AI agents invoke input_text to trigger actions in Android Debug Bridge MCP. 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 executes an external operation (ADB text injection) on an Android device. It simulates user input, which can interact with any active field including login forms, search boxes, or message composers. Misuse could lead to unintended data entry, credential submission, or triggering of automated workflows — making it Execute with medium severity.
From the tool's definition "Input text into the current field" — triggers an ADB input action that sends keystrokes/text to the active UI element on a connected Android device
Documented attack patterns abuse exactly the kind of access input_text gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Android Debug Bridge MCP, and nothing reaches the server without passing your rules. This is the rule we recommend for input_text:
{
"version": "1",
"default": "deny",
"tools": {
"input_text": {
"limits": [
{
"counter": "input_text_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}input_text 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.
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Input text into the current field. It is categorised as a Execute tool in the Android Debug Bridge MCP MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Android Debug Bridge MCP server in PolicyLayer and add a rule for input_text: 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 Android Debug Bridge MCP. Nothing to install.
input_text 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 input_text 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 input_text. 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.
input_text is provided by the Android Debug Bridge MCP server (tiagodanin/android-debug-bridge-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Android Debug Bridge MCP, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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9 Android Debug Bridge MCP tools catalogued and risk-classified — across an index of 43,000+ MCP servers.