Install the Scalekit Auth Stack plugin into your coding agent and paste one prompt. The agent scaffolds OAuth handling, token management, and connected account logic so you can start writing agent logic immediately.
As AI agents raise the velocity of code changes, the volume of open PRs on any team keeps growing. This recipe builds a Render Workflow that finds the five most-discussed open PRs in a repository, reads their diffs and comment threads, and generates a plain-language paragraph per PR — written for a team lead or manager. Each team member runs the same workflow with their own user ID; Scalekit’s token vault handles per-user GitHub OAuth so the agent acts as the right person every time.
Connecting an agent to two external APIs means handling two separate OAuth tokens, two authorization flows, and two different error surfaces. This recipe shows how Scalekit manages the OAuth lifecycle for both connectors, then demonstrates two patterns for calling those APIs: fetching a token and calling the REST API directly, versus letting Scalekit execute the call through a built-in action.
Switching to a browser to look up Scalekit docs breaks your coding flow. This cookbook shows you how to configure the ref.tools MCP server so your AI coding assistant can search Scalekit documentation inline — in Cursor, Claude Code, Windsurf, or any MCP-compatible client.
Building a scheduling agent means coordinating authentication to two separate tools — Google Calendar and Gmail — then chaining their outputs in one workflow. Without managed OAuth, each connector requires its own token lifecycle and error-handling logic. This recipe shows how Scalekit handles auth per connector so your agent can focus on finding a free slot, creating the event, and drafting the confirmation.
