browser_login
A execute tool on the Looking Glass MCP server.
This record as markdown: /tools/io-github-sahib-sawhney-wh-looking-glass-mcp/browser-login.md
What browser_login does on Looking Glass
AI agents invoke browser_login to trigger actions in Looking Glass. 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 | string | Yes | Login page URL |
password | string | Yes | Password |
username | string | Yes | Username or email |
submitSelector | string | — | CSS selector for submit button (auto-detected if omitted) |
passwordSelector | string | — | CSS selector for password field (auto-detected if omitted) |
usernameSelector | string | — | CSS selector for username field (auto-detected if omitted) |
Parameters from the server's own tool schema.
Why browser_login is rated High
Based on the name, this tool likely automates a browser login sequence (filling credentials and submitting a form), which constitutes executing browser actions with potential security implications. However, the empty description significantly lowers confidence. Given the sibling tools suggest a browser automation context, Execute is the most appropriate category.
From the tool's definition Tool name 'browser_login' suggests performing a login action in a browser context; description is empty and uninformative.
Risk signalsAccepts URL/endpoint input (url) · Handles credentials or secrets (password)
Attacks that exploit this kind of access
The rule that runs browser_login safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Looking Glass, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For browser_login, this is the rule to start with:
browser_login 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 Looking Glass, apply this rule, and every browser_login call is checked against it from then on.
Questions about browser_login
browser_login is a execute tool on the Looking Glass MCP server. It is categorised as a Execute tool in the Looking Glass MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
browser_login accepts 6 parameters: url, password, username, submitSelector, passwordSelector, usernameSelector. Required: url, password, username. The full parameter table on this page comes from the server's own tool schema.
Register the Looking Glass MCP server in PolicyLayer and add a rule for browser_login: 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 Looking Glass. Nothing to install.
browser_login 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_login 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_login. 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_login is provided by the Looking Glass MCP server (looking-glass-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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