Bolt.new AI and Framer integration: Step-by-Step Guide 2025

The short version is: there is no direct “Bolt → Framer” integration API. They are separate tools. But you can integrate them the same way you integrate any frontend (Framer) with any backend or AI service (your Bolt.new-generated backend). The pattern is: you build an API in Bolt.new, deploy it, and call that API from Framer using Framer’s built‑in code hooks (Data API, fetch, or custom components). Bolt is simply where you build and host the logic — Framer is where you design and call it.

 

What “Integrating Bolt.new with Framer” Actually Means

 

You build a backend or API endpoint inside Bolt.new — typically something like:

• An HTTP API route that handles requests (for example, to run AI logic, process a form, save data, etc.)
• Environment variables in Bolt.new to store API keys (OpenAI, Stripe, Airtable, etc.)
• A deployed server URL that Framer can call using fetch()

Then you call that backend from Framer using client-side fetch inside a Framer “Code Component” or Framer’s Data settings.

That’s the entire integration. Bolt.new acts as your backend, Framer acts as your frontend.

 

Step-by-Step: The Clean, Real Integration Pattern

 

This is the real workflow teams use today. Nothing magical, just standard API calls.

• Step A — Build an API in Bolt.new
  You create a server route such as /api/ai inside a Node/Express or Next.js scaffold. Bolt.new can auto‑generate the file structure. For example:

// routes/ai.js (Express example)
import express from "express";
import OpenAI from "openai";

const router = express.Router();
const client = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });

router.post("/", async (req, res) => {
  try {
    const { message } = req.body;

    const completion = await client.chat.completions.create({
      model: "gpt-4o-mini",
      messages: [{ role: "user", content: message }]
    });

    res.json({ reply: completion.choices[0].message.content });
  } catch (err) {
    res.status(500).json({ error: err.message });
  }
});

export default router;

• Step B — Deploy your Bolt.new project
  When you click Deploy, Bolt gives you a public endpoint like:
  https://your‑bolt‑app.vercel.app/api/ai
• Step C — Call this endpoint inside Framer
  You use a Framer Code Component or a hook. Here is a simple working fetch example inside a Framer component:

// Framer Code Component example
import { useState } from "react";

export default function ChatToBolt() {
  const [reply, setReply] = useState("");

  async function sendMessage() {
    const res = await fetch("https://your-bolt-app.vercel.app/api/ai", {
      method: "POST",
      headers: { "Content-Type": "application/json" },
      body: JSON.stringify({ message: "Hello from Framer!" })
    });

    const data = await res.json();
    setReply(data.reply);
  }

  return (
    <div>
      <button onClick={sendMessage}>Send to Bolt API</button>
      <p>{reply}</p>
    </div>
  );
}

• Framer runs this client-side.
• The request goes to your Bolt.new backend.
• Bolt returns AI-generated text (or any other data).

This is the proper integration pattern.

 

Important Notes When Integrating

 

• Framer must never expose your secret keys. All secrets stay in Bolt.new environment variables — Framer only calls the backend endpoint.
• Use POST, not GET when sending user data from Framer to Bolt.
• Use CORS middleware in Bolt.new if your Framer site needs it (only if API and frontend are from different domains):

import cors from "cors";
app.use(cors());

• Deploy Bolt.new backend to Vercel or Node host so Framer can reach it publicly.

 

What You CAN Build With This Integration

 

• A Framer site with an AI chatbot powered by a Bolt.new backend
• A Framer form that sends data to Bolt.new → then to Airtable, Notion, Supabase, etc.
• A Framer UI that triggers workflows or data processing handled in Bolt

Everything works via normal HTTP requests — there is no proprietary bridge or special SDK.

 

The Direct Answer, Restated Clearly

 

You integrate Bolt.new with Framer by deploying a backend/API from Bolt and calling it from Framer using fetch() inside a code component. Bolt handles server‑side logic (AI, databases, third‑party APIs), while Framer is the frontend that invokes it. There is no native integration, but the API-based pattern works cleanly and is how real teams do it.