How to Use the Browserbase MCP in LangChain
Chain together Browserbase sessions in LangChain to automate browser tasks without managing infrastructure.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Browserbase MCP to LangChain
Create your Vinkius account to connect Browserbase to LangChain and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Launch cloud browsers from LangChain chains
Trigger `create_browser_session` directly within your agent logic to spin up isolated Chromium instances. This keeps your local machine free of heavy browser binaries while the server handles the heavy lifting. You gain a CDP WebSocket URL instantly. Plug this into your existing automation scripts to navigate, click, or scrape content as part of a larger LangGraph workflow.
Manage active sessions inside LangChain
Use `list_browser_sessions` to keep track of every instance running under your account. You can filter by status to see which jobs are still active or which hit an error state. This visibility prevents resource leaks. If a chain hangs, you can use `get_browser_session` to inspect the state before deciding to clean up.
Kill stuck processes using LangChain tools
Invoke `stop_browser_session` when your agent finishes its task or hits a timeout. This immediately halts the remote instance and clears out the memory. It ensures you aren't paying for idle time. Since LangChain handles the tool execution, you can wrap this call in a finally block to guarantee cleanup every time.
Set up Browserbase MCP in LangChain
Prerequisites
- Python 3.10+ installed
-
langchain-mcp-adapters+langgraphpackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChainBaseToolobjects. - 2
Connect via HTTP transport
Use
MultiServerMCPClientwith"transport": "http"pointing to your Vinkius endpoint. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. - 3
Create a ReAct agent
Pass the discovered tools to
create_react_agent()from LangGraph. The agent automatically routes Browserbase tool calls through the MCP protocol. - 4
Run with any LLM
Swap
ChatOpenAIforChatAnthropic,ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.
from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI
async with MultiServerMCPClient({
"browserbase-mcp": {
"transport": "http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
result = await agent.ainvoke({
"messages": "List recent Browserbase transactions"
})
print(result["messages"][-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Browserbase. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
Why Choose Vinkius
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Real-time monitoring
Live
visibility into every interaction
Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.
Built-in savings
60%
lower AI costs
Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.
Single dashboard
One
place for every integration
Every tool your AI connects to, managed from a single screen. One account, complete control.
Common questions about Browserbase MCP in LangChain
Use it with your favorite AI tools
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