GetMemUsageData
Retrieve memory utilization metrics for specified Alibaba Cloud ECS instances to monitor performance and optimize resource allocation efficiently.
Instructions
获取内存利用率指标数据
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| InstanceIds | Yes | AlibabaCloud ECS instance ID List | |
| RegionId | No | AlibabaCloud region ID | cn-hangzhou |
Implementation Reference
- Handler function implementing the GetMemUsageData tool (named CMS_GetMemUsageData), which retrieves memory utilization metrics from Alibaba Cloud CMS for given ECS instance IDs.
@tools.append def CMS_GetMemUsageData( InstanceIds: List[str] = Field(description='AlibabaCloud ECS instance ID List'), RegionId: str = Field(description='AlibabaCloud region ID', default='cn-hangzhou') ): """获取内存利用率指标数据""" return _get_cms_metric_data(RegionId, InstanceIds, 'memory_usedutilization') - Core helper function that performs the actual API call to Alibaba Cloud CMS to fetch metric data (e.g., memory_usedutilization for GetMemUsageData).
def _get_cms_metric_data(region_id: str, instance_ids: List[str], metric_name: str): client = create_client(region_id) dimesion = [] for instance_id in instance_ids: dimesion.append({ 'instanceId': instance_id }) describe_metric_last_request = cms_20190101_models.DescribeMetricLastRequest( namespace='acs_ecs_dashboard', metric_name=metric_name, dimensions=json.dumps(dimesion), ) describe_metric_last_resp = client.describe_metric_last(describe_metric_last_request) logger.info(f'CMS Tools response: {describe_metric_last_resp.body}') return describe_metric_last_resp.body.datapoints - src/alibaba_cloud_ops_mcp_server/server.py:84-85 (registration)MCP server registration loop that adds all tools from cms_tools.tools (including CMS_GetMemUsageData) to the FastMCP server instance.
for tool in cms_tools.tools: mcp.tool(tool) - src/alibaba_cloud_ops_mcp_server/tools/cms_tools.py:86-86 (registration)Module-level registration decorator that appends the CMS_GetMemUsageData handler to the cms_tools.tools list, which is later registered in server.py.
@tools.append