Integrating OpenClaw Rating API with Moltbook: A Complete Guide

You can fetch, display, and submit plugin ratings in Moltbook by calling the OpenClaw Rating API’s GET and POST endpoints and wiring the JSON responses into Moltbook’s UI components.

Introduction

Moltbook has quickly become the go‑to AI‑agent platform for developers who want to expose autonomous plugins to a social‑style marketplace. One of the most common needs is to surface community‑driven UBOS homepage plugin ratings and allow users to contribute their own scores. The OpenClaw Rating API provides a lightweight, REST‑ful interface for exactly that purpose.

The timing couldn’t be better. Recent coverage of Moltbook’s rapid adoption (Substack analysis) shows a surge in AI‑agent platform interest, making a solid rating integration a competitive advantage for any plugin developer.

Prerequisites

• Node.js ≥ 14.x and npm ≥ 6.x installed locally.
• An OpenClaw API key – obtain it from your UBOS partner program dashboard.
• Access to a Moltbook development sandbox (you can spin one up via the UBOS platform overview).
• Basic familiarity with Moltbook’s Web app editor on UBOS and its component model.

For a quick start, you may also want to review the UBOS pricing plans to ensure your sandbox has enough request quota for testing.

Fetching Plugin Ratings

API endpoint details

The OpenClaw Rating API exposes a /ratings/:pluginId endpoint that returns a JSON payload with the average score, total votes, and an array of recent reviews.

// Example GET request using fetch
const PLUGIN_ID = 'my-awesome-plugin';
const API_KEY = process.env.OPENCLAW_API_KEY;

fetch(`https://api.openclaw.io/ratings/${PLUGIN_ID}`, {
  method: 'GET',
  headers: {
    'Authorization': `Bearer ${API_KEY}`,
    'Content-Type': 'application/json'
  }
})
  .then(res => res.json())
  .then(data => console.log('Rating data:', data))
  .catch(err => console.error('Error fetching rating:', err));

Parsing and handling the response

The response shape is predictable:

{
  "pluginId": "my-awesome-plugin",
  "averageScore": 4.3,
  "totalVotes": 128,
  "recentReviews": [
    {"user":"alice","score":5,"comment":"Excellent!"},
    {"user":"bob","score":4,"comment":"Very useful."}
  ]
}

In Moltbook you typically store this object in a local state hook (e.g., useState) and trigger a re‑render when the data arrives.

Displaying Ratings in Moltbook

UI component integration

Moltbook’s UI library is built on Tailwind CSS, so you can create a reusable RatingCard component that consumes the JSON payload.

// RatingCard.jsx
import React from 'react';

export default function RatingCard({rating}) {
  return (
    <div className="border rounded-lg p-4 shadow-sm bg-white">
      <h3 className="text-lg font-medium mb-2">{rating.pluginId}</h3>
      <div className="flex items-center mb-2">
        <span className="text-2xl font-bold mr-2">{rating.averageScore.toFixed(1)}</span>
        <span className="text-sm text-gray-600">/5 ({rating.totalVotes} votes)</span>
      </div>
      <ul className="list-disc list-inside text-sm text-gray-700">
        {rating.recentReviews.map((rev,i) => (
          <li key={i}>
            <strong>{rev.user}</strong>: {rev.comment} ({rev.score}★)
          </li>
        ))}
      </ul>
    </div>
  );
}

Drop <RatingCard rating={ratingData} /> into any Moltbook page. The component automatically adapts to dark mode because it uses Tailwind’s utility classes.

Formatting rating data for display

For a polished look, you may want to convert the numeric score into a star graphic. The UBOS templates for quick start include a “star rating” snippet you can copy‑paste.

Submitting New Ratings

POST endpoint

To let users contribute, send a POST request to /ratings/:pluginId with a JSON body containing score (1‑5) and an optional comment.

