​Building a Browser Automation Agent​

The browser is still the most universal interface, with 4.3 billion pages visited every day!

Today, let's do a demo on how we can completely automate it with a local stack:

• ​Stagehand​ open-source AI browser automation.
• CrewAI for orchestration.
• Ollama to run gpt-oss.

System overview:

• The user enters an automation query.
• Planner Agent creates an automation plan.
• The Browser Automation Agent executes it using the Stagehand tool.
• The Response Agent generates a response.

Now, let's dive into the code!

Define LLM

We use three LLMs:

• Planner LLM: Creates a structured plan for an automation task.
• Automation LLM: Executes the plan using the Stagehand tool.
• Response LLM: Synthesizes final response.

Define Automation Planner Agent

The planner agent receives an automation task from the user and creates a structured layout for execution by the browser agent.

Define Stagehand Browser Tool

A custom CrewAI tool utilizes AI to interact with web pages.

It leverages Stagehand's computer-use agentic capabilities to autonomously navigate URLs, perform page actions, and extract data to answer questions.

Define Browser Automation Agent

Browser Automation Agent utilizes the aforementioned Stagehand tool for autonomous browser control and plan execution.

Define Response Synthesis Agent

Synthesis Agent acts as final quality control, refining output from the browser automation agent to generate a polished response.

Create CrewAI Agentic Flow

Finally, we connect our Agents within a workflow using CrewAI Flows.

Done!

Here’s our multi-agent browser automation workflow in action, where we asked it to find the top contributor on the Stagehand GitHub repo:

It initiated a local browser session, navigated the web page, and extracted the information.

​You can find the Stagehand GitHub repo here →​

​You can find the code in the GitHub Repository →

Thanks for reading!