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MCP Browser Use Server

by JovaniPink
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# MCP server w/ Browser Use [![smithery badge](https://smithery.ai/badge/@JovaniPink/mcp-browser-use)](https://smithery.ai/server/@JovaniPink/mcp-browser-use) > MCP server for [browser-use](https://github.com/browser-use/browser-use). ## Overview This repository contains the server for the [browser-use](https://github.com/browser-use/browser-use) library, which provides a powerful browser automation system that enables AI agents to interact with web browsers through natural language. The server is built on Anthropic's [Model Context Protocol (MCP)](https://modelcontextprotocol.io/introduction) and provides a seamless integration with the [browser-use](https://github.com/browser-use/browser-use) library. ## Features 1. **Browser Control** - Automated browser interactions via natural language - Navigation, form filling, clicking, and scrolling capabilities - Tab management and screenshot functionality - Cookie and state management 2. **Agent System** - Custom agent implementation in custom_agent.py - Vision-based element detection - Structured JSON responses for actions - Message history management and summarization 3. **Configuration** - Environment-based configuration for API keys and settings - Chrome browser settings (debugging port, persistence) - Model provider selection and parameters ## Dependencies This project relies on the following Python packages: | Package | Version | Description | | :----------------------------------------- | :--------- | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | [pydantic](https://docs.pydantic.dev/) | >=2.10.5 | Data validation and settings management using Python type annotations. Provides runtime enforcement of types and automatic model creation. Essential for defining structured data models in the agent. | | [fastapi](https://fastapi.tiangolo.com/) | >=0.115.6 | Modern, fast (high-performance) web framework for building APIs with Python 3.7+ based on standard Python type hints. Used to create the server that exposes the agent's functionality. | | [uvicorn](https://www.uvicorn.org/) | >=0.22.0 | ASGI web server implementation for Python. Used to serve the FastAPI application. | | [fastmcp](https://pypi.org/project/fastmcp/) | >=0.4.1 | A framework that wraps FastAPI for building MCP (Model Context Protocol) servers. | | [python-dotenv](https://pypi.org/project/python-dotenv/) | >=1.0.1 | Reads key-value pairs from a `.env` file and sets them as environment variables. Simplifies local development and configuration management. | | [langchain](https://www.langchain.com/) | >=0.3.14 | Framework for developing applications with large language models (LLMs). Provides tools for chaining together different language model components and interacting with various APIs and data sources. | | [langchain-openai](https://api.python.langchain.com/en/latest/langchain_openai.html) | >=0.2.14 | LangChain integrations with OpenAI's models. Enables using OpenAI models (like GPT-4) within the LangChain framework. Used in this project for interacting with OpenAI's language and vision models. | | [langchain-ollama](https://api.python.langchain.com/en/latest/langchain_ollama/chat_models/ChatOllama.html) | >=0.2.2 | Langchain integration for Ollama, enabling local execution of LLMs. | | [openai](https://platform.openai.com/docs/api-reference) | >=1.59.5 | Official Python client library for the OpenAI API. Used to interact directly with OpenAI's models (if needed, in addition to LangChain). | | [browser-use](https://github.com/browser-use/browser-use) | ==0.1.19 | A powerful browser automation system that enables AI agents to interact with web browsers through natural language. The core library that powers this project's browser automation capabilities. | | [instructor](https://github.com/jxnl/instructor) | >=1.7.2 | Library for structured output prompting and validation with OpenAI models. Enables extracting structured data from model responses. | | [pyperclip](https://pyperclip.readthedocs.io/) | >=1.9.0 | Cross-platform Python module for copy and paste clipboard functions. | ## Components ### Resources The server implements a browser automation system with: - Integration with browser-use