Browserbase MCP Server for LlamaIndex 4 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Browserbase as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Browserbase. "
"You have 4 tools available."
),
)
response = await agent.run(
"What tools are available in Browserbase?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Browserbase MCP Server
Connect your AI agent to Browserbase — the serverless platform for running headless cloud browsers at scale.
LlamaIndex agents combine Browserbase tool responses with indexed documents for comprehensive, grounded answers. Connect 4 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Create Sessions — Spin up isolated Chromium browser sessions in the cloud. Each session returns a CDP (Chrome DevTools Protocol) WebSocket URL for connecting Playwright, Puppeteer, or Selenium
- List Sessions — Monitor all active, completed, or errored browser sessions across your account
- Get Session Details — Check status, connection URLs, pages visited, and duration of any session
- Stop Sessions — Terminate running sessions to free resources
The Browserbase MCP Server exposes 4 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Browserbase to LlamaIndex via MCP
Follow these steps to integrate the Browserbase MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 4 tools from Browserbase
Why Use LlamaIndex with the Browserbase MCP Server
LlamaIndex provides unique advantages when paired with Browserbase through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Browserbase tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Browserbase tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Browserbase, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Browserbase tools were called, what data was returned, and how it influenced the final answer
Browserbase + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Browserbase MCP Server delivers measurable value.
Hybrid search: combine Browserbase real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Browserbase to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Browserbase for fresh data
Analytical workflows: chain Browserbase queries with LlamaIndex's data connectors to build multi-source analytical reports
Browserbase MCP Tools for LlamaIndex (4)
These 4 tools become available when you connect Browserbase to LlamaIndex via MCP:
create_browser_session
The session provides a connectUrl (CDP WebSocket) that can be used with Playwright, Puppeteer, or Selenium to control the browser programmatically. Default timeout is 300 seconds. Create a new cloud browser session. Returns a CDP WebSocket URL for connecting automation frameworks like Playwright or Puppeteer
get_browser_session
Useful for monitoring active sessions. Get details of a specific browser session by its ID
list_browser_sessions
Filter by status: RUNNING, COMPLETED, ERROR. List all active browser sessions in your Browserbase account
stop_browser_session
Any unsaved state in the browser is lost. Stop a running browser session by its ID
Example Prompts for Browserbase in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Browserbase immediately.
"Create a new browser session so I can automate a login flow."
"Show me all my running browser sessions."
"Stop browser session sess_abc123."
Troubleshooting Browserbase MCP Server with LlamaIndex
Common issues when connecting Browserbase to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpBrowserbase + LlamaIndex FAQ
Common questions about integrating Browserbase MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Browserbase with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Browserbase to LlamaIndex
Get your token, paste the configuration, and start using 4 tools in under 2 minutes. No API key management needed.