configure_display
Updates display settings: rename (name), lock or unlock content changes (locked), privacy mode for share links (privacy_mode), embed-origin allowlist (origins), hardware permissions (camera, microphone, geolocation), preferred language, mouse cursor, badge overlay and watermark position. Only the...
This record as markdown: /tools/de-agentview-agentview-mcp/configure-display.md
What configure_display does on agentView
AI agents use configure_display to create or update resources in agentView, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your agentView environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
name | string | — | New display name (rename). |
locked | boolean | — | true blocks content changes until unlocked; false unlocks. |
origins | array | — | Embed-origin allowlist for Public displays; [] allows all origins. |
whitelist | array | — | Domain whitelist for whitelist-only mode. |
display_id | string | Yes | 8-character display profile ID, e.g. 'ABCD1234'. |
access_token | string | — | Optional bearer token; prefer session_request_id. |
allow_camera | boolean | — | |
privacy_mode | string | — | Private caps share-link TTL at 1 hour; Public (signage mode) allows 24 hours. |
allow_microphone | boolean | — | |
strict_whitelist | boolean | — | true: the display whitelist replaces the org whitelist instead of extending it. |
allow_geolocation | boolean | — | |
connectivity_mode | string | — | Per-display network mode override. |
Parameters from the server's own tool schema.
Why configure_display is rated Medium
An AI agent can call configure_display faster than any human can review: one bad instruction and it creates or modifies resources in agentView by the hundred, each call as confident as the last.
Risk signalsHandles credentials or secrets (access_token) · High parameter count (17 properties) · Admin/system-level operation
Attacks that exploit this kind of access
The rule that runs configure_display safely
PolicyLayer is an MCP gateway: it sits between your AI agents and agentView, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For configure_display, this is the rule to start with:
configure_display 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.
The button opens the PolicyLayer dashboard: create your workspace, connect agentView, apply this rule, and every configure_display call is checked against it from then on.
Questions about configure_display
Updates display settings: rename (name), lock or unlock content changes (locked), privacy mode for share links (privacy_mode), embed-origin allowlist (origins), hardware permissions (camera, microphone, geolocation), preferred language, mouse cursor, badge overlay and watermark position. Only the fields you pass are changed; online displays apply changes immediately. Use for any display setting change. Not for sending content (send_html, send_url) or deleting (delete_display). Requires admin scope. It is categorised as a Write tool in the agentView MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
configure_display accepts 12 parameters: name, locked, origins, whitelist, display_id, access_token, allow_camera, privacy_mode, allow_microphone, strict_whitelist, allow_geolocation, connectivity_mode. Required: display_id. The full parameter table on this page comes from the server's own tool schema.
Register the agentView MCP server in PolicyLayer and add a rule for configure_display: 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 agentView. Nothing to install.
configure_display 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 configure_display 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 configure_display. 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.
configure_display is provided by the agentView MCP server (https://agentview.de/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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