library for advanced browser control - Custom browser automation capabilities - Agent-based interaction system with vision capabilities - Persistent state management - Customizable model settings ### Requirements - Operating Systems (Linux, macOS, Windows; we haven't tested for Docker or Microsoft WSL) - Python 3.11 or higher - uv (fast Python package installer) - Chrome/Chromium browser - [Claude Desktop](https://claude.ai/download) ### Quick Start #### Claude Desktop On MacOS: `~/Library/Application\ Support/Claude/claude_desktop_config.json` On Windows: `%APPDATA%/Claude/claude_desktop_config.json` #### Installing via Smithery To install Browser Use for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@JovaniPink/mcp-browser-use): ```bash npx -y @smithery/cli install @JovaniPink/mcp-browser-use --client claude ``` <details> <summary>Development Configuration</summary> ```json "mcpServers": { "mcp_server_browser_use": { "command": "uvx", "args": [ "mcp-server-browser-use", ], "env": { "OPENAI_ENDPOINT": "https://api.openai.com/v1", "OPENAI_API_KEY": "", "ANTHROPIC_API_KEY": "", "GOOGLE_API_KEY": "", "AZURE_OPENAI_ENDPOINT": "", "AZURE_OPENAI_API_KEY": "", // "DEEPSEEK_ENDPOINT": "https://api.deepseek.com", // "DEEPSEEK_API_KEY": "", // Set to false to disable anonymized telemetry "ANONYMIZED_TELEMETRY": "false", // Chrome settings "CHROME_PATH": "", "CHROME_USER_DATA": "", "CHROME_DEBUGGING_PORT": "9222", "CHROME_DEBUGGING_HOST": "localhost", // Set to true to keep browser open between AI tasks "CHROME_PERSISTENT_SESSION": "false", // Model settings "MCP_MODEL_PROVIDER": "anthropic", "MCP_MODEL_NAME": "claude-3-5-sonnet-20241022", "MCP_TEMPERATURE": "0.3", "MCP_MAX_STEPS": "30", "MCP_USE_VISION": "true", "MCP_MAX_ACTIONS_PER_STEP": "5", "MCP_TOOL_CALL_IN_CONTENT": "true" } } } ``` </details> ### Environment Variables Key environment variables: ```bash # API Keys ANTHROPIC_API_KEY=anthropic_key # Chrome Configuration # Optional: Path to Chrome executable CHROME_PATH=/path/to/chrome # Optional: Chrome user data directory CHROME_USER_DATA=/path/to/user/data # Default: 9222 CHROME_DEBUGGING_PORT=9222 # Default: localhost CHROME_DEBUGGING_HOST=localhost # Keep browser open between tasks CHROME_PERSISTENT_SESSION=false # Model Settings # Options: anthropic, openai, azure, deepseek MCP_MODEL_PROVIDER=anthropic # Model name MCP_MODEL_NAME=claude-3-5-sonnet-20241022 MCP_TEMPERATURE=0.3 MCP_MAX_STEPS=30 MCP_USE_VISION=true MCP_MAX_ACTIONS_PER_STEP=5 ``` ## Development ### Setup 1. Clone the repository: ```bash git clone https://github.com/JovaniPink/mcp-browser-use.git cd mcp-browser-use ``` 2. Create and activate virtual environment: ```bash python -m venv .venv source .venv/bin/activate # On Windows: .venv\Scripts\activate ``` 3. Install dependencies: ```bash uv sync ``` 4. Start the server ```bash uv run mcp-browser-use ``` ### Debugging For debugging, use the [MCP Inspector](https://github.com/modelcontextprotocol/inspector): ```bash npx @modelcontextprotocol/inspector uv --directory /path/to/project run mcp-server-browser-use ``` The Inspector will display a URL for the debugging interface. ## Browser Actions The server supports various browser actions through natural language: - Navigation: Go to URLs, back/forward, refresh - Interaction: Click, type, scroll, hover - Forms: Fill forms, submit, select options - State: Get page content, take screenshots - Tabs: Create, close, switch between tabs - Vision: Find elements by visual appearance - Cookies & Storage: Manage browser state ## Security I want to note that their are some Chrome settings that are set to allow for the browser to be controlled by the server. This is a security risk and should be used with caution. The server is not intended to be used in a production environment. Security Details: [SECURITY.MD](./documentation/SECURITY.md) ## Contributing We welcome contributions to this project. Please follow these steps: 1. Fork this repository. 2. Create your feature branch: `git checkout -b my-new-feature`. 3. Commit your changes: `git commit -m 'Add some feature'`. 4. Push to the branch: `git push origin my-new-feature`. 5. Submit a pull request. For major changes, open an issue first to discuss what you would like to change. Please update tests as appropriate to reflect any changes made.