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\n
\n
\n $\"Browser$ \n
\n
\n

\n\n# Browser Use MCP Server\n\nA FastMCP server that enables browser automation through natural language commands. This server allows Language Models to browse the web, fill out forms, click buttons, and perform other web-based tasks via a simple API.\n\n## Quick Start\n\n### 1. Install the package\n\nInstall with a specific provider (e.g., OpenAI)\n\n```bash\npip install -e \"git+https://github.com/yourusername/browser-use-mcp.git#egg=browser-use-mcp[openai]\"\n```\nOr install all providers\n```bash\n\npip install -e \"git+https://github.com/yourusername/browser-use-mcp.git#egg=browser-use-mcp[all-providers]\"\n```\nInstall Playwright browsers\n```bash\nplaywright install chromium\n```\n\n### 2. Configure your MCP client\n\nAdd the browser-use-mcp server to your MCP client configuration:\n\n```javascript\n{\n \"mcpServers\": {\n \"browser-use-mcp\": {\n \"command\": \"browser-use-mcp\",\n \"args\": [\"--model\", \"gpt-4o\"],\n \"env\": {\n \"OPENAI_API_KEY\": \"your-openai-api-key\", // Or any other provider's API key\n \"DISPLAY\": \":0\" // For GUI environments\n }\n }\n }\n}\n```\n\nReplace `\"your-openai-api-key\"` with your actual API key or use an environment variable reference like `process.env.OPENAI_API_KEY`.\n\n### 3. Use it with your favorite MCP client\n\n#### Example using mcp-use with Python\n\n```python\nimport asyncio\nimport os\nfrom dotenv import load_dotenv\nfrom langchain_openai import ChatOpenAI\nfrom mcp_use import MCPAgent, MCPClient\n\nasync def main():\n # Load environment variables\n load_dotenv()\n\n # Create MCPClient from config file\n client = MCPClient(\n config={\n \"mcpServers\": {\n \"browser-use-mcp\": {\n \"command\": \"browser-use-mcp\",\n \"args\": [\"--model\", \"gpt-4o\"],\n \"env\": {\n \"OPENAI_API_KEY\": os.getenv(\"OPENAI_API_KEY\"),\n \"DISPLAY\": \":0\",\n },\n }\n }\n }\n )\n\n # Create LLM\n llm = ChatOpenAI(model=\"gpt-4o\")\n\n # Create agent with the client\n agent = MCPAgent(llm=llm, client=client, max_steps=30)\n\n # Run the query\n result = await agent.run(\n \"\"\"\n Navigate to https://github.com, search for \"browser-use-mcp\", and summarize the project.\n \"\"\",\n max_steps=30,\n )\n print(f\"\\nResult: {result}\")\n\nif __name__ == \"__main__\":\n asyncio.run(main())\n```\n\n#### Using Claude for Desktop\n\n1. Open Claude for Desktop\n2. Go to Settings → Experimental features\n3. Enable Claude API Beta and OpenAPI schema for API\n4. Add the following configuration to your Claude Desktop config file:\n - Mac: `~/Library/Application Support/Claude/claude_desktop_config.json`\n - Windows: `%AppData%\\Claude\\claude_desktop_config.json`\n\n```json\n{\n \"mcpServers\": {\n \"browser-use\": {\n \"command\": \"browser-use-mcp\",\n \"args\": [\"--model\", \"claude-3-opus-20240229\"]\n }\n }\n}\n```\n\n5. Start a new conversation with Claude and ask it to perform web tasks\n\n## Supported LLM Providers\n\nThe following LLM providers are supported for browser automation:\n\n| Provider | API Key Environment Variable |\n|----------|----------------------------|\n| OpenAI | `OPENAI_API_KEY` |\n| Anthropic | `ANTHROPIC_API_KEY` |\n| Google | `GOOGLE_API_KEY` |\n| Cohere | `COHERE_API_KEY` |\n| Mistral AI | `MISTRAL_API_KEY` |\n| Groq | `GROQ_API_KEY` |\n| Together AI | `TOGETHER_API_KEY` |\n| AWS Bedrock | `AWS_ACCESS_KEY_ID` and `AWS_SECRET_ACCESS_KEY` |\n| Fireworks | `FIREWORKS_API_KEY` |\n| Azure OpenAI | `AZURE_OPENAI_API_KEY` and `AZURE_OPENAI_ENDPOINT` |\n| Vertex AI | `GOOGLE_APPLICATION_CREDENTIALS` |\n| NVIDIA | `NVIDIA_API_KEY` |\n| AI21 | `AI21_API_KEY` |\n| Databricks | `DATABRICKS_HOST` and `DATABRICKS_TOKEN` |\n| IBM watsonx.ai | `WATSONX_API_KEY` |\n| xAI | `XAI_API_KEY` |\n| Upstage | `UPSTAGE_API_KEY` |\n| Hugging Face | `HUGGINGFACE_API_KEY` |\n| Ollama | `OLLAMA_BASE_URL` |\n| Llama.cpp | `LLAMA_CPP_SERVER_URL` |\n\nFor more information check out: https://python.langchain.com/docs/integrations/chat/\n\nYou can create a `.env` file in the project directory with your API keys:\n\n```\nOPENAI_API_KEY=your_openai_key_here\n# Or any other provider key\n```\n\n## Troubleshooting\n\n- **API Key Issues**: Ensure your API key is correctly set in your environment variables or `.env` file.\n- **Provider Not Found**: Make sure you've installed the required provider package.\n- **Browser Automation Errors**: Check that Playwright is correctly installed with `playwright install chromium`.\n- **Model Selection**: If you get errors about an invalid model, try using the `--model` flag to specify a valid model for your provider.\n- **Debug Mode**: Use `--debug` to enable more detailed logging that can help identify issues.\n- **MCP Client Configuration**: Make sure your MCP client is correctly configured with the right command and environment variables.\n\n## License\n\nMIT # browser-use-mcp\n","English","tag","en-US",{"_41":42,"_13":43,"_50":32,"_51":32,"_16":52,"_53":54,"_33":34,"_129":130,"_137":-5,"_138":-5,"_139":140,"_169":170,"_174":-5,"_61":156,"_175":160,"_64":176,"_177":178},"addedAt","2025-04-21T22:00:38.418756Z",[44,45,46,47,48,49],"category:browser-automation","category:agent-orchestration","environment:local","hosting:hybrid","language:python","author:claimed","descriptionMarkdown","descriptionPlainText",5780,"integrations",[55,66,73,80,87,94,101,108,115,122],{"_56":57,"_31":63,"_64":65},"brand",{"_58":59,"_33":60,"_61":62},"logoSvgPath","M.95 14.184L12 20.403l9.919-5.55v2.21L12 22.662l-10.484-5.96-.565.308v.77L12 24l11.05-6.218v-4.317l-.515-.309L12 19.118l-9.867-5.653v-2.21L12 16.805l11.05-6.218V6.32l-.515-.308L12 11.974 2.647 6.681 12 1.388l7.76 4.368.668-.411v-.566L12 0 .95 6.27v.72L12 13.207l9.919-5.55v2.26L12 15.52 1.516 9.56l-.565.308Z","Databricks","slug","databricks","Enables browser automation with Databricks language 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