execute_batch
Execute multiple commands in parallel. Use for
This record as markdown: /tools/deswong-openhab-mcp/execute-batch.md
What execute_batch does on Openhab
AI agents invoke execute_batch to trigger actions in Openhab. 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.
Why execute_batch is rated High
This tool allows execution of arbitrary commands in parallel without apparent constraints. In a home automation context, executing multiple commands simultaneously could trigger unintended device actions (e.g., unlocking doors, turning off critical systems, disabling security). The ability to execute batches amplifies the risk compared to single-command execution.
From the tool's definition Tool named 'execute_batch' with description stating 'Execute multiple commands in parallel.' The verb 'execute' combined with 'commands' and the context of an OpenHAB automation/control system indicates arbitrary command execution.
Attacks that exploit this kind of access
The rule that runs execute_batch safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Openhab, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For execute_batch, this is the rule to start with:
execute_batch 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 Openhab, apply this rule, and every execute_batch call is checked against it from then on.
Questions about execute_batch
Execute multiple commands in parallel. Use for. It is categorised as a Execute tool in the Openhab MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Openhab MCP server in PolicyLayer and add a rule for execute_batch: 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 Openhab. Nothing to install.
execute_batch 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 execute_batch 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 execute_batch. 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.
execute_batch is provided by the Openhab MCP server (deswong/openhab-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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