AI agents use update_payment to create or update resources in Mcp Ap2 — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Mcp Ap2 environment.
Updating a pending payment changes financial data but does not itself move money or commit an irreversible financial obligation — it modifies a payment record that is still in a pending state. However, depending on implementation, updating a pending payment (e.g., changing amount, recipient, or status) could have significant downstream financial consequences, warranting a high severity rating.
From the tool's definition 'Update a pending payment' — modifies an existing payment record; the word 'update' implies reversible modification rather than deletion or financial execution.
Documented attack patterns abuse exactly the kind of access update_payment gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Mcp Ap2, and nothing reaches the server without passing your rules. This is the rule we recommend for update_payment:
{
"version": "1",
"default": "deny",
"tools": {
"update_payment": {
"limits": [
{
"counter": "update_payment_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}update_payment stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
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Update a pending payment. It is categorised as a Write tool in the Mcp Ap2 MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Mcp Ap2 MCP server in PolicyLayer and add a rule for update_payment: 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 Mcp Ap2. Nothing to install.
update_payment is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the update_payment 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 update_payment. 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.
update_payment is provided by the Mcp Ap2 MCP server (@codespar/mcp-ap2). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Mcp Ap2, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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