High Risk →

call_aws

call_aws

How to control call_aws ↓

What call_aws does on CloudWatch Application Signals MCP Server

AI agents invoke call_aws to trigger actions in CloudWatch Application Signals MCP Server. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.

High Risk

Why call_aws needs a policy

The name 'call_aws' strongly implies execution of arbitrary AWS API calls. Given the sibling tools include destructive and write operations (add_inline_policy, add_user_to_group, etc.), this tool likely enables broad AWS operations. With no description to constrain its scope, it could cover any AWS service action including destructive or financial ones.

From the tool's definition Tool name is 'call_aws' on an AWS MCP server; description is empty and uninformative.

Documented attack patterns abuse exactly the kind of access call_aws gives an agent:

How to control call_aws

PolicyLayer is an MCP gateway — it sits between your AI agents and CloudWatch Application Signals MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for call_aws:

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "call_aws": {
      "limits": [
        {
          "counter": "call_aws_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

call_aws stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.

  1. Create a free account and register CloudWatch Application Signals MCP Server — nothing to install.
  2. Add this policy — paste it, or build it visually.
  3. Point your MCP client (Claude, Cursor, anything) at your gateway URL.
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Related tools and policies

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Questions about call_aws

What does the call_aws tool do? +

call_aws. It is categorised as a Execute tool in the CloudWatch Application Signals MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on call_aws? +

Register the CloudWatch Application Signals MCP Server MCP server in PolicyLayer and add a rule for call_aws: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches CloudWatch Application Signals MCP Server. Nothing to install.

What risk level is call_aws? +

call_aws is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit call_aws? +

Yes. Add a rate_limit block to the call_aws rule in your PolicyLayer 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.

How do I block call_aws completely? +

Set action: deny in the PolicyLayer policy for call_aws. 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.

What MCP server provides call_aws? +

call_aws is provided by the CloudWatch Application Signals MCP Server MCP server (awslabs.cloudwatch-applicationsignals-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every CloudWatch Application Signals MCP Server tool call.

Start from CloudWatch Application Signals MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

Free to start. No card required.

805 CloudWatch Application Signals MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.

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