How to integrate Hyperbrowser MCP with LlamaIndex

This guide walks you through connecting Hyperbrowser to LlamaIndex using the Composio tool router. By the end, you'll have a working Hyperbrowser agent that can start a browser session with stealth mode, extract all product titles from this url, check status of your ongoing scrape job through natural language commands. This guide will help you understand how to give your LlamaIndex agent real control over a Hyperbrowser account through Composio's Hyperbrowser MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

Hyperbrowser logoHyperbrowser
Api Key

Hyperbrowser is a next-generation platform for scalable browser automation. It empowers AI agents to interact with web apps, automate workflows, and handle browser sessions at scale.

42 Tools

Introduction

This guide walks you through connecting Hyperbrowser to LlamaIndex using the Composio tool router. By the end, you'll have a working Hyperbrowser agent that can start a browser session with stealth mode, extract all product titles from this url, check status of your ongoing scrape job through natural language commands.

This guide will help you understand how to give your LlamaIndex agent real control over a Hyperbrowser account through Composio's Hyperbrowser MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Hyperbrowser with

TL;DR

Here's what you'll learn:
  • Set your OpenAI and Composio API keys
  • Install LlamaIndex and Composio packages
  • Create a Composio Tool Router session for Hyperbrowser
  • Connect LlamaIndex to the Hyperbrowser MCP server
  • Build a Hyperbrowser-powered agent using LlamaIndex
  • Interact with Hyperbrowser through natural language

What is LlamaIndex?

LlamaIndex is a data framework for building LLM applications. It provides tools for connecting LLMs to external data sources and services through agents and tools.

Key features include:

  • ReAct Agent: Reasoning and acting pattern for tool-using agents
  • MCP Tools: Native support for Model Context Protocol
  • Context Management: Maintain conversation context across interactions
  • Async Support: Built for async/await patterns

What is the Hyperbrowser MCP server, and what's possible with it?

The Hyperbrowser MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Hyperbrowser account. It provides structured and secure access to automated browser sessions, web scraping, and browser-based task management, so your agent can launch sessions, extract data, manage automation jobs, and monitor progress on your behalf.

  • Automated browser session creation: Let your agent spin up new browser sessions with custom privacy, stealth, and proxy settings for tailored automation tasks.
  • Scalable web scraping and extraction: Easily initiate and manage scrape jobs to extract structured content from any target website, with support for session and scrape customization.
  • Real-time job status monitoring: Have your agent check, track, and report the live status of browser-use, crawl, or data extraction jobs, ensuring you always know what's happening.
  • Retrieve results from automation jobs: Fetch and review the outputs of completed crawl or extract jobs, including paginated data and detailed results, right inside your workflow.
  • Profile and automation management: Create or delete Hyperbrowser profiles as needed, giving you flexible control over your automation environment and resources.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step10 STEPS
1

Prerequisites

Before you begin, make sure you have:
  • Python 3.8/Node 16 or higher installed
  • A Composio account with the API key
  • An OpenAI API key
  • A Hyperbrowser account and project
  • Basic familiarity with async Python/Typescript
2

Getting API Keys for OpenAI, Composio, and Hyperbrowser

OpenAI API key (OPENAI_API_KEY)
  • Go to the OpenAI dashboard
  • Create an API key if you don't have one
  • Assign it to OPENAI_API_KEY in .env
Composio API key and user ID
  • Log into the Composio dashboard
  • Copy your API key from Settings
    • Use this as COMPOSIO_API_KEY
  • Pick a stable user identifier (email or ID)
    • Use this as COMPOSIO_USER_ID
3

Installing dependencies

npm install @composio/llamaindex @llamaindex/openai @llamaindex/tools @llamaindex/workflow dotenv

Create a new Typescript project and install the necessary dependencies:

  • @composio/llamaindex: Composio's LlamaIndex integration
  • @llamaindex/openai: OpenAI LLM integration
  • @llamaindex/tools: MCP client for LlamaIndex
  • @llamaindex/workflow: Workflow framework for LlamaIndex
  • dotenv: Environment variable management
4

Set environment variables

bash
OPENAI_API_KEY=your-openai-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id

Create a .env file in your project root:

These credentials will be used to:

  • Authenticate with OpenAI's GPT-5 model
  • Connect to Composio's Tool Router
  • Identify your Composio user session for Hyperbrowser access
5

