approve-job
Waits for human approval before reporting the change as applied
This record as markdown: /tools/frontmcp/approve-job.md
What approve-job does on Frontmcp
AI agents invoke approve-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.
Why approve-job is rated High
Triggers an approval gate that unblocks and applies a pending change operation.
From the tool's definition Waits for human approval before reporting the change as applied
Attacks that exploit this kind of access
The rule that runs approve-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 approve-job, this is the rule to start with:
approve-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.
The button opens the PolicyLayer dashboard: create your workspace, connect Frontmcp, apply this rule, and every approve-job call is checked against it from then on.
Questions about approve-job
Waits for human approval before reporting the change as applied. 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.
Register the Front MCP server in PolicyLayer and add a rule for approve-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.
approve-job 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 approve-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.
Set action: deny in the PolicyLayer policy for approve-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.
approve-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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