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Working with AI

Give your AI coding assistant direct access to Wristband's documentation and APIs.

📘

Source Repository

All setup scripts and source files referenced on this page live in the wristband-dev/vibe-coding repository on GitHub.

Wristband offers three ways to bring AI into your development workflow:

ToolWhat It DoesWhere It Works
MCP ServerDirect API access, documentation search, and code generation through the Model Context ProtocolCursor, Windsurf, Claude Desktop, and other MCP-capable clients
Cursor SkillsPre-built patterns for common Wristband integration tasks, installed alongside MCP in a single stepCursor
llms.txtWristband's full documentation formatted as a single URL for AI consumptionChatGPT, Claude Web, and other chat-based tools

What You Can Do

Depending on how you set up your AI-assisted coding environment, you should be able to ask your AI topics like the following:

Integrate Wristband auth into your app

  • "Add Wristband authentication to my Next.js app"
  • "Set up login and logout in my FastAPI backend"
  • "Protect my API routes with Wristband session middleware"

Work with the Wristband API

  • "Create a new tenant via the Wristband API"
  • "Query all active users in a tenant via the Wristband API"
  • "Update a user's profile fields via the Wristband API"

Understand the auth flows

  • "How does the Password Reset flow work with self-hosted UI?"
  • "How does the Tenant Discovery flow work for Wristband-hosted UI?"
  • "How does user activation work for new signups?"

Which One To Choose

  • MCP Server: This gives your AI direct, queryable access to Wristband's API and docs. It's the right call in Claude Desktop, Windsurf, or any other MCP-capable client, letting your AI query docs and API interactively, asking follow-up questions and pulling exactly what it needs.
  • Cursor Skills: Applies pre-built patterns for common Wristband integration tasks directly in Cursor. Pair it with the MCP Server for the most complete setup, adding live lookup alongside the guided implementation, installed together in one step.
  • llms.txt: is the fastest way to get accurate Wristband context into a chat tool, requiring just a URL and no setup. It's a reference file your AI reads from, rather than an interactive connection it can query.