Suggest AWS CLI commands based on a natural language query. This is a FALLBACK tool to use when you are uncertain about the exact AWS CLI command needed to fulfill a user's request. IMPORTANT: Only use this tool when: 1. You are unsure about the exact AWS service or operation to use ...
Accepts freeform code/query input (query); Single-target operation
Part of the AWS API MCP Server MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.
AI agents may call suggest_aws_commands to permanently remove or destroy resources in AWS API MCP Server. Without a policy, an autonomous agent could delete critical data in a loop with no way to undo the damage. Intercept blocks destructive tools by default and requires explicit human approval before enabling them.
Without a policy, an AI agent could call suggest_aws_commands in a loop, permanently destroying resources in AWS API MCP Server. There is no undo for destructive operations. Intercept blocks this tool by default and only allows it when a human explicitly approves the action.
Destructive tools permanently remove data. Block by default. Only enable with explicit approval workflows.
tools:
suggest_aws_commands:
rules:
- action: deny
reason: "Blocked by default — enable with approval"See the full AWS API MCP Server policy for all 3 tools.
Agents calling destructive-class tools like suggest_aws_commands have been implicated in these attack patterns. Read the full case and prevention policy for each:
Other tools in the Destructive risk category across the catalogue. The same policy patterns (deny, require_approval) apply to each.
suggest_aws_commands is one of the critical-risk operations in AWS API MCP Server. For the full severity-focused view — only the critical-risk tools with their recommended policies — see the breakdown for this server, or browse all critical-risk tools across every MCP server.
Suggest AWS CLI commands based on a natural language query. This is a FALLBACK tool to use when you are uncertain about the exact AWS CLI command needed to fulfill a user's request. IMPORTANT: Only use this tool when: 1. You are unsure about the exact AWS service or operation to use 2. The user's request is ambiguous or lacks specific details 3. You need to explore multiple possible approaches to solve a task 4. You want to provide options to the user for different ways to accomplish their goal DO NOT use this tool when: 1. You are confident about the exact AWS CLI command needed - use 'call_aws' instead 2. The user's request is clear and specific about the AWS service and operation 3. You already know the exact parameters and syntax needed 4. The task requires immediate execution of a known command Best practices for query formulation: 1. Include the user's primary goal or intent 2. Specify any relevant AWS services if mentioned 3. Include important parameters or conditions mentioned 4. Add context about the environment or constraints 5. Mention any specific requirements or preferences CRITICAL: Query Granularity - Each query should be granular enough to be accomplished by a single CLI command - If the user's request requires multiple commands to complete, break it down into individual tasks - Call this tool separately for each specific task to get the most relevant suggestions - Example of breaking down a complex request: User request: "Set up a new EC2 instance with a security group and attach it to an EBS volume" Break down into: 1. "Create a new security group with inbound rules for SSH and HTTP" 2. "Create a new EBS volume with 100GB size" 3. "Launch an EC2 instance with t2.micro instance type" 4. "Attach the EBS volume to the EC2 instance" Query examples: 1. "List all running EC2 instances in us-east-1 region" 2. "Get the size of my S3 bucket named 'my-backup-bucket'" 3. "List all IAM users who have AdministratorAccess policy" 4. "List all Lambda functions in my account" 5. "Create a new S3 bucket with versioning enabled and server-side encryption" 6. "Update the memory allocation of my Lambda function 'data-processor' to 1024MB" 7. "Add a new security group rule to allow inbound traffic on port 443" 8. "Tag all EC2 instances in the 'production' environment with 'Environment=prod'" 9. "Configure CloudWatch alarms for high CPU utilization on my RDS instance" Returns: A list of up to 10 most likely AWS CLI commands that could accomplish the task, including: - The CLI command - Confidence score for the suggestion - Required parameters - Description of what the command does. It is categorised as a Destructive tool in the AWS API MCP Server MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Add a rule in your Intercept YAML policy under the tools section for suggest_aws_commands. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the AWS API MCP Server MCP server.
suggest_aws_commands is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.
Yes. Add a rate_limit block to the suggest_aws_commands 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 suggest_aws_commands. 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.
suggest_aws_commands is provided by the AWS API MCP Server MCP server (awslabs.aws-api-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.