feat(cloudwatch-mcp-server): Add Anomaly Detection Alarm recommendation to AWS CloudWatch MCP server

src/cloudwatch-mcp-server/CHANGELOG.md

@@ -6,6 +6,16 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
 ## Unreleased
+
+## [0.0.5] - 2025-10-06
+
+### Added
+- Added tool to analyze CloudWatch Metric data
+
+### Changed
+
+- Updated Alarm recommendation tool to support CloudWatch Anomaly Detection Alarms
+
 ## [0.0.4] - 2025-07-11
 
 ### Changed

src/cloudwatch-mcp-server/README.md

@@ -29,6 +29,7 @@ Alarm Recommendations - Suggests recommended alarm configurations for CloudWatch
 * `get_metric_data` - Retrieves detailed CloudWatch metric data for any CloudWatch metric. Use this for general CloudWatch metrics that aren't specific to Application Signals. Provides ability to query any metric namespace, dimension, and statistic
 * `get_metric_metadata` - Retrieves comprehensive metadata about a specific CloudWatch metric
 * `get_recommended_metric_alarms` - Gets recommended alarms for a CloudWatch metric
+* `analyze_metric` - Analyzes CloudWatch metric data to determine trend, seasonality, and statistical properties
 
 ### Tools for CloudWatch Alarms
 * `get_active_alarms` - Identifies currently active CloudWatch alarms across the account

src/cloudwatch-mcp-server/awslabs/cloudwatch_mcp_server/cloudwatch_metrics/cloudformation_template_generator.py

@@ -0,0 +1,119 @@
+# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import json
+import logging
+import os
+from awslabs.cloudwatch_mcp_server.cloudwatch_metrics.constants import COMPARISON_OPERATOR_ANOMALY
+from jinja2 import Environment, FileSystemLoader, select_autoescape
+from typing import Any, Dict
+
+
+logger = logging.getLogger(__name__)
+
+
+class CloudFormationTemplateGenerator:
+    """Generate CloudFormation JSON for CloudWatch Anomaly Detection Alarms using templates."""
+
+    ANOMALY_DETECTION_ALARM_TEMPLATE = 'anomaly_detection_alarm.json'
+
+    def __init__(self):
+        """Initialize the CloudFormation template generator."""
+        template_dir = os.path.join(os.path.dirname(__file__), 'templates')
+        self.env = Environment(
+            loader=FileSystemLoader(template_dir),
+            autoescape=select_autoescape(['html', 'xml', 'json']),
+        )
+
+    def generate_template(self, alarm_data: Dict[str, Any]) -> Dict[str, Any]:
+        """Generate CFN template for a single CloudWatch Alarm."""
+        if not self._is_anomaly_detection_alarm(alarm_data):
+            return {}
+
+        # Process alarm data and add computed fields
+        formatted_data = self._format_anomaly_detection_alarm_data(alarm_data)
+        alarm_json = self._generate_anomaly_detection_alarm_resource(formatted_data)
+        resources = json.loads(alarm_json)
+
+        final_template = {
+            'AWSTemplateFormatVersion': '2010-09-09',
+            'Description': 'CloudWatch Alarms and Anomaly Detectors',
+            'Resources': resources,
+        }
+
+        return final_template
+
+    def _format_anomaly_detection_alarm_data(self, alarm_data: Dict[str, Any]) -> Dict[str, Any]:
+        """Sanitise alarm data and add computed fields."""
+        formatted_data = alarm_data.copy()
+
+        # Generate alarm name if not provided
+        if 'alarmName' not in formatted_data:
+            metric_name = alarm_data.get('metricName', 'Alarm')
+            namespace = alarm_data.get('namespace', '')
+            formatted_data['alarmName'] = self._generate_alarm_name(metric_name, namespace)
+
+        # Generate resource key (sanitized alarm name for CloudFormation resource)
+        formatted_data['resourceKey'] = self._sanitize_resource_name(formatted_data['alarmName'])
+
+        # Process threshold value
+        threshold = alarm_data.get('threshold', {})
+        formatted_data['sensitivity'] = threshold.get('sensitivity', 2)
+
+        # Set defaults
+        formatted_data.setdefault(
+            'alarmDescription', 'CloudWatch alarm generated by CloudWatch MCP server.'
+        )
+        formatted_data.setdefault('statistic', 'Average')
+        formatted_data.setdefault('period', 300)
+        formatted_data.setdefault('evaluationPeriods', 2)
+        formatted_data.setdefault('datapointsToAlarm', 2)
+        formatted_data.setdefault('comparisonOperator', COMPARISON_OPERATOR_ANOMALY)
+        formatted_data.setdefault('treatMissingData', 'missing')
+        formatted_data.setdefault('dimensions', [])
+
+        return formatted_data
+
+    def _generate_anomaly_detection_alarm_resource(self, alarm_data: Dict[str, Any]) -> str:
+        """Generate CloudWatch anomaly detection alarm template using Jinja2.
+
+        Args:
+            alarm_data: Alarm configuration data
+
+        Returns:
+            str: Generated CloudFormation template
+        """
+        template = self.env.get_template(self.ANOMALY_DETECTION_ALARM_TEMPLATE)
+        alarm_resource = template.render(**alarm_data)
+
+        return alarm_resource
+
+    def _is_anomaly_detection_alarm(self, alarm_data: Dict[str, Any]) -> bool:
+        return alarm_data.get('comparisonOperator') == COMPARISON_OPERATOR_ANOMALY
+
+    def _generate_alarm_name(self, metric_name: str, namespace: str) -> str:
+        """Generate alarm name from metric name and namespace."""
+        return f'{metric_name.capitalize()}{namespace.replace("/", "").replace("AWS", "")}Alarm'
+
+    def _sanitize_resource_name(self, name: str) -> str:
+        """Sanitize name for CloudFormation resource key."""
+        sanitized = name.replace('-', '').replace('_', '').replace('/', '').replace(' ', '')
+        # Validate CloudFormation naming requirements
+        if not sanitized or not sanitized[0].isalpha():
+            logger.warning(f'Invalid resource name: {sanitized} (must start with letter)')
+            sanitized = 'Resource' + sanitized
+        if len(sanitized) > 255:
+            logger.warning(f'Resource name too long ({len(sanitized)} chars), truncating')
+            sanitized = sanitized[:255]
+        return sanitized

