Medium Risk

update_job_hunt

Update job hunt settings and search filters. Use this to change what jobs are matched. IMPORTANT: When updating config, you must pass the ENTIRE config object as it replaces the existing config (not a partial merge). Use get_job_hunt first to see current config, then include all fields you want t...

High parameter count (26 properties); Bulk/mass operation — affects multiple targets

Part of the JobGPT AutoApply MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.

xfigr-com/jobgpt Write Risk 3/5

AI agents use update_job_hunt to create or modify resources in JobGPT AutoApply. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.

Without a policy, an AI agent could call update_job_hunt repeatedly, creating or modifying resources faster than any human could review. Intercept's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach JobGPT AutoApply.

Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.

xfigr-com-jobgpt.yaml
tools:
  update_job_hunt:
    rules:
      - action: allow
        rate_limit:
          max: 30
          window: 60

See the full JobGPT AutoApply policy for all 35 tools.

Tool Name update_job_hunt
Category Write
Risk Level Medium

View all 35 tools →

Agents calling write-class tools like update_job_hunt have been implicated in these attack patterns. Read the full case and prevention policy for each:

Browse the full MCP Attack Database →

Other tools in the Write risk category across the catalogue. The same policy patterns (rate-limit, validate) apply to each.

What does the update_job_hunt tool do? +

Update job hunt settings and search filters. Use this to change what jobs are matched. IMPORTANT: When updating config, you must pass the ENTIRE config object as it replaces the existing config (not a partial merge). Use get_job_hunt first to see current config, then include all fields you want to keep.. It is categorised as a Write tool in the JobGPT AutoApply MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on update_job_hunt? +

Add a rule in your Intercept YAML policy under the tools section for update_job_hunt. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the JobGPT AutoApply MCP server.

What risk level is update_job_hunt? +

update_job_hunt is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit update_job_hunt? +

Yes. Add a rate_limit block to the update_job_hunt rule in your Intercept 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 update_job_hunt completely? +

Set action: deny in the Intercept policy for update_job_hunt. 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 update_job_hunt? +

update_job_hunt is provided by the JobGPT AutoApply MCP server (xfigr-com/jobgpt). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policies on JobGPT AutoApply

Open source. One binary. Zero dependencies.

npx -y @policylayer/intercept
github.com/policylayer/intercept →
// GET IN TOUCH

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