Nota del proyecto : Esta implementación del servidor MCP se basa en la base del uso del navegador y la interfaz web . La lógica principal de automatización del navegador y los patrones de configuración se adaptaron del proyecto original.
Servidor de automatización de navegador impulsado por IA que implementa el Protocolo de contexto de modelo (MCP) para el control del navegador en lenguaje natural.
🧠 Integración MCP : implementación completa del protocolo para la comunicación con agentes de IA
🌐 Automatización del navegador : navegación de páginas, llenado de formularios e interacción con elementos
👁️ Comprensión visual : análisis de capturas de pantalla e interacciones basadas en la visión
🔄 Persistencia del estado : mantener las sesiones del navegador entre tareas
🔌 Compatibilidad con múltiples LLM : integración con OpenAI, Anthropic, Azure y DeepSeek
Related MCP server: Cloudflare Playwright MCP
Python 3.11 o superior
uv (instalador rápido de paquetes de Python)
Navegador Chrome/Chromium
En MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json En Windows: %APPDATA%/Claude/claude_desktop_config.json
"mcpServers": {
"browser-use": {
"command": "uvx",
"args": [
"mcp-server-browser-use",
],
"env": {
"OPENROUTER_API_KEY": "",
"OPENROUTER_ENDPOINT": "https://openrouter.ai/api/v1",
"OPENAI_ENDPOINT": "https://api.openai.com/v1",
"OPENAI_API_KEY": "",
"ANTHROPIC_ENDPOINT": "https://api.anthropic.com",
"ANTHROPIC_API_KEY": "",
"GOOGLE_API_KEY": "",
"AZURE_OPENAI_ENDPOINT": "",
"AZURE_OPENAI_API_KEY": "",
"DEEPSEEK_ENDPOINT": "https://api.deepseek.com",
"DEEPSEEK_API_KEY": "",
"MISTRAL_API_KEY": "",
"MISTRAL_ENDPOINT": "https://api.mistral.ai/v1",
"OLLAMA_ENDPOINT": "http://localhost:11434",
"ANONYMIZED_TELEMETRY": "true",
"BROWSER_USE_LOGGING_LEVEL": "info",
"CHROME_PATH": "",
"CHROME_USER_DATA": "",
"CHROME_DEBUGGING_PORT": "9222",
"CHROME_DEBUGGING_HOST": "localhost",
"CHROME_PERSISTENT_SESSION": "false",
"BROWSER_HEADLESS": "false",
"BROWSER_DISABLE_SECURITY": "false",
"BROWSER_WINDOW_WIDTH": "1280",
"BROWSER_WINDOW_HEIGHT": "720",
"BROWSER_TRACE_PATH": "trace.json",
"BROWSER_RECORDING_PATH": "recording.mp4",
"RESOLUTION": "1920x1080x24",
"RESOLUTION_WIDTH": "1920",
"RESOLUTION_HEIGHT": "1080",
"VNC_PASSWORD": "youvncpassword",
"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"
}
}"browser-use": {
"command": "uv",
"args": [
"--directory",
"/path/to/mcp-browser-use",
"run",
"mcp-server-browser-use"
],
"env": {
...
}
}# Install dev dependencies
uv sync
# Run with debugger
npx @modelcontextprotocol/inspector uv --directory . run mcp-server-browser-useConflictos del navegador : cierre todas las instancias de Chrome antes de comenzar.
Errores de API : Verifique que las claves de API en las variables de entorno coincidan con su proveedor de LLM.
Soporte de visión : asegúrese de que MCP_USE_VISION=true para el análisis de capturas de pantalla.
El servidor admite múltiples proveedores LLM mediante variables de entorno. Estas son las opciones disponibles para MCP_MODEL_PROVIDER :
Proveedor | Valor | Variables de entorno requeridas |
Antrópico |
| CLAVE DE API |
OpenAI |
|
|
Azure OpenAI |
| CLAVE DE API |
Búsqueda profunda |
| CLAVE DE API |
Géminis |
|
|
Mistral |
|
|
Ollama |
|
|
OpenRouter |
| CLAVE DE API DE OPENROUTER PUNTO FINAL |
Para los puntos finales marcados como opcionales, se utilizarán los valores predeterminados si no se especifican
La temperatura se puede configurar usando MCP_TEMPERATURE (valor predeterminado: 0,3)
El modelo se puede especificar utilizando MCP_MODEL_NAME
Para los modelos Ollama, se pueden configurar configuraciones de contexto adicionales como num_ctx y num_predict
Este proyecto amplía la interfaz web y el uso del navegador bajo la licencia MIT. Agradecemos especialmente a los autores originales por su marco de automatización del navegador.
MIT - Ver LICENCIA para más detalles.
Handle run-browser-agent tool calls.
| Name | Required | Description | Default |
|---|---|---|---|
| add_infos | No | ||
| task | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure but fails completely. It doesn't indicate whether this is a read or write operation, what side effects it might have, what permissions are required, or what the expected behavior is. The phrase 'Handle... tool calls' is too vague to convey any meaningful behavioral information.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
While the description is technically concise (only 5 words), this represents under-specification rather than effective brevity. The single sentence doesn't earn its place by providing meaningful information. A truly concise description would still convey essential purpose and usage information in minimal words, which this fails to do.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a tool with 2 parameters, no annotations, no output schema, and 0% schema description coverage, the description is completely inadequate. It provides no information about what the tool does, how to use it, what parameters mean, or what to expect from its operation. The description fails to compensate for any of the missing structured information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, meaning neither parameter has any description in the schema. The tool description provides no information about what the 'task' or 'add_infos' parameters mean, what format they should take, or how they affect the tool's operation. For a tool with 2 parameters and zero schema documentation, this represents a complete failure to add parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Handle run-browser-agent tool calls' is essentially a tautology that restates the tool name without explaining what the tool actually does. It doesn't specify what 'run-browser-agent' means, what resources it operates on, or what action it performs. While it mentions 'tool calls', this adds no meaningful information beyond the name itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance on when to use this tool, what context it's appropriate for, or what alternatives might exist. There are no sibling tools mentioned, but even for a standalone tool, the description fails to give any indication of its intended use case or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v1.0.0run_browser_agentScored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'run_browser_agent' has a distinct purpose that cannot be confused with any other tool in this set.
The naming pattern cannot be inconsistent with only one tool. The tool name 'run_browser_agent' follows a clear verb_noun pattern, and there are no other tools to create naming conflicts or mixed conventions.
A single tool is generally too few for most server purposes, as it limits functionality and may not cover the domain adequately. For a browser automation server, one tool feels thin and restrictive compared to typical expectations of multiple actions like navigation, clicking, or form filling.
The tool surface is severely incomplete for browser automation. With only one tool to run an agent, there are obvious gaps in core operations such as navigating to URLs, interacting with page elements, extracting data, or managing browser sessions, which will likely cause agent failures in practical use.
AI-powered browser automation — navigate, click, fill forms, and extract data from any website.
AI-powered web automation. Navigate websites using AI agents for one page or a thousand
AI-powered web automation. Navigate websites using AI agents for one page or a thousand
Stealth web automation for AI agents. Login, signup, navigate, screenshot.
