browser_tabs
Manage tabs within the same BrowserContext as page_id. action ∈ {list, switch, close, new}. For list, returns all open tab metadata; for new, returns the new tab's page_id.
This record as markdown: /tools/io-github-saloprj-dialogbrain/browser-tabs.md
What browser_tabs does on Dialogbrain
AI agents invoke browser_tabs to trigger actions in Dialogbrain. 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.
| Parameter | Type | Required | Description |
|---|---|---|---|
url | object | — | |
action | string | Yes | |
tab_id | object | — | |
page_id | string | Yes |
Parameters from the server's own tool schema.
Why browser_tabs is rated High
This tool controls browser tab lifecycle within a BrowserContext. While 'list' is a read operation, 'new', 'switch', and 'close' are active browser manipulation actions that trigger external operations (opening URLs, changing focus, terminating tabs). Since the tool spans categories and Execute is more severe than Read/Write, it is classified as Execute.
From the tool's definition 'action' ∈ {list, switch, close, new}' — the tool performs browser tab management operations including opening new tabs, switching between tabs, and closing tabs
Risk signalsAccepts URL/endpoint input (url)
Attacks that exploit this kind of access
The rule that runs browser_tabs safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Dialogbrain, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For browser_tabs, this is the rule to start with:
browser_tabs 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 Dialogbrain, apply this rule, and every browser_tabs call is checked against it from then on.
Questions about browser_tabs
Manage tabs within the same BrowserContext as page_id. action ∈ {list, switch, close, new}. For list, returns all open tab metadata; for new, returns the new tab's page_id. It is categorised as a Execute tool in the Dialogbrain MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
browser_tabs accepts 4 parameters: url, action, tab_id, page_id. Required: action, page_id. The full parameter table on this page comes from the server's own tool schema.
Register the Dialogbrain MCP server in PolicyLayer and add a rule for browser_tabs: 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 Dialogbrain. Nothing to install.
browser_tabs 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 browser_tabs 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 browser_tabs. 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.
browser_tabs is provided by the Dialogbrain MCP server (https://api.dialogbrain.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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