Import modules

import "dotenv/config";
import readline from "node:readline/promises";
import { stdin as input, stdout as output } from "node:process";

import { Composio } from "@composio/core";

import { mcp } from "@llamaindex/tools";
import { agent as createAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";

dotenv.config();

Create a new file called hyperbrowser_llamaindex_agent.ts and import the required modules:

Key imports:

  • dotenv.config loads .env at runtime
  • readline gives us a simple CLI chat loop
  • Composio is the main Composio SDK client
  • mcp connects to an MCP endpoint
  • createAgent builds a LlamaIndex agent
  • openai configures the LLM backend
6

Load environment variables and initialize Composio

const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY;
const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID;

if (!OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!COMPOSIO_API_KEY) throw new Error("COMPOSIO_API_KEY is not set");
if (!COMPOSIO_USER_ID) throw new Error("COMPOSIO_USER_ID is not set");

What's happening:

This ensures missing credentials cause early, clear errors before the agent attempts to initialise.

7

Create a Tool Router session and build the agent function

async function buildAgent() {

  console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`);
  console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`);

  const composio = new Composio({
    apiKey: COMPOSIO_API_KEY,
    provider: new LlamaindexProvider(),
  });

  const session = await composio.create(
    COMPOSIO_USER_ID!,
    {
      toolkits: ["hyperbrowser"],
    },
  );

  const mcpUrl = session.mcp.url;
  console.log(`Composio Tool Router MCP URL: ${mcpUrl}`);

  const server = mcp({
    url: mcpUrl,
    clientName: "composio_tool_router_with_llamaindex",
    requestInit: {
      headers: {
        "x-api-key": COMPOSIO_API_KEY!,
      },
    },
    // verbose: true,
  });

  const tools = await server.tools();

  const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" });

  const agent = createAgent({
    name: "composio_tool_router_with_llamaindex",
        description : "An agent that uses Composio Tool Router MCP tools to perform actions.",
    systemPrompt:
      "You are a helpful assistant connected to Composio Tool Router."+
"Use the available tools to answer user queries and perform Hyperbrowser actions." ,
    llm,
    tools,
  });

  return agent;
}

What's happening here:

  • We create a Composio client using your API key and configure it with the LlamaIndex provider
  • We then create a tool router MCP session for your user, specifying the toolkits we want to use (in this case, hyperbrowser)
  • The session returns an MCP HTTP endpoint URL that acts as a gateway to all your configured tools
  • LlamaIndex will connect to this endpoint to dynamically discover and use the available Hyperbrowser tools.
  • The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.
8

Create an interactive chat loop

async function chatLoop(agent: ReturnType<typeof createAgent>) {
  const rl = readline.createInterface({ input, output });

  console.log("Type 'quit' or 'exit' to stop.");

  while (true) {
    let userInput: string;

    try {
      userInput = (await rl.question("\nYou: ")).trim();
    } catch {
      console.log("\nAgent: Bye!");
      break;
    }

    if (!userInput) {
      continue;
    }

    const lower = userInput.toLowerCase();
    if (lower === "quit" || lower === "exit") {
      console.log("Agent: Bye!");
      break;
    }

    try {
      process.stdout.write("Agent: ");

      const stream = agent.runStream(userInput);
      let finalResult: any = null;

      for await (const event of stream) {
        // The event.data contains the streamed content
        const data: any = event.data;

        // Check for streaming delta content
        if (data?.delta) {
          process.stdout.write(data.delta);
        }

        // Store final result for fallback
        if (data?.result || data?.message) {
          finalResult = data;
        }
      }

      // If no streaming happened, show the final result
      if (finalResult) {
        const answer =
          finalResult.result ??
          finalResult.message?.content ??
          finalResult.message ??
          "";
        if (answer && typeof answer === "string" && !answer.includes("[object")) {
          process.stdout.write(answer);
        }
      }

      console.log(); // New line after streaming completes
    } catch (err: any) {
      console.error("\nAgent error:", err?.message ?? err);
    }
  }

  rl.close();
}

What's happening:

