AI agents use send_email to create or update resources in Google Toolbox — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Google Toolbox environment.
Sending an email creates new data in the email system and can be reversed (deleted/retracted in many systems), making this a Write operation rather than Execute. The severity is medium because misuse could result in spam, phishing, or unintended communications, but the action itself is not destructive or financial. The confidence is high given the clear naming and straightforward function.
From the tool's definition Tool name 'send_email' with description 'Send a new email' indicates creation of new email messages, which modifies data (the email system) reversibly.
Documented attack patterns abuse exactly the kind of access send_email gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Google Toolbox, and nothing reaches the server without passing your rules. This is the rule we recommend for send_email:
{
"version": "1",
"default": "deny",
"tools": {
"send_email": {
"limits": [
{
"counter": "send_email_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}send_email 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.
Free to start. No card required.
Send a new email. It is categorised as a Write tool in the Google Toolbox MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Google Toolbox MCP server in PolicyLayer and add a rule for send_email: 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 Google Toolbox. Nothing to install.
send_email 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 send_email 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 send_email. 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.
send_email is provided by the Google Toolbox MCP server (jikime/py-mcp-google-toolbox). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Google Toolbox, 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.
11 Google Toolbox tools catalogued and risk-classified — across an index of 43,000+ MCP servers.