How to integrate Browserless MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Browserless to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Browserless agent that can download all invoices from my dashboard, extract product details from a competitor's site, take a screenshot of my homepage after login, generate a pdf of my latest blog post through natural language commands.

This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Browserless account through Composio's Browserless MCP server.

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

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Browserless
  • Configure an AI agent that can use Browserless as a tool
  • Run a live chat session where you can ask the agent to perform Browserless operations

What is open-ai-agents-sdk?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

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

The Browserless MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Browserless account. It provides structured and secure access to browser automation tools, so your agent can perform actions like fetching web content, scraping data, generating PDFs, taking screenshots, and running custom browser scripts on your behalf.

  • Dynamic web content extraction: Instruct your agent to fetch full HTML content—including JavaScript-rendered pages—from any website.
  • Automated web scraping: Let your agent extract structured data from pages using CSS selectors, returning results in convenient JSON format.
  • On-demand PDF generation: Have your agent instantly generate PDFs from any webpage, with customizable parameters like format and filename.
  • Website screenshot capture: Direct your agent to take high-quality screenshots of entire pages or specific sections, supporting multiple image formats and options.
  • Custom browser automations: Empower your agent to execute tailored Puppeteer scripts, enabling powerful workflows like file downloads or bypassing bot protections.

Supported Tools & Triggers

Tools
Download file using Puppeteer scriptThis tool allows downloading files that chrome has downloaded during the execution of puppeteer code.
Execute Custom FunctionA tool that allows executing custom puppeteer scripts via http requests.
Fetch HTML ContentThis tool fetches the complete html content of a webpage using browserless's content api.
Generate PDF from webpageThis tool generates a pdf from a specified webpage using browserless's pdf generation api.
Scrape webpage content using CSS selectorsA tool to extract structured content from a webpage by specifying css selectors.
Take ScreenshotA tool that captures a screenshot of a webpage using browserless's screenshot api.
Unblock Protected ContentThis tool provides access to content from websites that implement bot protection mechanisms.

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

What is Tool Router?

Composio's Tool Router 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 Tool Router

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

How the Tool Router works

The Tool Router 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

Prerequisites

Before starting, make sure you have:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Browserless project
  • Some knowledge of Python or Typescript

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key

Install dependencies

pip install composio_openai_agents openai-agents python-dotenv

Install the Composio SDK and the OpenAI Agents SDK.

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

Import dependencies

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Browserless.

Set up the Composio instance

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
What's happening:
  • load_dotenv() loads your .env file so OPENAI_API_KEY and COMPOSIO_API_KEY are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.

Create a Tool Router session

# Create a Browserless Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["browserless"]
)

mcp_url = session.mcp.url

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only browserless.
  • The router checks the user's Browserless connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Browserless.
  • This approach keeps things lightweight and lets the agent request Browserless tools only when needed during the conversation.

Configure the agent

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Browserless. "
        "Help users perform Browserless operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access Browserless and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a HostedMCPTool that connects to the MCP server URL we created earlier.
  • The headers dict includes the Composio API key for secure authentication with the MCP server.
  • require_approval: 'never' means the agent can execute Browserless operations without asking for permission each time, making interactions smoother.

Start chat loop and handle conversation

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
What's happening:
  • The program prints a session URL that you visit to authorize Browserless.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using Runner.run().
  • The responses are printed to the console, and conversations are saved locally using SQLite.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Browserless and open-ai-agents-sdk:

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["browserless"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Browserless. "
        "Help users perform Browserless operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())

Conclusion

This was a starter code for integrating Browserless MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Browserless.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

How to build Browserless MCP Agent with another framework

Claude Agent SDK

Claude Agent SDK

Use Browserless MCP with Claude Agent SDK

Google ADK

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Use Browserless MCP with Google ADK

LangChain

LangChain

Use Browserless MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Browserless MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Browserless MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Browserless MCP with LlamaIndex

CrewAI

CrewAI

Use Browserless MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Browserless MCP?

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

Can I use Tool Router MCP with OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK 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 Browserless tools.

Can I manage the permissions and scopes for Browserless while using Tool Router?

Yes, absolutely. You can configure which Browserless 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.

How safe is my data with Composio Tool Router?

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 Browserless data and credentials are handled as safely as possible.

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