Waits for ECS tasks in a service to reach RUNNING status. This tool polls the service every 10 seconds to check if tasks are running. It will wait up to the specified timeout before returning a timeout status. ## Parameters: - Required: cluster (ECS cluster name) - Required: service_name (ECS s...
Bulk/mass operation — affects multiple targets
Part of the Amazon ECS MCP Server MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.
AI agents invoke wait_for_service_ready to trigger processes or run actions in Amazon ECS MCP Server. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.
wait_for_service_ready can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. Intercept enforces rate limits and validates arguments to keep execution within safe bounds.
Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.
tools:
wait_for_service_ready:
rules:
- action: allow
rate_limit:
max: 10
window: 60
validate:
required_args: trueSee the full Amazon ECS MCP Server policy for all 10 tools.
Agents calling execute-class tools like wait_for_service_ready have been implicated in these attack patterns. Read the full case and prevention policy for each:
Other tools in the Execute risk category across the catalogue. The same policy patterns (rate-limit, validate) apply to each.
wait_for_service_ready is one of the high-risk operations in Amazon ECS MCP Server. For the full severity-focused view — only the high-risk tools with their recommended policies — see the breakdown for this server, or browse all high-risk tools across every MCP server.
Waits for ECS tasks in a service to reach RUNNING status. This tool polls the service every 10 seconds to check if tasks are running. It will wait up to the specified timeout before returning a timeout status. ## Parameters: - Required: cluster (ECS cluster name) - Required: service_name (ECS service name) - Optional: timeout_seconds (Max wait time, defaults to 300 seconds) ## Returns: Dictionary containing: - status: "success" if tasks are running, "timeout" if timeout reached, "failed" if an error occurred - message: Human-readable status message ## Usage Examples: ``` # Wait for service with default 5-minute timeout wait_for_service_ready( cluster="my-cluster", service_name="my-service" ) # Wait for service with custom timeout wait_for_service_ready( cluster="my-cluster", service_name="my-service", timeout_seconds=600 ) ``` Returns on success: ``` { "status": "success", "message": "Service is ready with 2 running task(s)" } ``` Returns on timeout: ``` { "status": "timeout", "message": "Timeout after 300s - service not ready" } ```. It is categorised as a Execute tool in the Amazon ECS MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Add a rule in your Intercept YAML policy under the tools section for wait_for_service_ready. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the Amazon ECS MCP Server MCP server.
wait_for_service_ready is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the wait_for_service_ready 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 wait_for_service_ready. 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.
wait_for_service_ready is provided by the Amazon ECS MCP Server MCP server (awslabs.ecs-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.