AI agents invoke chotuBlinkEyes to trigger actions in Chotu Robo 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.
Based on the server context and sibling tools, chotuBlinkEyes likely triggers a physical hardware action (blinking LED eyes on a robot), which constitutes executing an external operation affecting real-world hardware. The description is empty, lowering confidence. Severity is medium as it controls physical actuators but appears limited in blast radius.
From the tool's definition Tool name 'chotuBlinkEyes' on a server that controls Arduino-based robotics hardware (LEDs, motors, servos, sensors); sibling tools include blinkLED, moveServo, controlFan indicating physical hardware actuation.
Documented attack patterns abuse exactly the kind of access chotuBlinkEyes gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Chotu Robo Server, and nothing reaches the server without passing your rules. This is the rule we recommend for chotuBlinkEyes:
{
"version": "1",
"default": "deny",
"tools": {
"chotuBlinkEyes": {
"limits": [
{
"counter": "chotublinkeyes_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}chotuBlinkEyes 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.
Free to start. No card required.
chotuBlinkEyes. It is categorised as a Execute tool in the Chotu Robo Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Chotu Robo Server MCP server in PolicyLayer and add a rule for chotuBlinkEyes: 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 Chotu Robo Server. Nothing to install.
chotuBlinkEyes 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 chotuBlinkEyes 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 chotuBlinkEyes. 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.
chotuBlinkEyes is provided by the Chotu Robo Server MCP server (vishalmysore/choturobo). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 15 Chotu Robo Server tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
15 Chotu Robo Server tools catalogued and risk-classified — across an index of 42,500+ MCP servers.