execute_job

Execute a registered job by name. Supports inline (synchronous) and background execution.

SERVERFrontmcp SOURCEagentfront/frontmcp

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/frontmcp/execute-job.md

WHAT IT DOES

What execute_job does on Frontmcp

AI agents invoke execute_job to trigger actions in Frontmcp. 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 execute_job is rated High

This tool triggers execution of arbitrary registered jobs, which can perform side effects (API calls, database operations, external service calls, etc.). The synchronous/asynchronous execution model and lack of constraints on what jobs can do means an AI agent misusing this could trigger unintended operations at scale.

From the tool's definition Tool name 'execute_job' and description 'Execute a registered job by name. Supports inline (synchronous) and background execution' indicate the tool runs external operations (jobs) whose effects are determined by the job definition and arguments.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs execute_job safely

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

execute_job Rate-limited

execute_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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "execute_job": {
      "limits": [
        {
          "counter": "execute_job_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 Frontmcp, apply this rule, and every execute_job call is checked against it from then on.

FAQ

Questions about execute_job

What does the execute_job tool do? +

Execute a registered job by name. Supports inline (synchronous) and background execution. It is categorised as a Execute tool in the Frontmcp MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on execute_job? +

Register the Front MCP server in PolicyLayer and add a rule for execute_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 Frontmcp. Nothing to install.

What risk level is execute_job? +

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

Can I rate-limit execute_job? +

Yes. Add a rate_limit block to the execute_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 execute_job completely? +

Set action: deny in the PolicyLayer policy for execute_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 execute_job? +

execute_job is provided by the Front MCP server (agentfront/frontmcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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