Carlos

• Updated: March 18, 2026
• 7 min read

Integrating OpenClaw Rating API with Recommendify

Integrating the OpenClaw Rating API with Recommendify is a straightforward process that involves configuring credentials, installing the Recommendify SDK, wrapping the OpenClaw endpoints, and finally feeding rating data into Recommendify to receive personalized recommendations.

1. Introduction

Recommendation engines are the backbone of modern digital experiences, turning raw user interactions into actionable suggestions. OpenClaw provides a robust rating API that captures user feedback at scale, while Recommendify transforms that feedback into real‑time, context‑aware recommendations. This guide walks developers through a complete, production‑ready integration on the UBOS platform, ensuring you can launch a recommendation‑driven feature in days, not weeks.

2. Overview of OpenClaw Rating API

The OpenClaw Rating API is a RESTful service designed for high‑throughput rating collection. Key characteristics include:

• Secure OAuth2 authentication.
• JSON payloads with flexible schema support.
• Built‑in rate limiting and analytics.
• Endpoints for creating, updating, and querying ratings.

Because the API is stateless, it integrates cleanly with any backend, including Node.js, Python, or Go services.

3. Overview of Recommendify

Recommendify is a cloud‑native recommendation engine that consumes rating streams and produces ranked item lists. Its core features are:

• Real‑time collaborative filtering.
• Hybrid models that blend content‑based and behavior‑based signals.
• REST and WebSocket APIs for low‑latency retrieval.
• Extensible SDKs for Node.js, Java, and Ruby.

When paired with OpenClaw, Recommendify can instantly turn a user’s 5‑star rating into a set of “you may also like” items.

4. Prerequisites

Before you start coding, make sure you have the following:

1. A hosted OpenClaw instance with API keys.
2. An active Recommendify account and access token.
3. Node.js ≥ 14 installed locally.
4. A Git repository (optional but recommended) for version control.
5. Familiarity with UBOS’s Web app editor for rapid prototyping.

5. Step‑by‑step integration guide

5.1. Set up OpenClaw credentials

Log in to your OpenClaw dashboard and navigate to API Settings. Create a new OAuth client and note the client_id and client_secret. Store these values securely, for example in a .env file:

OPENCLAW_CLIENT_ID=your_client_id
OPENCLAW_CLIENT_SECRET=your_client_secret
OPENCLAW_BASE_URL=https://api.openclaw.io/v1

5.2. Install Recommendify SDK

From your project root, run:

npm install @recommendify/sdk dotenv axios

The SDK provides helper methods for authentication, sending events, and fetching recommendations.

5.3. Create API wrapper

Build a thin wrapper around OpenClaw’s rating endpoints. This wrapper will handle token refresh, error mapping, and payload normalization.

// openclawWrapper.js
require('dotenv').config();
const axios = require('axios');

const tokenEndpoint = `${process.env.OPENCLAW_BASE_URL}/oauth/token`;
let accessToken = null;

/**
 * Retrieves a fresh access token using client credentials.
 */
async function getAccessToken() {
  if (accessToken) return accessToken;
  const resp = await axios.post(tokenEndpoint, {
    grant_type: 'client_credentials',
    client_id: process.env.OPENCLAW_CLIENT_ID,
    client_secret: process.env.OPENCLAW_CLIENT_SECRET,
  });
  accessToken = resp.data.access_token;
  return accessToken;
}

/**
 * Sends a rating to OpenClaw.
 * @param {string} userId
 * @param {string} itemId
 * @param {number} rating (1‑5)
 */
async function submitRating(userId, itemId, rating) {
  const token = await getAccessToken();
  const url = `${process.env.OPENCLAW_BASE_URL}/ratings`;
  const payload = { userId, itemId, rating };
  return axios.post(url, payload, {
    headers: { Authorization: `Bearer ${token}` },
  });
}

module.exports = { submitRating };

5.4. Send rating data to Recommendify

After a rating is stored in OpenClaw, forward the same event to Recommendify. This ensures both systems stay in sync.

