cancel_job

THE RISK

High Risk

Why cancel_job needs a policy

Cancelling a running job is an operational action that terminates an in-progress execution. It is not purely reading data, nor does it delete/overwrite stored data irreversibly, but it does affect the runtime state of an external operation. Execute is the most appropriate category as it triggers an external operation (job termination) whose effects depend on which job is targeted.

From the tool's definition Cancel a running async job

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

POLICY

How to control cancel_job

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

policy.json

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

cancel_job 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 Web Scraper — 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 →

Free to start. No card required.

EXPLORE

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All 62 Web Scraper tools →

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Go deeper

High-risk tools in Web Scraper → 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 →

FAQ

Questions about cancel_job

What does the cancel_job tool do? +

Cancel a running async job. It is categorised as a Execute tool in the Web Scraper 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_job? +

Register the Web Scraper MCP server in PolicyLayer and add a rule for cancel_job: 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 Web Scraper. Nothing to install.

What risk level is cancel_job? +

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

Can I rate-limit cancel_job? +

Yes. Add a rate_limit block to the cancel_job 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_job completely? +

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

cancel_job is provided by the Web Scraper MCP server (imyourboyroy/webscrapertoolkit). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Web Scraper tool call.

Start from Web Scraper, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

CHECK YOUR STACK →