selenium-mcp 1.0.0

Selenium WebDriver MCP server for AI agents and LLM-powered browser automation

selenium-mcp-server

Selenium WebDriver MCP server that enables LLMs & AI agents to control real browsers using Selenium and MCP.

This project exposes Selenium WebDriver as an MCP (Model Context Protocol) server, allowing AI agents to control a real browser through structured tools.

It enables LLMs and autonomous agents to perform tasks like:

• Opening browsers
• Navigating websites
• Discovering UI elements
• Clicking buttons and links
• Typing into inputs
• Extracting page text
• Taking screenshots
• Many more future upgrades (in-progress)

This makes it possible to build AI-powered browser automation systems and autonomous QA agents.

WHY THIS PROJECT EXISTS

Modern AI agents need a way to interact with real applications.

While traditional automation tools like Selenium exist, they are not directly usable by LLM agents.

This project bridges that gap by exposing Selenium functionality through MCP tools so that agents can:

• Understand web pages
• Discover UI elements
• Perform actions
• Validate results

ARCHITECTURE

flowchart TD
    A[LLM Agent] --> B[MCP Protocol]
    B --> C[Selenium MCP Server]

    C --> D[Browser Tools]
    C --> E[Navigation Tools]
    C --> F[Interaction Tools]
    C --> G[Element Tools]
    C --> H[Debug Tools]

    D --> I[Selenium WebDriver]
    E --> I
    F --> I
    G --> I
    H --> I
    
    I --> J[Browser]

FEATURES

• MCP-compatible Selenium automation server
• Browser session management
• Navigation controls
• UI element discovery
• Accessibility-aware interaction
• Screenshot capture
• Page text extraction
• Headless browser support

INSTALLATION

Clone the repository

git clone https://github.com/nayakprashant/selenium-mcp-server.git

cd selenium-mcp-server

Create a virtual environment

python -m venv .venv

Activate the environment

Mac / Linux

source .venv/bin/activate

Windows

.venv\Scripts\activate

Install dependencies

pip install -r requirements.txt

ENVIRONMENT CONFIGURATION

Create a .env file in the root of the project.

Add the following variable:

MCP_SCREENSHOT_DIR=/path/to/screenshot/directory

Example:

MCP_SCREENSHOT_DIR=/Users/yourname/screenshots

This variable defines the directory where screenshots captured by the take_screenshot tool will be saved.

Make sure the directory exists, and the application has permission to write files to it.

RUNNING THE SERVER

Start the MCP server

python -m server

This launches the Selenium MCP server and exposes browser automation tools to AI agents.

TESTING THE SERVER

Run the following command to verify that the MCP server is running correctly:

python -m test.mcp_test 

This script checks whether the Selenium MCP server is initialized successfully and whether the required tools are available.

If the server is set up correctly, you should see the following message in the terminal or logs:

Selenium MCP Server Test Status: SUCCESS

If the setup fails, the logs will display an error message indicating that the server test did not pass.

BROWSER SESSION FLOW

Each browser session is identified by a session_id.

Typical workflow for agents:

1. open_browser
2. open_url
3. wait_for_page
4. get_interactive_elements
5. click_element or type_into_element

AVAILABLE MCP TOOLS

BROWSER CONTROL

1. open_browser – Launch a new browser session
2. close_browser – Close the browser session
3. maximize_browser – Maximize browser window
4. fullscreen_browser – Switch browser to fullscreen

NAVIGATION

1. open_url – Navigate to a specific URL
2. navigate_back – Navigate back in browser history
3. navigate_forward – Navigate forward in history
4. refresh_page – Reload the page
5. wait_for_page – Wait for page to load
6. get_page_title – Get the current page title

ELEMENT DISCOVERY

1. get_interactive_elements – Discover visible interactive elements on the page
2. get_accessibility_tree – Retrieve simplified accessibility tree for the page

These tools allow agents to understand the UI structure before interacting with it.

INTERACTION TOOLS

1. click_element – Click an element by index
2. type_into_element – Enter text into an input field

Elements must first be discovered using: get_interactive_elements

PAGE ANALYSIS

get_page_text – Extract visible text from the page

Useful for:

• validation
• reasoning
• information extraction

VISUAL DEBUGGING

take_screenshot – Capture a screenshot of the current browser window

To change the location, set the environment variable:

MCP_SCREENSHOT_DIR

EXAMPLE AGENT WORKFLOW

Example task:

Search Google for "Selenium MCP"

Agent steps:

open_browser

open_url("https://google.com")

wait_for_page

get_interactive_elements

type_into_element(index, "Selenium MCP")

click_element(index)

wait_for_page

get_page_text

SYSTEM PROMPT FOR AI AGENTS

This repository includes a production-grade system prompt designed specifically for browser automation agents that interact with this Selenium MCP server.

The prompt contains detailed operational guidelines that instruct the AI agent on how to:

• initialize and control the browser
• discover and interact with UI elements
• analyze page structure using the accessibility tree
• avoid hallucinating element indexes
• handle navigation and page reloads
• recover from stale elements
• follow a deterministic execution loop (PLAN → ACT → OBSERVE → UPDATE PLAN)
• enforce safety limits on tool usage

Prompt location

prompts/system_prompt.py

How to use

Whenever you build an AI agent that interacts with this MCP server, this prompt should be provided as the system prompt for the model.

Example:

from prompts.system_prompt import SYSTEM_PROMPT

messages = [
    {"role": "system", "content": SYSTEM_PROMPT},
    {"role": "user", "content": "Your task here"}
]

Why this prompt

Browser automation agents can easily make incorrect decisions if not guided properly. This system prompt provides strict operational rules and guardrails that help the agent:

• use MCP tools correctly
• avoid incorrect element interactions
• minimize hallucinations
• perform reliable browser automation tasks

Using this prompt significantly improves the stability, accuracy, and reliability of AI-driven browser automation.

Recommendation

It is strongly recommended that all AI agents interacting with this Selenium MCP server use this system prompt to ensure consistent and reliable behavior.

PROMPT CUSTOMIZATION

You may modify or extend the system prompt depending on your use case. However, it is recommended to preserve the core operational rules related to:

• MCP tool usage
• element discovery
• navigation handling
• safety limits

LOGGING

All application logs are written to the logs/ directory located at the project root.

Features:

• Daily log file rotation
• Automatic cleanup of older log files
• Logs written to both console and file

This helps with easier debugging and monitoring of the MCP server.

REQUIREMENTS

• Python 3.10+
• Selenium
• Web browser
• webdriver-manager
• MCP Python SDK

USE CASES

This project can be used to build:

• AI test automation agents
• Autonomous QA assistants
• LLM-powered browser copilots
• Self-healing test frameworks
• AI web scraping agents
• Intelligent UI testing systems

CONTRIBUTING

Contributions are welcome.

Steps:

1. Fork the repository
2. Create a feature branch
3. Submit a pull request

LICENSE

MIT License

AUTHOR

Prashant Nayak

🔗 LinkedIn: https://www.linkedin.com/in/prashantjnayak

Built to help the QA and AI automation community build intelligent browser automation systems.

SUPPORT THE PROJECT

If this project helps you:

• Star the repository
• Share it with the QA community