// Example POST request
async function submitRating(pluginId, score, comment) {
  const payload = { score, comment };
  const response = await fetch(`https://api.openclaw.io/ratings/${pluginId}`, {
    method: 'POST',
    headers: {
      'Authorization': `Bearer ${process.env.OPENCLAW_API_KEY}`,
      'Content-Type': 'application/json'
    },
    body: JSON.stringify(payload)
  });

  if (!response.ok) {
    const err = await response.json();
    throw new Error(`Failed: ${err.message}`);
  }
  return await response.json(); // returns updated rating object
}

Error handling and validation

The API validates the score range and sanitizes the comment. A typical error response looks like:

{
  "error": "InvalidScore",
  "message": "Score must be an integer between 1 and 5."
}

In the UI, surface these messages using a toast component from the Workflow automation studio so users get immediate feedback.

Full End‑to‑End Example

Below is a minimal Moltbook page that fetches the current rating, displays it, and lets a logged‑in user submit a new score. The example stitches together everything we covered.

// RatingPage.jsx
import React, {useEffect, useState} from 'react';
import RatingCard from './RatingCard';
import {toast} from '@ubos/workflow'; // hypothetical toast lib

export default function RatingPage({pluginId}) {
  const [rating, setRating] = useState(null);
  const [newScore, setNewScore] = useState(5);
  const [comment, setComment] = useState('');

  // Fetch rating on mount
  useEffect(() => {
    fetch(`https://api.openclaw.io/ratings/${pluginId}`, {
      headers: { 'Authorization': `Bearer ${process.env.OPENCLAW_API_KEY}` }
    })
      .then(r => r.json())
      .then(setRating)
      .catch(err => toast.error('Unable to load rating'));
  }, [pluginId]);

  const handleSubmit = async e => {
    e.preventDefault();
    try {
      const updated = await submitRating(pluginId, newScore, comment);
      setRating(updated);
      toast.success('Thanks for your rating!');
      setComment('');
    } catch (err) {
      toast.error(err.message);
    }
  };

  return (
    <div className="space-y-6">
      {rating ? <RatingCard rating={rating} /> : <p>Loading…</p>}

      <form onSubmit={handleSubmit} className="max-w-md space-y-4">
        <label className="block">
          Score
          <select
            value={newScore}
            onChange={e => setNewScore(Number(e.target.value))}
            className="mt-1 block w-full border rounded">
            {[1,2,3,4,5].map(v => (
              <option key={v} value={v}>{v}</option>
            ))}
          </select>
        </label>

        <label className="block">
          Comment (optional)
          <textarea
            value={comment}
            onChange={e => setComment(e.target.value)}
            className="mt-1 block w-full border rounded">
          </textarea>
        </label>

        <button type="submit" className="px-4 py-2 bg-blue-600 text-white rounded">
          Submit Rating
        </button>
      </form>
    </div>
  );
}

Deploy this page via the Web app editor on UBOS, and you’ll have a fully functional rating widget inside Moltbook in minutes.

SEO, Keywords, and Internal Linking Strategy

Throughout this guide we naturally referenced several UBOS resources. Adding contextual internal links not only helps readers discover related tools, it also signals relevance to search engines. Below are the key keywords we targeted:

• OpenClaw Rating API
• Moltbook
• plugin ratings
• developer guide
• integration tutorial

For a concise meta description, consider: “Learn how to fetch, display, and submit plugin ratings in Moltbook using the OpenClaw Rating API. Step‑by‑step Node.js guide with code snippets, UI integration, and best‑practice tips.”

Related UBOS capabilities you might explore

• AI marketing agents – automate promotional copy for your plugin.
• Enterprise AI platform by UBOS – scale rating analytics across thousands of agents.
• UBOS solutions for SMBs – cost‑effective hosting for small‑team plugins.
• UBOS for startups – fast‑track your MVP with pre‑built integrations.

Conclusion

Integrating the OpenClaw Rating API into Moltbook is a straightforward process that delivers immediate value: users see trustworthy community scores, and developers gain actionable feedback loops. By following the steps above—setting up credentials, fetching data, rendering a Tailwind‑styled card, and handling POST submissions—you’ll have a production‑ready rating system in place.

Ready to take the next step? Join the UBOS partner program, spin up a sandbox, and start building your own rating‑enhanced plugins today.