AI agents invoke deploy_app to trigger actions in Kintone MCP Server. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
This tool executes a deployment operation that applies configuration changes to a Kintone application. Deployments are executable actions with side effects on external systems—they modify live app state and behavior.
From the tool's definition deploy_app performs 'kintoneアプリの設定をデプロイします' (deploys Kintone app configuration), which triggers external system operations (deploying app settings to a production or staging Kintone instance).
Documented attack patterns abuse exactly the kind of access deploy_app 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 deploy_app:
{
"version": "1",
"default": "deny",
"tools": {
"deploy_app": {
"limits": [
{
"counter": "deploy_app_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}deploy_app stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
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kintoneアプリの設定をデプロイします. It is categorised as a Execute tool in the Kintone MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Kintone MCP Server MCP server in PolicyLayer and add a rule for deploy_app: 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.
deploy_app is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the deploy_app 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 deploy_app. 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.
deploy_app 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.