> For the complete documentation index, see [llms.txt](https://docs.natoma.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.natoma.ai/apps/aws-cloudwatch.md).

# AWS CloudWatch

**Type:** Official

**Source Type:** Repository

**Source:** [GitHub](https://github.com/awslabs/mcp/tree/main/src/cloudwatch-mcp-server)

**Description:** AWS CloudWatch MCP server enables AI assistants to query metrics, analyze alarms, and search logs using CloudWatch Logs Insights. It is useful for incident investigation, observability workflows, and on-call triage directly from your AI assistant.

**Configuration Parameters:**

* **AwsAccessKey ID** \* - AWS access key ID for authentication
* **AwsRegion** \* - AWS region for API requests (e.g., `us-east-1`)
* **AwsSecretAccessKey** \* - AWS secret access key for authentication
* **AwsSessionToken** \* - Session token for temporary AWS credentials
* **FastmcpLogLevel** - Logging level for the server (optional). Default: `ERROR`

**Setup Steps:**

1. Log in to the AWS Console and navigate to IAM.
2. Create a new IAM user (or select an existing one) for the MCP server.
3. Attach a policy that grants the following CloudWatch and Logs permissions:
   * `cloudwatch:DescribeAlarms`
   * `cloudwatch:DescribeAlarmHistory`
   * `cloudwatch:GetMetricData`
   * `cloudwatch:ListMetrics`
   * `logs:DescribeLogGroups`
   * `logs:DescribeQueryDefinitions`
   * `logs:ListLogAnomalyDetectors`
   * `logs:ListAnomalies`
   * `logs:StartQuery`
   * `logs:GetQueryResults`
   * `logs:StopQuery`
4. Generate an Access Key ID and Secret Access Key for the user. For short-lived credentials, also generate a Session Token via AWS STS.
5. Note the AWS region you want to query (e.g., `us-east-1`).
6. Copy the credentials into the Natoma connector configuration.

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