This record as markdown: /tools/io-github-vmoranv-jshookmcp/tab-workflow.md
What tab_workflow does on Jshookmcp
AI agents invoke tab_workflow to trigger actions in Jshookmcp. 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 tab_workflow is rated High
Browser automation tool that coordinates across tabs, triggering external browser operations.
From the tool's definition Cross-tab coordination; browser automation server context
Attacks that exploit this kind of access
The rule that runs tab_workflow safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Jshookmcp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For tab_workflow, this is the rule to start with:
tab_workflow 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 Jshookmcp, apply this rule, and every tab_workflow call is checked against it from then on.
Questions about tab_workflow
Cross-tab coordination. It is categorised as a Execute tool in the Jshookmcp MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Jshook MCP server in PolicyLayer and add a rule for tab_workflow: 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 Jshookmcp. Nothing to install.
tab_workflow 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 tab_workflow 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 tab_workflow. 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.
tab_workflow is provided by the Jshook MCP server (@jshookmcp/jshook). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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