AI agents use add_update 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.
Based on naming convention ('add_*' pattern matches sibling write operations like add_decision, add_tag, add_relationship) and context as a database-backed kanban system, this tool most likely creates or appends updates/comments to items. This is a reversible write operation. Severity is medium because unintended updates could clutter the board but are not destructive or executable.
From the tool's definition Tool name 'add_update' on a kanban board MCP server with sibling tools including edit_item, add_tag, and advance_status suggests creating or appending new data. The description is empty, limiting certainty.
Documented attack patterns abuse exactly the kind of access add_update 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 add_update:
{
"version": "1",
"default": "deny",
"tools": {
"add_update": {
"limits": [
{
"counter": "add_update_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}add_update 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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add_update. 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 add_update: 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.
add_update 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 add_update 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 add_update. 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.
add_update 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.