src/cloudwatch-mcp-server/awslabs/cloudwatch_mcp_server/cloudwatch_metrics/constants.py

@@ -0,0 +1,42 @@
+# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# CloudWatch MCP Server Constants
+
+# Time constants
+SECONDS_PER_MINUTE = 60
+MINUTES_PER_HOUR = 60
+HOURS_PER_DAY = 24
+DAYS_PER_WEEK = 7
+
+# Analysis period constants
+DEFAULT_ANALYSIS_WEEKS = 2
+DEFAULT_ANALYSIS_PERIOD = (
+    MINUTES_PER_HOUR * HOURS_PER_DAY * DEFAULT_ANALYSIS_WEEKS * DAYS_PER_WEEK
+)  # 2 weeks in minutes
+
+# Threshold constants
+DEFAULT_SENSITIVITY = 2.0
+ANOMALY_DETECTION_TYPE = 'anomaly_detection'
+STATIC_TYPE = 'static'
+COMPARISON_OPERATOR_ANOMALY = 'LessThanLowerOrGreaterThanUpperThreshold'
+TREAT_MISSING_DATA_BREACHING = 'breaching'
+
+# Seasonality constants
+SEASONALITY_STRENGTH_THRESHOLD = 0.6  # See https://robjhyndman.com/hyndsight/tsoutliers/
+ROUNDING_THRESHOLD = 0.1
+
+# Numerical stability
+NUMERICAL_STABILITY_THRESHOLD = 1e-10
+STATISTICAL_SIGNIFICANCE_THRESHOLD = 0.05