Medium Risk

should_apply

GrantIQ should_apply: opinionated apply / don't-apply decision for a specific grant. Returns a verdict (yes / borderline / no), confidence (0-1), specific blockers, an effort estimate with confidence band, competition-risk label (or 'unknown' when funder data is absent), and the structured eviden...

Part of the GrantIQ server.

should_apply can modify GrantIQ data, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents use should_apply to create or modify resources in GrantIQ. 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 should_apply repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach GrantIQ.

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

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "should_apply": {
      "limits": [
        {
          "counter": "should_apply_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

See the full GrantIQ policy for all 6 tools.

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These attack patterns abuse exactly the kind of access should_apply gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so should_apply only ever does what you allow.

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Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the should_apply tool do? +

GrantIQ should_apply: opinionated apply / don't-apply decision for a specific grant. Returns a verdict (yes / borderline / no), confidence (0-1), specific blockers, an effort estimate with confidence band, competition-risk label (or 'unknown' when funder data is absent), and the structured evidence behind it. Requires the caller's profile to be set via a prior find_opportunities call or web sign-up.. It is categorised as a Write tool in the GrantIQ MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on should_apply? +

Register the GrantIQ MCP server in PolicyLayer and add a rule for should_apply: 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 GrantIQ. Nothing to install.

What risk level is should_apply? +

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

Can I rate-limit should_apply? +

Yes. Add a rate_limit block to the should_apply 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 should_apply completely? +

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

should_apply is provided by the GrantIQ MCP server (https://grantiq.co.uk/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every GrantIQ tool call.

Deterministic rules across all 6 GrantIQ tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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