AI agents invoke send_ros2_action_goal to trigger actions in ROS 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.
The tool name 'send_ros2_action_goal' strongly implies sending action goals to ROS 2 action servers, which triggers external operations on physical or simulated robots (e.g., navigation, manipulation). This is an Execute-category operation as it initiates robot behaviors with real-world or simulation effects. Severity is high because misuse could cause physical damage, unsafe robot motion, or unintended actuation.
From the tool's definition Tool name: send_ros2_action_goal; server context: 'Enabling controlling robots in ROS environments'
Documented attack patterns abuse exactly the kind of access send_ros2_action_goal gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and ROS MCP, and nothing reaches the server without passing your rules. This is the rule we recommend for send_ros2_action_goal:
{
"version": "1",
"default": "deny",
"tools": {
"send_ros2_action_goal": {
"limits": [
{
"counter": "send_ros2_action_goal_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}send_ros2_action_goal 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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send_ros2_action_goal. It is categorised as a Execute tool in the ROS MCP MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the ROS MCP server in PolicyLayer and add a rule for send_ros2_action_goal: 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 ROS MCP. Nothing to install.
send_ros2_action_goal 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 send_ros2_action_goal 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 send_ros2_action_goal. 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.
send_ros2_action_goal is provided by the ROS MCP server (yutarop/ros-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 24 ROS MCP tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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24 ROS MCP tools catalogued and risk-classified — across an index of 42,500+ MCP servers.