cancel_query

A execute tool on the Mcpg MCP server.

SERVERMcpg SOURCEpypi:mcpg

High RISK CLASS

Category Execute

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-devopam-mcpg/cancel-query.md

WHAT IT DOES

What cancel_query does on Mcpg

AI agents invoke cancel_query to trigger actions in Mcpg. 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.

RISK

Why cancel_query is rated High

Cancelling a running query is an active operation that terminates an executing database process. It has side effects (interrupting ongoing operations) but is generally reversible (the query can be re-run), placing it in Execute. Severity is high because an AI agent misusing this could disrupt production database operations. Confidence is reduced due to the empty description.

From the tool's definition Tool name 'cancel_query' — description is empty and uninformative, so relying on name alone.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs cancel_query safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Mcpg, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For cancel_query, this is the rule to start with:

cancel_query Rate-limited

cancel_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.

View as policy code

policy.json

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

RATE-LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Mcpg, apply this rule, and every cancel_query call is checked against it from then on.

FAQ

Questions about cancel_query

What does the cancel_query tool do? +

cancel_query is a execute tool on the Mcpg MCP server. It is categorised as a Execute tool in the Mcpg 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_query? +

Register the Mcpg MCP server in PolicyLayer and add a rule for cancel_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 Mcpg. Nothing to install.

What risk level is cancel_query? +

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

Can I rate-limit cancel_query? +

Yes. Add a rate_limit block to the cancel_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_query completely? +

Set action: deny in the PolicyLayer policy for cancel_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_query? +

cancel_query is provided by the Mcpg MCP server (pypi:mcpg). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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