android_tap
Tap on the Android device screen at specified coordinates. Coordinates are in device pixels.
This record as markdown: /tools/io-github-saloprj-dialogbrain/android-tap.md
What android_tap does on Dialogbrain
AI agents invoke android_tap to trigger actions in Dialogbrain. 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.
| Parameter | Type | Required | Description |
|---|---|---|---|
x | integer | Yes | X coordinate in device pixels |
y | integer | Yes | Y coordinate in device pixels |
channel_account_id | integer | — | Android device channel_account ID. Omit when the workspace has a single Android device; REQUIRED when it has more than one (e.g. WhatsApp + LINE), else the call |
Parameters from the server's own tool schema.
Why android_tap is rated High
This tool performs a physical UI interaction (screen tap) on an Android device at arbitrary coordinates. It triggers real device actions whose effects depend entirely on what is displayed at those coordinates — could open apps, confirm dialogs, send messages, make purchases, etc.
From the tool's definition Tap on the Android device screen at specified coordinates
Attacks that exploit this kind of access
The rule that runs android_tap safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Dialogbrain, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For android_tap, this is the rule to start with:
android_tap stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Dialogbrain, apply this rule, and every android_tap call is checked against it from then on.
Questions about android_tap
Tap on the Android device screen at specified coordinates. Coordinates are in device pixels. It is categorised as a Execute tool in the Dialogbrain MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
android_tap accepts 3 parameters: x, y, channel_account_id. Required: x, y. The full parameter table on this page comes from the server's own tool schema.
Register the Dialogbrain MCP server in PolicyLayer and add a rule for android_tap: 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 Dialogbrain. Nothing to install.
android_tap 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 android_tap 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 android_tap. 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.
android_tap is provided by the Dialogbrain MCP server (https://api.dialogbrain.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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