AI agents use set_status to create or update resources in Kanban — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Kanban environment.
The tool modifies the status of kanban items, which changes item state reversibly. This is a Write operation (modifies data) rather than Destructive (since status changes are typically undoable via state transitions). Severity is medium because changing item status could affect workflow visibility and task prioritization, but the operation is reversible.
From the tool's definition Tool name 'set_status' on a kanban board system; sibling tools include 'advance_status', 'close_item', and status workflow operations typical of kanban systems. Description is empty but context strongly indicates state modification.
Documented attack patterns abuse exactly the kind of access set_status gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Kanban, and nothing reaches the server without passing your rules. This is the rule we recommend for set_status:
{
"version": "1",
"default": "deny",
"tools": {
"set_status": {
"limits": [
{
"counter": "set_status_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}set_status 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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set_status. It is categorised as a Write tool in the Kanban MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Kanban MCP server in PolicyLayer and add a rule for set_status: 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 Kanban. Nothing to install.
set_status 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 set_status 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 set_status. 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.
set_status is provided by the Kanban MCP server (multidimensionalcats/kanban-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Kanban, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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45 Kanban tools catalogued and risk-classified — across an index of 43,000+ MCP servers.