Medium Risk

subscribe_to_changes

Register a filter set that streams matching field-level changes to your endpoint. With deliveryUrl the server POSTs HMAC-signed JSON payloads (webhook mode). Without deliveryUrl the subscription runs in SSE mode (consume via GET /api/agent/v1/subscriptions/{id}/stream). $0.05 per registration. We...

Part of the TRIALPATH server.

subscribe_to_changes can modify TRIALPATH 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 subscribe_to_changes to create or modify resources in TRIALPATH. 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 subscribe_to_changes 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 TRIALPATH.

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

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

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These attack patterns abuse exactly the kind of access subscribe_to_changes 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 subscribe_to_changes 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 subscribe_to_changes tool do? +

Register a filter set that streams matching field-level changes to your endpoint. With deliveryUrl the server POSTs HMAC-signed JSON payloads (webhook mode). Without deliveryUrl the subscription runs in SSE mode (consume via GET /api/agent/v1/subscriptions/{id}/stream). $0.05 per registration. Webhook deliveries are billed at $0.005 each from your prepaid credit balance; SSE deliveries are not metered.. It is categorised as a Write tool in the TRIALPATH MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on subscribe_to_changes? +

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

What risk level is subscribe_to_changes? +

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

Can I rate-limit subscribe_to_changes? +

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

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

subscribe_to_changes is provided by the TRIALPATH MCP server (spencerdgarrett/TRIALPATH). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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