']} (find public access) 4. Find groups by tag: filters={'tag:Environment': ['production']} 5. Owner-based filtering: filters={'owner-id': ['123456789012']} **Response includes:** Group ID, name, description, VPC ID, owner ID, ingress/egress rules (with ports, protocols, source/destination), tags, and associated resources. Essential for security auditing and network access control management.

Retrieve comprehensive VPC information with advanced filtering for network infrastructure analysis. This tool provides complete VPC data including CIDR blocks, DNS settings, tenancy, and associated resources. Essential for network planning, security auditing, and infrastructure management. **Required Parameters:** - profile_name (str): AWS profile name from ~/.aws/credentials - region (str): AWS region (e.g., 'us-east-1', 'eu-west-1') **Optional Parameters:** - vpc_ids (List[str]): Specific VPC IDs to retrieve Example: ['vpc-12345678', 'vpc-87654321'] - filters (Dict[str, Any]): Advanced filtering options **State Filters:** - 'state': ['pending', 'available'] - Filter by VPC state **Network Configuration:** - 'cidr': ['10.0.0.0/16', '172.16.0.0/12'] - Filter by primary CIDR block - 'cidr-block-association.cidr-block': ['10.1.0.0/16'] - Filter by any CIDR block - 'cidr-block-association.state': ['associated', 'associating', 'disassociated'] **DNS and Networking:** - 'dhcp-options-id': ['dopt-12345678'] - Filter by DHCP options set - 'dns-resolution': ['true', 'false'] - Filter by DNS resolution support - 'dns-hostnames': ['true', 'false'] - Filter by DNS hostnames support **Default VPC:** - 'is-default': ['true', 'false'] - Filter default vs custom VPCs **Tenancy:** - 'instance-tenancy': ['default', 'dedicated', 'host'] - Filter by instance tenancy **Ownership:** - 'owner-id': ['123456789012'] - Filter by AWS account ID **Tag Filters:** - 'tag:Name': ['production-vpc', 'staging-vpc'] - Filter by Name tag - 'tag:Environment': ['production', 'staging'] - Filter by Environment tag - 'tag-key': ['Owner'] - Filter by tag key existence - max_results (int): Limit results (5-1000). Default: no limit - next_token (str): Pagination token from previous request **Common Use Cases:** 1. Find default VPC: filters={'is-default': ['true']} 2. List production VPCs: filters={'tag:Environment': ['production']} 3. Find VPCs with specific CIDR: filters={'cidr': ['10.0.0.0/16']} 4. Audit DNS settings: filters={'dns-resolution': ['true']} 5. Check tenancy: filters={'instance-tenancy': ['dedicated']} **Response includes:** VPC ID, state, CIDR blocks, DNS resolution settings, DHCP options, instance tenancy, default VPC flag, owner ID, tags, and associated CIDR block associations. Critical for network architecture planning and security compliance auditing.

Retrieve comprehensive RDS database instance information with advanced filtering and pagination. This tool provides detailed information about RDS database instances including configuration, status, performance settings, and security details. Essential for database monitoring, compliance auditing, and operational management. **Required Parameters:** - profile_name (str): AWS profile name from ~/.aws/credentials - region (str): AWS region (e.g., 'us-east-1', 'eu-west-1') **Optional Parameters:** - db_instance_identifier (str): Specific database instance identifier Example: 'production-mysql-db', 'staging-postgres-01' - filters (Dict[str, Any]): Advanced filtering options **Engine Filters:** - 'engine': Database engine types * MySQL: ['mysql'] * PostgreSQL: ['postgres'] * Oracle: ['oracle-ee', 'oracle-se2', 'oracle-se1', 'oracle-se'] * SQL Server: ['sqlserver-ex', 'sqlserver-web', 'sqlserver-se', 'sqlserver-ee'] * MariaDB: ['mariadb'] * Aurora: ['aurora-mysql', 'aurora-postgresql'] **Version Filters:** - 'engine-version': ['8.0.35', '13.7', '19.0.0.0.ru-2023-01.rur-2023-01.r1'] **Instance Class Filters:** - 'db-instance-class': ['db.t3.micro', 'db.r5.large', 'db.m5.xlarge'] **Status Filters:** - 'db-instance-status': ['available', 'creating', 'deleting', 'modifying', 'rebooting', 'stopped'] **Network Filters:** - 'vpc-id': ['vpc-12345678'] - Filter by VPC - 'subnet-group-name': ['default', 'custom-subnet-group'] **Availability Filters:** - 'availability-zone': ['us-east-1a', 'us-east-1b'] - 'multi-az': ['true', 'false'] - Multi-AZ deployment filter **Security Filters:** - 'db-security-group': ['sg-12345678'] - VPC security groups - 'db-parameter-group': ['default.mysql8.0', 'custom-params'] **Backup and Maintenance:** - 'backup-retention-period': ['7', '14', '30'] - Backup retention days - 'maintenance-window': ['sun:05:00-sun:06:00'] - Maintenance window **Performance Insights:** - 'performance-insights-enabled': ['true', 'false'] - 'monitoring-interval': ['0', '60', '300'] - Enhanced monitoring interval - max_records (int): Maximum results per request (20-100) * Default: 100 * Use smaller values for memory efficiency * Combine with pagination for large fleets - marker (str): Pagination marker from previous response * Use 'Marker' value from previous call * Enables seamless pagination through large DB fleets **Common Use Cases:** 1. **Production DB audit:** filters={'engine': ['mysql'], 'db-instance-status': ['available']} 2. **Multi-AZ check:** filters={'multi-az': ['true']} 3. **Security audit:** filters={'vpc-id': ['vpc-12345678']} 4. **Performance monitoring:** filters={'performance-insights-enabled': ['true']} 5. **Backup compliance:** filters={'backup-retention-period': ['7', '14', '30']} 6. **Engine version check:** filters={'engine': ['mysql'], 'engine-version': ['8.0.35']} **Response includes:** DB instance identifier, status, engine details, instance class, availability zone, VPC security groups, parameter groups, backup settings, performance insights status, monitoring configuration, endpoint information, and more. **Use Cases:** - Database inventory and compliance reporting - Performance monitoring and optimization - Security auditing and configuration review - Backup and disaster recovery planning - Cost optimization and rightsizing analysis Essential for comprehensive RDS fleet management and operational visibility.

A generic AWS SDK wrapper to call any AWS service and operation. Args: service_name (str): The name of the AWS service to call (e.g. 's3', 'ec2', 'rds', etc.). operation_name (str): The name of the operation to call (e.g. 'list_buckets', 'describe_instances', etc.). region_name (str): The AWS region to use. profile_name (str): The name of the AWS profile to use. operation_kwargs (dict): The arguments to pass to the operation. Returns: Any: The response from the AWS service. Example: aws_sdk_wrapper('ce', 'get_cost_and_usage_with_resources', region_name='us-east-1', profile_name='my_profile', operation_kwargs={'TimePeriod': {'Start': '2023-01-01', 'End': '2023-01-31'}, 'Granularity': 'MONTHLY', 'GroupBy': [{'Type': 'DIMENSION', 'Key': 'SERVICE'}], 'Metrics': ['BlendedCost']})

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.