  • We're creating a direct terminal interface to chat with Hyperbrowser
  • The LLM's responses are streamed to the CLI for faster interaction.
  • The agent uses context to maintain conversation history
  • The agent processes the request, selects appropriate Hyperbrowser tools, and returns a result
  • We extract the answer from the result data structure and display it to the user
  • You can type 'quit' or 'exit' to stop the chat loop gracefully
  • Agent responses and any errors are streamed in a clear, readable format
9

Define the main entry point

async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err) {
    console.error("Failed to start agent:", err);
    process.exit(1);
  }
}

main();

What's happening here:

  • We're orchestrating the entire application flow
  • The agent gets built with proper error handling
  • Then we kick off the interactive chat loop so you can start talking to Hyperbrowser
10

Run the agent

npx ts-node llamaindex-agent.ts

When prompted, authenticate and authorise your agent with Hyperbrowser, then start asking questions.

Complete Code

Here's the complete code to get you started with Hyperbrowser and LlamaIndex:

import "dotenv/config";
import readline from "node:readline/promises";
import { stdin as input, stdout as output } from "node:process";

import { Composio } from "@composio/core";
import { LlamaindexProvider } from "@composio/llamaindex";

import { mcp } from "@llamaindex/tools";
import { agent as createAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";

dotenv.config();

const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY;
const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID;

if (!OPENAI_API_KEY) {
    throw new Error("OPENAI_API_KEY is not set in the environment");
  }
if (!COMPOSIO_API_KEY) {
    throw new Error("COMPOSIO_API_KEY is not set in the environment");
  }
if (!COMPOSIO_USER_ID) {
    throw new Error("COMPOSIO_USER_ID is not set in the environment");
  }

async function buildAgent() {

  console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`);
  console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`);

  const composio = new Composio({
    apiKey: COMPOSIO_API_KEY,
    provider: new LlamaindexProvider(),
  });

  const session = await composio.create(
    COMPOSIO_USER_ID!,
    {
      toolkits: ["hyperbrowser"],
    },
  );

  const mcpUrl = session.mcp.url;
  console.log(`Composio Tool Router MCP URL: ${mcpUrl}`);

  const server = mcp({
    url: mcpUrl,
    clientName: "composio_tool_router_with_llamaindex",
    requestInit: {
      headers: {
        "x-api-key": COMPOSIO_API_KEY!,
      },
    },
    // verbose: true,
  });

  const tools = await server.tools();

  const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" });

  const agent = createAgent({
    name: "composio_tool_router_with_llamaindex",
    description:
      "An agent that uses Composio Tool Router MCP tools to perform actions.",
    systemPrompt:
      "You are a helpful assistant connected to Composio Tool Router."+
"Use the available tools to answer user queries and perform Hyperbrowser actions." ,
    llm,
    tools,
  });

  return agent;
}

async function chatLoop(agent: ReturnType<typeof createAgent>) {
  const rl = readline.createInterface({ input, output });

  console.log("Type 'quit' or 'exit' to stop.");

  while (true) {
    let userInput: string;

    try {
      userInput = (await rl.question("\nYou: ")).trim();
    } catch {
      console.log("\nAgent: Bye!");
      break;
    }

    if (!userInput) {
      continue;
    }

    const lower = userInput.toLowerCase();
    if (lower === "quit" || lower === "exit") {
      console.log("Agent: Bye!");
      break;
    }

    try {
      process.stdout.write("Agent: ");

      const stream = agent.runStream(userInput);
      let finalResult: any = null;

      for await (const event of stream) {
        // The event.data contains the streamed content
        const data: any = event.data;

        // Check for streaming delta content
        if (data?.delta) {
          process.stdout.write(data.delta);
        }

        // Store final result for fallback
        if (data?.result || data?.message) {
          finalResult = data;
        }
      }

      // If no streaming happened, show the final result
      if (finalResult) {
        const answer =
          finalResult.result ??
          finalResult.message?.content ??
          finalResult.message ??
          "";
        if (answer && typeof answer === "string" && !answer.includes("[object")) {
          process.stdout.write(answer);
        }
      }

      console.log(); // New line after streaming completes
    } catch (err: any) {
      console.error("\nAgent error:", err?.message ?? err);
    }
  }

  rl.close();
}

async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err: any) {
    console.error("Failed to start agent:", err?.message ?? err);
    process.exit(1);
  }
}

main();

Conclusion

You've successfully connected Hyperbrowser to LlamaIndex through Composio's Tool Router MCP layer. Key takeaways:
  • Tool Router dynamically exposes Hyperbrowser tools through an MCP endpoint
  • LlamaIndex's ReActAgent handles reasoning and orchestration; Composio handles integrations
  • The agent becomes more capable without increasing prompt size
  • Async Python provides clean, efficient execution of agent workflows
You can easily extend this to other toolkits like Gmail, Notion, Stripe, GitHub, and more by adding them to the toolkits parameter.
TOOLS

Supported Tools

Every Hyperbrowser action and event your agent gets out of the box.

