Update an existing order via PUT /admin/orders/{id}.json. Supports: tags, note,
AI agents use update_order to create or update resources in Sapo — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Sapo environment.
This tool modifies order data (tags, notes) reversibly without deleting or executing arbitrary code. It is a Write operation. Severity is medium because unauthorized order modifications could affect order accuracy, customer fulfillment, and business operations, but the changes are not irreversible and do not involve financial transactions or destructive deletion.
From the tool's definition Tool description states 'Update an existing order via PUT /admin/orders/{id}.json. Supports: tags, note' — the PUT method and 'update' operation indicate modification of existing data.
Risk signalsAdmin/system-level operation
Documented attack patterns abuse exactly the kind of access update_order gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Sapo, and nothing reaches the server without passing your rules. This is the rule we recommend for update_order:
{
"version": "1",
"default": "deny",
"tools": {
"update_order": {
"limits": [
{
"counter": "update_order_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}update_order 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 order via PUT /admin/orders/{id}.json. Supports: tags, note,. It is categorised as a Write tool in the Sapo MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Sapo MCP server in PolicyLayer and add a rule for update_order: 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 Sapo. Nothing to install.
update_order 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_order 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_order. 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_order is provided by the Sapo MCP server (nguyennguyenit/sapo-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Sapo, 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.
93 Sapo tools catalogued and risk-classified — across an index of 43,000+ MCP servers.