cancel_logs_insight_query

THE RISK

High Risk

Why cancel_logs_insight_query needs a policy

The name suggests cancelling a running CloudWatch Logs Insights query, which is an action that triggers an external operation (stopping an active query execution). This is most likely an Execute-category action. However, the empty description significantly lowers confidence.

From the tool's definition Tool name 'cancel_logs_insight_query' — description is empty and uninformative

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

POLICY

How to control cancel_logs_insight_query

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

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "cancel_logs_insight_query": {
      "limits": [
        {
          "counter": "cancel_logs_insight_query_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

cancel_logs_insight_query 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.

Create a free account and register Amazon ECS MCP Server — nothing to install.
Add this policy — paste it, or build it visually.
Point your MCP client (Claude, Cursor, anything) at your gateway URL.

RATE-LIMIT THIS TOOL →

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EXPLORE

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All 805 Amazon ECS MCP Server tools →

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Go deeper

Govern code and CI agents → Branch allowlists, approval on merges, and rate caps on the build and pipeline tools agents trigger.
High-risk tools in Amazon ECS MCP Server → Every high-risk tool this server exposes, in one view.
All high-risk MCP tools → Every high-risk tool across the catalogue, and the policy pattern that contains them.
The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Agent sandbox → Bounding what an agent can execute and where the boundary should sit.
Least privilege for MCP → Granting agents the minimum tool surface the task needs.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →
PolicyLayer vs alternatives → How deterministic, per-call MCP policy compares with gateways, identity layers, and authorisation platforms.

FAQ

Questions about cancel_logs_insight_query

What does the cancel_logs_insight_query tool do? +

cancel_logs_insight_query. 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.

How do I enforce a policy on cancel_logs_insight_query? +

Register the Amazon ECS MCP Server MCP server in PolicyLayer and add a rule for cancel_logs_insight_query: 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 Amazon ECS MCP Server. Nothing to install.

What risk level is cancel_logs_insight_query? +

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

Can I rate-limit cancel_logs_insight_query? +

Yes. Add a rate_limit block to the cancel_logs_insight_query 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 cancel_logs_insight_query completely? +

Set action: deny in the PolicyLayer policy for cancel_logs_insight_query. 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 cancel_logs_insight_query? +

cancel_logs_insight_query is provided by the Amazon ECS MCP Server MCP server (awslabs.ecs-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 Amazon ECS MCP Server tool call.

Start from Amazon ECS 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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