AI agents call list_schedules to retrieve information from Jules MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and enumerates scheduled tasks without modifying, deleting, or executing anything. It is a read-only operation that simply returns information about existing schedules. The low severity reflects minimal risk: exposure of scheduling metadata alone cannot cause harm unless combined with other tools to modify or delete schedules.
From the tool's definition Tool name is 'list_schedules' and description states 'List all locally-managed scheduled tasks' — a pure query operation with no side effects.
Documented attack patterns abuse exactly the kind of access list_schedules gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Jules MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for list_schedules:
{
"version": "1",
"default": "deny",
"tools": {
"list_schedules": {}
}
} list_schedules is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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List all locally-managed scheduled tasks. It is categorised as a Read tool in the Jules MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Jules MCP Server MCP server in PolicyLayer and add a rule for list_schedules: 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 Jules MCP Server. Nothing to install.
list_schedules is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the list_schedules 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 list_schedules. 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.
list_schedules is provided by the Jules MCP Server MCP server (savethepolarbears/jules-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Jules MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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11 Jules MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.