Add Extension

Tool to add a new browser extension to Hyperbrowser for use in sessions.

Create Hyperbrowser Profile

Creates a new persistent Hyperbrowser profile for storing browser state (cookies, sessions, etc.

Create Scrape Job

Tool to initiate a new scrape job.

Create Session

Tool to create a new browser session with custom stealth, proxy, and privacy settings.

Delete Profile

Tool to delete a profile.

Fetch Web Page

Tool to fetch a web page and return content in various formats (HTML, Markdown, JSON, screenshot, etc.

Get browser-use task status

Tool to retrieve the current status of a browser-use task.

Get Claude Computer Use Task Result

Tool to retrieve the complete result and status of a Claude Computer Use task.

Get Claude Computer Use Task Status

Poll the execution status of a Claude Computer Use task.

Get Crawl Job Status

Tool to retrieve the status and results of a specific crawl job.

Get Crawl Status

Tool to retrieve the current status of a specific crawl job.

Get CUA Task Result

Tool to retrieve the status and results of a CUA (Claude User Agent) task.

Get CUA Task Status

Poll the execution status of a CUA task.

Get Extract Job Result

Tool to fetch the status and results of a specific extract job.

Get Extract Job Status

Retrieve the status of an extract job.

Get Gemini Computer Use task result

Tool to retrieve the current status and results of a Gemini Computer Use task.

Get HyperAgent Task Result

Tool to retrieve the status and results of a HyperAgent task.

Get Profile By ID

Retrieves details of a specific Hyperbrowser profile by its UUID.

Get Scrape Job Result

Retrieves the status and results of a scrape job.

Get Scrape Job Status

Tool to retrieve the current status of a specific scrape job.

Get Session Details

Retrieve detailed information about a Hyperbrowser session by its ID.

Get Session Downloads URL

Tool to retrieve the downloads URL for a session.

Get Session Recording

Retrieve the recording URL for a browser session.

Get Session Video Recording URL

Tool to retrieve the video recording URL for a browser session.

Get Web Crawl Result

Tool to retrieve the status and results of a web crawl job.

Get Web Crawl Status

Tool to retrieve just the status of a web crawl job without the full results.

List Extensions

Tool to list all browser extensions.

List Profiles

Tool to list profiles.

List Sessions

Tool to list sessions with optional status filter.

Search Web

Tool to perform a web search and retrieve results with titles, URLs, and descriptions.

Start Browser Use Task

Tool to start an asynchronous browser-use task.

Start Claude Computer Use Task

Tool to start a Claude Computer Use task.

Start Crawl Job

Tool to start a new crawl job for a specified URL.

Start CUA Task

Tool to start an OpenAI CUA (Computer-Using Agent) task.

Start Extract Job

Start an AI-powered data extraction job from one or more web pages.

Start Gemini Computer Use Task

Tool to start a Gemini Computer Use task for browser automation using Google's Gemini.

Start Web Crawl

Tool to start an asynchronous web crawl job that follows links from a starting URL and returns content from each page.

Stop Browser Use Task

Tool to stop a running browser-use task.

Stop Claude Computer Use Task

Tool to stop a running Claude computer use task.

Stop CUA Task

Tool to stop a running CUA task.

Stop Gemini Computer Use Task

Tool to stop a running Gemini computer use task.

Stop Session

Tool to stop a running session by ID.

FAQ

Frequently asked questions

With a standalone Hyperbrowser MCP server, the agents and LLMs can only access a fixed set of Hyperbrowser tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Hyperbrowser and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. LlamaIndex fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Hyperbrowser tools.

Yes, absolutely. You can configure which Hyperbrowser scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Hyperbrowser data and credentials are handled as safely as possible.

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