Enable or disable a specific scheduler on a Runtime Manager application. Scheduler names are visible in the runtime_list_deployments UI. Call runtime_list_deployments first to obtain the deploymentId and scheduler name.
AI agents invoke runtime_set_scheduler_state to trigger actions in Anypoint 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 modifies the execution state of a scheduler on a live runtime application — enabling or disabling scheduled jobs. This is an operational action that triggers or suppresses execution of potentially critical automated processes. It is not a simple data write (it affects runtime execution behavior), but it is also not inherently destructive/irreversible.
From the tool's definition Enable or disable a specific scheduler on a Runtime Manager application
Attacks that exploit this kind of access
Enable or disable a specific scheduler on a Runtime Manager application. Scheduler names are visible in the runtime_list_deployments UI. Call runtime_list_deployments first to obtain the deploymentId and scheduler name. It is categorised as a Execute tool in the Anypoint MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Anypoint MCP Server MCP server in PolicyLayer and add a rule for runtime_set_scheduler_state: 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 Anypoint MCP Server. Nothing to install.
runtime_set_scheduler_state 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 runtime_set_scheduler_state 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 runtime_set_scheduler_state. 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.
runtime_set_scheduler_state is provided by the Anypoint MCP Server MCP server (sravannerella/mulesoft-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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