BrowserOS/packages/browseros-agent/apps/server

BrowserOS Server

MCP server and AI agent loop powering BrowserOS browser automation. This is the core backend — it connects to Chromium via CDP, exposes 53+ MCP tools, and runs the AI agent that interprets natural language into browser actions.

Runtime: Bun · Framework: Hono · AI: Vercel AI SDK · License: AGPL-3.0

Architecture

┌──────────────────────────────────────────────────────────────────────┐
│                         MCP Clients                                  │
│           (Agent UI, Claude Code, Gemini CLI, browseros-cli)         │
└──────────────────────────────────────────────────────────────────────┘
                                │
                                │ HTTP / SSE / StreamableHTTP
                                ▼
┌──────────────────────────────────────────────────────────────────────┐
│                    BrowserOS Server (Bun)                             │
│                                                                      │
│   /mcp ─────── MCP tool endpoints (53+ tools)                       │
│   /chat ────── Agent streaming (AI SDK)                              │
│   /health ─── Health check                                           │
│                                                                      │
│   ┌─────────────────────────────────────────────────────────────┐   │
│   │  Agent Loop                                                  │   │
│   │  ├── Multi-provider AI SDK (OpenAI, Anthropic, Google, ...) │   │
│   │  ├── Session & conversation management                       │   │
│   │  ├── Context overflow handling + compaction                  │   │
│   │  └── MCP client for external tool servers                    │   │
│   └─────────────────────────────────────────────────────────────┘   │
│                                                                      │
│   ┌─────────────────────────────────────────────────────────────┐   │
│   │  CDP-backed browser tools                                   │   │
│   │  (tabs, bookmarks, history, navigation, tab groups,         │   │
│   │   screenshots, DOM, network, console, input)                │   │
│   └─────────────────────────────────────────────────────────────┘   │
└──────────────────────────────────────────────────────────────────────┘
                                │
                                │ Chrome DevTools Protocol
                                ▼
                     ┌─────────────────────┐
                     │   Chromium CDP      │
                     │  (port 9000)        │
                     │                     │
                     │  DOM, network,      │
                     │  input, screenshots │
                     └─────────────────────┘

MCP Tools

53+ tools organized by category:

Category	Tools
Navigation	new_page, navigate, go_back, go_forward, reload
Input	click, type, press_key, hover, scroll, drag, fill, clear, focus, check, uncheck, select_option, upload_file
Observation	take_snapshot, take_enhanced_snapshot, extract_text, extract_links
Screenshots	take_screenshot, save_screenshot
Evaluation	evaluate_script
Pages	list_pages, active_page, close_page, new_hidden_page
Windows	window_list, window_create, window_close, window_activate
Bookmarks	bookmark_list, bookmark_create, bookmark_remove, bookmark_update, bookmark_move, bookmark_search
History	history_search, history_recent, history_delete, history_delete_range
Tab Groups	group_list, group_create, group_update, group_ungroup, group_close
Filesystem	ls, read, write, edit, find, grep, bash
Memory	read_core, update_core, read_soul, update_soul, search_memory, write_memory
DOM	dom, dom_search
Console	get_console_messages
Other	browseros_info, handle_dialog, wait_for, download, export_pdf, output_file, nudges

Agent Loop

The agent loop uses the Vercel AI SDK to orchestrate multi-step browser automation:

• Multi-provider support — OpenAI, Anthropic, Google, Azure, Bedrock, OpenRouter, Ollama, LM Studio, and any OpenAI-compatible endpoint
• Session management — conversations persist in a local SQLite database
• Context overflow handling — automatic message compaction when context windows fill up
• MCP client — connects to external MCP servers for additional tool access (40+ app integrations)
• Tool adapter — bridges MCP tool definitions to AI SDK tool format

Provider Factory

The provider factory (src/agent/provider-factory.ts) creates AI SDK providers from runtime configuration, supporting hot-swapping between providers without restart.

Skills System

Skills are custom instruction sets that shape agent behavior:

• Catalog (src/skills/catalog.ts) — registry of available skills
• Defaults (src/skills/defaults/) — built-in skill definitions
• Loader (src/skills/loader.ts) — loads skills from local and remote sources
• Remote sync (src/skills/remote-sync.ts) — syncs skills from the BrowserOS cloud

Graph Executor (Workflows)

The graph executor (src/graph/executor.ts) runs visual workflow graphs built in the BrowserOS workflow editor. Each node in the graph maps to agent actions, conditionals, or data transformations.

Directory Structure

apps/server/
├── src/
│   ├── index.ts               # Server entry point
│   ├── main.ts                # Server initialization
│   ├── api/                   # HTTP route handlers
│   ├── agent/                 # Agent loop
│   │   ├── ai-sdk-agent.ts    # Main agent implementation
│   │   ├── provider-factory.ts# LLM provider factory
│   │   ├── session-store.ts   # Conversation persistence
│   │   ├── compaction.ts      # Context window management
│   │   ├── mcp-builder.ts     # External MCP client setup
│   │   └── tool-adapter.ts    # MCP → AI SDK tool bridge
│   ├── browser/               # Browser connection layer
│   ├── tools/                 # MCP tool implementations
│   │   ├── navigation.ts
│   │   ├── input.ts
│   │   ├── snapshot.ts
│   │   ├── memory/
│   │   ├── filesystem/
│   │   └── ...
│   ├── skills/                # Skills system
│   ├── graph/                 # Workflow graph executor
│   ├── lib/                   # Shared utilities
│   └── rpc.ts                 # JSON-RPC type definitions
├── tests/
│   ├── tools/                 # Tool-level tests
│   ├── sdk/                   # SDK integration tests
│   └── server.integration.test.ts
├── graph/                     # Workflow graph definitions
└── package.json

Development

Prerequisites

• Bun runtime
• A running BrowserOS instance (for CDP connectivity)

Setup

# Copy environment files
cp .env.example .env.development

# Start the server (with hot reload)
bun run start

See the agent monorepo README for full environment variable reference and process-compose setup.

Testing

bun run test:tools          # Tool-level tests
bun run test:integration    # Full integration tests (requires running BrowserOS)
bun run test:sdk            # SDK integration tests

Building

# Build cross-platform server binaries
bun run build

# Build for specific targets
bun scripts/build/server.ts --target=darwin-arm64,linux-x64

# Build without uploading to R2
bun scripts/build/server.ts --target=all --no-upload

Ports

Port	Env Variable	Purpose
9100	BROWSEROS_SERVER_PORT	HTTP server (MCP, chat, health)
9000	BROWSEROS_CDP_PORT	Chromium CDP (server connects as client)
9300	BROWSEROS_EXTENSION_PORT	Legacy BrowserOS launch arg kept for compatibility