Manage AWS EMR EC2 instances with both read and write operations. This tool provides comprehensive operations for managing Amazon EMR EC2 instances, including adding and modifying instance fleets and groups, as well as listing instance details. It enables scaling cluster capacity, configuring in...
High parameter count (13 properties)
Part of the Amazon Data Processing MCP Server MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.
AI agents use manage_aws_emr_ec2_instances to create or modify resources in Amazon Data Processing MCP Server. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.
Without a policy, an AI agent could call manage_aws_emr_ec2_instances repeatedly, creating or modifying resources faster than any human could review. Intercept's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Amazon Data Processing MCP Server.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
tools:
manage_aws_emr_ec2_instances:
rules:
- action: allow
rate_limit:
max: 30
window: 60See the full Amazon Data Processing MCP Server policy for all 36 tools.
Agents calling write-class tools like manage_aws_emr_ec2_instances have been implicated in these attack patterns. Read the full case and prevention policy for each:
Other tools in the Write risk category across the catalogue. The same policy patterns (rate-limit, validate) apply to each.
Manage AWS EMR EC2 instances with both read and write operations. This tool provides comprehensive operations for managing Amazon EMR EC2 instances, including adding and modifying instance fleets and groups, as well as listing instance details. It enables scaling cluster capacity, configuring instance specifications, and monitoring instance status. ## Requirements - The server must be run with the `--allow-write` flag for add-instance-fleet, add-instance-groups, modify-instance-fleet, and modify-instance-groups operations - Appropriate AWS permissions for EMR instance operations ## Operations - **add-instance-fleet**: Add an instance fleet to an existing EMR cluster - Required: cluster_id, instance_fleet (with InstanceFleetType) - Returns: cluster_id, instance_fleet_id, cluster_arn - **add-instance-groups**: Add instance groups to an existing EMR cluster - Required: cluster_id, instance_groups (each with InstanceRole, InstanceType, InstanceCount) - Returns: cluster_id (as job_flow_id), instance_group_ids, cluster_arn - **modify-instance-fleet**: Modify an instance fleet in an EMR cluster - Required: cluster_id, instance_fleet_id, instance_fleet_config - Returns: confirmation of modification - **modify-instance-groups**: Modify instance groups in an EMR cluster - Required: instance_group_configs (each with InstanceGroupId) - Optional: cluster_id - Returns: confirmation of modification - **list-instance-fleets**: List all instance fleets in an EMR cluster - Required: cluster_id - Optional: marker - Returns: instance_fleets, marker for pagination - **list-instances**: List all instances in an EMR cluster - Required: cluster_id - Optional: instance_group_id, instance_group_types, instance_fleet_id, instance_fleet_type, instance_states, marker - Returns: instances, marker for pagination - **list-supported-instance-types**: List all supported instance types for EMR - Required: release_label - Optional: marker - Returns: instance_types, marker for pagination ## Example ```python # Add a task instance fleet with mixed instance types response = await manage_aws_emr_ec2_instances( operation='add-instance-fleet', cluster_id='j-123ABC456DEF', instance_fleet={ 'InstanceFleetType': 'TASK', 'Name': 'TaskFleet', 'TargetOnDemandCapacity': 2, 'TargetSpotCapacity': 3, 'InstanceTypeConfigs': [ { 'InstanceType': 'm5.xlarge', 'WeightedCapacity': 1, 'BidPriceAsPercentageOfOnDemandPrice': 80, }, { 'InstanceType': 'm5.2xlarge', 'WeightedCapacity': 2, 'BidPriceAsPercentageOfOnDemandPrice': 75, }, ], }, ) ``` Args: ctx: MCP context operation: Operation to perform cluster_id: ID of the EMR cluster instance_fleet_id: ID of the instance fleet instance_fleet: Instance fleet configuration instance_groups: List of instance group configurations instance_group_configs: List of instance group configurations for modification instance_fleet_config: Instance fleet configuration for modification instance_group_ids: List of instance group IDs instance_states: List of instance states to filter by instance_group_types: List of instance group types to filter by instance_fleet_type: Instance fleet type to filter by release_label: EMR release label for list-supported-instance-types marker: Pagination token for list operations Returns: Union of response types specific to the operation performed. It is categorised as a Write tool in the Amazon Data Processing MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Add a rule in your Intercept YAML policy under the tools section for manage_aws_emr_ec2_instances. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the Amazon Data Processing MCP Server MCP server.
manage_aws_emr_ec2_instances is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the manage_aws_emr_ec2_instances rule in your Intercept policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the Intercept policy for manage_aws_emr_ec2_instances. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
manage_aws_emr_ec2_instances is provided by the Amazon Data Processing MCP Server MCP server (awslabs.aws-dataprocessing-mcp-server). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic policy on every MCP tool call. Per-identity grants. Full audit log.