AI agents use update_plugins to create or update resources in Kintone MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Kintone MCP Server environment.
This tool updates plugin configurations for a Kintone app. Modifying plugin settings is a Write operation as it changes app configuration reversibly. However, severity is high because plugin settings can broadly affect app behavior, security posture, and data access patterns across the entire app and its users.
From the tool's definition update_plugins - 'kintoneアプリのプラグイン設定を更新します' (updates plugin settings for a kintone app)
Documented attack patterns abuse exactly the kind of access update_plugins gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Kintone MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for update_plugins:
{
"version": "1",
"default": "deny",
"tools": {
"update_plugins": {
"limits": [
{
"counter": "update_plugins_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}update_plugins 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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kintoneアプリのプラグイン設定を更新します. It is categorised as a Write tool in the Kintone MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Kintone MCP Server MCP server in PolicyLayer and add a rule for update_plugins: 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 Kintone MCP Server. Nothing to install.
update_plugins 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_plugins 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_plugins. 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_plugins is provided by the Kintone MCP Server MCP server (r3-yamauchi/kintone-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Kintone MCP Server, 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.
70 Kintone MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.