AI agents invoke run_checkov 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.
This tool triggers execution of Checkov, an external scanning/analysis engine. Although Checkov itself is read-focused (static analysis), the 'run_' prefix indicates the MCP server executes it as a subprocess or external operation. This falls into Execute category because it runs an external tool whose behavior and output depend on provided arguments (code/configuration to scan).
From the tool's definition Tool name 'run_checkov' indicates execution of Checkov, an infrastructure-as-code static analysis tool. While the description is empty, the name and context (AWS CloudWatch Application Signals MCP server with sibling tools like analyze_log_group,…
Documented attack patterns abuse exactly the kind of access run_checkov gives an agent:
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 run_checkov:
{
"version": "1",
"default": "deny",
"tools": {
"run_checkov": {
"limits": [
{
"counter": "run_checkov_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
} run_checkov 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.
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run_checkov. 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.
Register the CloudWatch Application Signals MCP Server MCP server in PolicyLayer and add a rule for run_checkov: 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.
run_checkov 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 run_checkov 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.
Set action: deny in the PolicyLayer policy for run_checkov. 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.
run_checkov 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.
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.
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805 CloudWatch Application Signals MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.