Update an existing product by ID
AI agents use update_product to create or update resources in Paystack — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Paystack environment.
This tool modifies an existing product's data, which is a reversible write operation. Misuse could lead to incorrect product information (wrong prices, descriptions) affecting customers, but changes can be corrected, making it medium severity.
From the tool's definition Update an existing product by ID
Documented attack patterns abuse exactly the kind of access update_product gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Paystack, and nothing reaches the server without passing your rules. This is the rule we recommend for update_product:
{
"version": "1",
"default": "deny",
"tools": {
"update_product": {
"limits": [
{
"counter": "update_product_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}update_product 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 an existing product by ID. It is categorised as a Write tool in the Paystack MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Paystack MCP server in PolicyLayer and add a rule for update_product: 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 Paystack. Nothing to install.
update_product 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_product 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_product. 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_product is provided by the Paystack MCP server (kohasummons/paystack-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Paystack, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
28 Paystack tools catalogued and risk-classified — across an index of 43,000+ MCP servers.