Low Risk

request_callback

Push a user's contact info to a business so they can call/email/text back. Use this when a question can't be answered without human contact (custom quote, after-hours scheduling, complaint, complex combo). Idempotent on idempotency_key within a 24h window — agent retries don't spam the business. ...

Risk signalsHigh parameter count (10 properties)

Part of the AdvocateMCP server.

request_callback is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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AI agents call request_callback to retrieve information from AdvocateMCP without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though request_callback only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "request_callback": {}
  }
}

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Get this rule live on your own AdvocateMCP server in minutes. PolicyLayer enforces it on every call, before it runs.

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

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

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the request_callback tool do? +

Push a user's contact info to a business so they can call/email/text back. Use this when a question can't be answered without human contact (custom quote, after-hours scheduling, complaint, complex combo). Idempotent on idempotency_key within a 24h window — agent retries don't spam the business. Returns delivery status the agent can quote to the user.. It is categorised as a Read tool in the AdvocateMCP MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on request_callback? +

Register the Advocate MCP server in PolicyLayer and add a rule for request_callback: 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 AdvocateMCP. Nothing to install.

What risk level is request_callback? +

request_callback is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit request_callback? +

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

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

request_callback is provided by the Advocate MCP server (https://api.advocatemcp.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every AdvocateMCP tool call.

Deterministic rules across all 10 AdvocateMCP tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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