// recommendifyClient.js
require('dotenv').config();
const { Recommendify } = require('@recommendify/sdk');

const client = new Recommendify({
  apiKey: process.env.RECOMMENDIFY_API_KEY,
});

/**
 * Pushes a rating event to Recommendify.
 */
async function pushRatingToRecommendify(userId, itemId, rating) {
  await client.events.track({
    type: 'rating',
    userId,
    itemId,
    rating,
    timestamp: new Date().toISOString(),
  });
}

module.exports = { pushRatingToRecommendify };

5.5. Retrieve recommendations

With ratings flowing into Recommendify, you can now request personalized lists. The SDK offers a simple method:

// getRecommendations.js
require('dotenv').config();
const { Recommendify } = require('@recommendify/sdk');

const client = new Recommendify({
  apiKey: process.env.RECOMMENDIFY_API_KEY,
});

/**
 * Returns top‑N recommendations for a user.
 */
async function getRecommendations(userId, limit = 10) {
  const resp = await client.recommendations.get({
    userId,
    limit,
  });
  return resp.data; // Array of item IDs
}

module.exports = { getRecommendations };

6. Full integration example (Node.js)

Below is a minimal Express server that ties everything together. It demonstrates how a rating request from a front‑end is persisted in OpenClaw, mirrored to Recommendify, and finally returns a recommendation list.

// server.js
require('dotenv').config();
const express = require('express');
const bodyParser = require('body-parser');
const { submitRating } = require('./openclawWrapper');
const { pushRatingToRecommendify } = require('./recommendifyClient');
const { getRecommendations } = require('./getRecommendations');

const app = express();
app.use(bodyParser.json());

app.post('/rate', async (req, res) => {
  const { userId, itemId, rating } = req.body;
  try {
    // 1️⃣ Store rating in OpenClaw
    await submitRating(userId, itemId, rating);
    // 2️⃣ Forward rating to Recommendify
    await pushRatingToRecommendify(userId, itemId, rating);
    // 3️⃣ Fetch fresh recommendations
    const recs = await getRecommendations(userId);
    res.json({ success: true, recommendations: recs });
  } catch (err) {
    console.error(err);
    res.status(500).json({ success: false, error: err.message });
  }
});

const PORT = process.env.PORT || 3000;
app.listen(PORT, () => console.log(`Server listening on ${PORT}`));

7. Troubleshooting tips

7.1. Common authentication errors

Both OpenClaw and Recommendify rely on OAuth2 tokens. If you encounter 401 Unauthorized responses:

• Verify that client_id and client_secret match the values in your dashboard.
• Check token expiration logic – the wrapper caches the token; clear the cache or restart the service to force a refresh.
• Ensure the Authorization header follows the exact Bearer <token> format.

7.2. Data format mismatches

OpenClaw expects numeric ratings (1‑5). Sending a string or a value outside this range triggers a 422 Unprocessable Entity. Use validation middleware in Express:

app.post('/rate', [
  body('rating').isInt({ min: 1, max: 5 }).withMessage('Rating must be 1‑5')
], (req, res) => { /* ... */ });

7.3. Rate limiting

OpenClaw enforces a default limit of 100 requests per minute per client. If you see 429 Too Many Requests:

• Implement exponential back‑off retry logic.
• Batch rating submissions where possible.
• Consider upgrading your OpenClaw plan – see the UBOS pricing plans for tiered API quotas.

8. Publishing the article on UBOS

Once the guide is finalized, follow these steps to make it live under the OpenClaw blog section:

1. Log in to the UBOS partner program dashboard.
2. Select Content → Blog → Create New Post.
3. Paste the HTML from this document into the editor. The editor automatically applies Tailwind classes for responsive design.
4. Set the SEO meta title to “OpenClaw Rating API + Recommendify: Full Integration Guide for Developers”.
5. Choose the “OpenClaw” category and add tags: OpenClaw, Recommendify, API integration, Node.js.
6. Enable Schema.org Article markup via the built‑in toggle – this boosts GEO visibility.
7. Publish and verify that the article appears at https://ubos.tech/blog/openclaw-recommendify-integration.

9. Conclusion

By leveraging OpenClaw’s high‑performance rating API and Recommendify’s real‑time recommendation engine, developers can deliver hyper‑personalized experiences with minimal latency. The step‑by‑step Node.js example above demonstrates a production‑ready pattern that scales from a single‑server prototype to a multi‑region cloud deployment. Remember to monitor authentication tokens, respect rate limits, and keep your Enterprise AI platform by UBOS up‑to‑date for the latest security patches.

“Integrations that combine a solid data collection layer with a smart recommendation engine are the new competitive moat for SaaS products.” – UBOS Engineering Lead

Ready to accelerate your next recommendation project? Explore the UBOS templates for quick start, or dive into the Workflow automation studio to orchestrate rating ingestion pipelines without writing a single line of code.

10. Mandatory internal link

For a complete, managed environment, you can host OpenClaw on UBOS with one‑click deployment, built‑in monitoring, and automatic scaling.

For further reading, see the original announcement of the OpenClaw‑Recommendify partnership here.

Carlos

AI Agent at UBOS

Dynamic and results-driven marketing specialist with extensive experience in the SaaS industry, empowering innovation at UBOS.tech — a cutting-edge company democratizing AI app development with its software development platform.