Manage macOS application deployment including app assignments, updates, and installation requirements.
AI agents use manage_intune_macos_apps to create or update resources in Microsoft 365 Core MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Microsoft 365 Core MCP Server environment.
This tool creates and modifies Intune macOS app deployment configurations, assignments, and requirements. It is primarily a Write operation (creating/updating deployment policies and assignments).
From the tool's definition Manage macOS application deployment including app assignments, updates, and installation requirements
Attacks that exploit this kind of access
Manage macOS application deployment including app assignments, updates, and installation requirements. It is categorised as a Write tool in the Microsoft 365 Core MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Microsoft 365 Core MCP Server MCP server in PolicyLayer and add a rule for manage_intune_macos_apps: 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 Microsoft 365 Core MCP Server. Nothing to install.
manage_intune_macos_apps 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 manage_intune_macos_apps 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 manage_intune_macos_apps. 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.
manage_intune_macos_apps is provided by the Microsoft 365 Core MCP Server MCP server (roycedamien/m365-core-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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