AI agents invoke set_oplock_state to trigger actions in mcpXL30. 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 suggests setting an 'oplock' (operator lock) state on a Philips XL30 ESEM microscope. In electron microscopy systems, an operator lock controls access to microscope controls, potentially enabling or disabling operator override of safety systems.
From the tool's definition Tool name 'set_oplock_state' on a microscope control server; description is empty and uninformative.
Attacks that exploit this kind of access
set_oplock_state. It is categorised as a Execute tool in the mcpXL30 MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the mcpXL30 MCP server in PolicyLayer and add a rule for set_oplock_state: 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 mcpXL30. Nothing to install.
set_oplock_state 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 set_oplock_state 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 set_oplock_state. 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.
set_oplock_state is provided by the mcpXL30 MCP server (tspspi/mcpxl30). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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