AI agents invoke cancel_logs_insight_query to trigger actions in Awslabs Valkey. 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.
The tool name suggests it cancels a running CloudWatch Logs Insights query, which is an action that triggers an external operation (cancellation of an in-progress query). With no description available, confidence is reduced. Cancelling a query is an Execute-level action (stopping a running operation), with medium severity as it could disrupt ongoing log analysis but is generally reversible by re-running the query.
From the tool's definition Tool name: cancel_logs_insight_query — description is empty/uninformative
Documented attack patterns abuse exactly the kind of access cancel_logs_insight_query gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Awslabs Valkey, and nothing reaches the server without passing your rules. This is the rule we recommend for cancel_logs_insight_query:
{
"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.
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cancel_logs_insight_query. It is categorised as a Execute tool in the Awslabs Valkey MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Awslabs Valkey 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 Awslabs Valkey. Nothing to install.
cancel_logs_insight_query 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 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.
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.
cancel_logs_insight_query is provided by the Awslabs Valkey MCP server (awslabs.valkey-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Awslabs Valkey, 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 Awslabs Valkey tools catalogued and risk-classified — across an index of 43,000+ MCP servers.