agent-browser-agent 0.1.1

Agent-ready tools and LangGraph integrations for vercel-agent-browser

agent-browser-agent

An agent-facing layer over vercel-agent-browser, the typed Python wrapper for Vercel's agent-browser CLI.

It turns the wrapper's complete, versioned CLI inventory into LLM-friendly StructuredTool objects and adds composed workflows that reduce browser tasks to fewer model turns. Tools can be used directly, passed to LangChain, placed in a LangGraph ToolNode, or assembled into a Deep Agent.

What is exposed

The default maximum-control profile provides 167 tools:

• all 151 commands in the agent-browser 0.31.1 inventory;
• the runtime addinitscript command and Python navigate alias;
• JSON, text, and typed-method escape hatches for forward compatibility;
• 11 composed workflows for inspection, forms, resilient clicks, diagnostics, downloads, screenshots, login, and isolated sessions.

Every tool has a generated JSON schema based on the native Python method signature, synchronous and asynchronous execution, structured recoverable errors, output limiting, and stable agent_browser_* names.

Install

Install the Vercel CLI and Chrome runtime once:

npm install -g agent-browser
agent-browser install

Install agent-browser-agent from PyPI:

pip install agent-browser-agent

Add the integration you need:

pip install "agent-browser-agent[langgraph,openai]"
# or
pip install "agent-browser-agent[deepagents,openai]"

Use the tools directly

from agent_browser_agent import AgentBrowserToolkit

toolkit = AgentBrowserToolkit()

result = toolkit.get_tool("agent_browser_open_and_inspect").invoke(
    {"url": "https://example.com"}
)
print(result)

# All tools also support ainvoke().
snapshot = await toolkit.get_tool("agent_browser_snapshot").ainvoke(
    {"interactive": True, "include_urls": True}
)

The underlying browser daemon persists between calls. Use one toolkit per agent/session, or create an isolated clone:

research = toolkit.for_session("research", namespace="my-app")

LangGraph agent

from agent_browser import AgentBrowser, ClientConfig, GlobalOptions
from agent_browser_agent import (
    AgentBrowserToolkit,
    AgentBrowserToolkitConfig,
    create_agent_browser_langgraph_agent,
)

browser = AgentBrowser(
    ClientConfig(
        timeout=60,
        options=GlobalOptions(
            session="research",
            namespace="my-app",
            headed=False,
            allowed_domains=("example.com", "*.example.com"),
        ),
    )
)

toolkit = AgentBrowserToolkit(
    browser,
    AgentBrowserToolkitConfig(access="browser", include_raw_commands=False),
)

agent = create_agent_browser_langgraph_agent(
    "openai:gpt-5.2",
    toolkit=toolkit,
    confirm_dangerous=True,
)

result = agent.invoke(
    {"messages": [{"role": "user", "content": "Inspect example.com."}]},
    config={"configurable": {"thread_id": "browser-1"}},
)

For a custom Graph API workflow:

from agent_browser_agent import create_agent_browser_tool_node

tool_node = create_agent_browser_tool_node(toolkit=toolkit)

Deep Agent

from agent_browser_agent import create_agent_browser_deep_agent

agent = create_agent_browser_deep_agent(
    model="openai:gpt-5.2",
    toolkit=toolkit,
    confirm_dangerous=True,
)

Additional options such as checkpointer, store, backend, subagents, skills, memory, and response_format are forwarded to deepagents.create_deep_agent.

Access control

Maximum control is the default:

AgentBrowserToolkitConfig(access="all")

This includes install, upgrade, plugin mutation, saved-state mutation, and raw command tools. For normal web automation use:

AgentBrowserToolkitConfig(
    access="browser",
    include_raw_commands=False,
)

Fine-grained policy is available with allowed_tools and denied_tools. recommended_interrupts() returns the host-mutating tools that should require human approval in agent runtimes.

Composed tools

• agent_browser_open_and_inspect
• agent_browser_call_and_inspect
• agent_browser_run_workflow
• agent_browser_page_context
• agent_browser_fill_form
• agent_browser_smart_click
• agent_browser_screenshot_and_snapshot
• agent_browser_download_and_verify
• agent_browser_login_and_inspect
• agent_browser_diagnose
• agent_browser_session_workflow

Use primitive tools when the model must inspect an intermediate result. Use a composed tool for deterministic steps that should happen together.

Safety notes

• No tool invokes a shell. Raw commands accept argument arrays and optional stdin.
• Prefer access="browser" and allowed_domains for untrusted tasks.
• Snapshot refs become stale after navigation or large DOM changes; take a new snapshot before retrying.
• Credentials passed as LLM tool arguments may appear in model traces. Prefer saved agent-browser auth profiles.
• Host paths returned for downloads, screenshots, PDFs, traces, or recordings refer to the machine running agent-browser.