Send a message/instruction to Jules in an active task
AI agents use jules_send_message to create or update resources in Google Jules MCP — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Google Jules MCP environment.
This tool sends a message or instruction to an active task session. It creates/modifies the state of a task by injecting input, which is a Write operation. However, since it sends instructions to an AI agent (Jules) that could then execute code or perform other actions, the actual blast radius depends on what instructions are sent.
From the tool's definition Send a message/instruction to Jules in an active task
Documented attack patterns abuse exactly the kind of access jules_send_message gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Google Jules MCP, and nothing reaches the server without passing your rules. This is the rule we recommend for jules_send_message:
{
"version": "1",
"default": "deny",
"tools": {
"jules_send_message": {
"limits": [
{
"counter": "jules_send_message_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
} jules_send_message 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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Send a message/instruction to Jules in an active task. It is categorised as a Write tool in the Google Jules MCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Google Jules MCP server in PolicyLayer and add a rule for jules_send_message: 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 Jules MCP. Nothing to install.
jules_send_message 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 jules_send_message 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 jules_send_message. 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.
jules_send_message is provided by the Google Jules MCP server (samihalawa/google-jules-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Google Jules MCP, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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13 Google Jules MCP tools catalogued and risk-classified — across an index of 43,000+ MCP servers.