finish_login
Second step: confirms the browser consent finished, saves the tokens to an owner-only file and verifies the login with a read-only identity call, returning the account email and the granted scopes. After success every tool works immediately — no client restart. If the user granted only part of th...
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What finish_login does on Mcp Google Calendar
AI agents use finish_login to create or update resources in Mcp Google Calendar, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Mcp Google Calendar environment.
Why finish_login is rated Medium
An AI agent can call finish_login faster than any human can review: one bad instruction and it creates or modifies resources in Mcp Google Calendar by the hundred, each call as confident as the last.
Risk signalsBulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
The rule that runs finish_login safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Mcp Google Calendar, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For finish_login, this is the rule to start with:
finish_login stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Mcp Google Calendar, apply this rule, and every finish_login call is checked against it from then on.
Questions about finish_login
Second step: confirms the browser consent finished, saves the tokens to an owner-only file and verifies the login with a read-only identity call, returning the account email and the granted scopes. After success every tool works immediately — no client restart. If the user granted only part of the requested permissions, the login is still saved and missingScopes lists what will not work. Logging in under a different Google account replaces the previous login (its refresh token is revoked best-effort) and the response carries previousAccountEmail so the change never goes unnoticed. It is categorised as a Write tool in the Mcp Google Calendar MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Mcp Google Calendar MCP server in PolicyLayer and add a rule for finish_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 Mcp Google Calendar. Nothing to install.
finish_login is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the finish_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 finish_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.
finish_login is provided by the Mcp Google Calendar MCP server (@a1-x-tech/mcp-google-calendar). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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