Hyperbrowser (Web Infra for AI) MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Hyperbrowser (Web Infra for AI) as an MCP tool provider through the 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 Hyperbrowser (Web Infra for AI). "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Hyperbrowser (Web Infra for AI)?"
)
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 Hyperbrowser (Web Infra for AI) MCP Server
Connect your Hyperbrowser account to any AI agent and take full control of your web automation and cloud browser infrastructure through natural conversation.
LlamaIndex agents combine Hyperbrowser (Web Infra for AI) tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through the 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
- Managed Sessions — Create and manage remote headless browser sessions with built-in support for proxies, stealth mode, and specific browser versions
- AI Scraping — Trigger asynchronous scraping jobs that handle dynamic loading, retries, and CAPTCHAs automatically to retrieve clean HTML payloads
- Data Extraction — Use LLM-powered capabilities to extract structured data from any URL by simply providing a natural language prompt and optional JSON schema
- Visual Capture — Capture full-page screenshots of any rendered URL to audit visual changes or document web states accurately
- Remote Scripts — Execute custom JavaScript within active browser sessions to perform complex interactions or evaluate page states in real-time
- DOM Access — Retrieve raw, rendered HTML synchronously to process page content without managing complex scraping infrastructures
The Hyperbrowser (Web Infra for AI) MCP Server exposes 10 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 Hyperbrowser (Web Infra for AI) to LlamaIndex via MCP
Follow these steps to integrate the Hyperbrowser (Web Infra for AI) 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 10 tools from Hyperbrowser (Web Infra for AI)
Why Use LlamaIndex with the Hyperbrowser (Web Infra for AI) MCP Server
LlamaIndex provides unique advantages when paired with Hyperbrowser (Web Infra for AI) through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Hyperbrowser (Web Infra for AI) tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Hyperbrowser (Web Infra for AI) tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Hyperbrowser (Web Infra for AI), a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Hyperbrowser (Web Infra for AI) tools were called, what data was returned, and how it influenced the final answer
Hyperbrowser (Web Infra for AI) + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Hyperbrowser (Web Infra for AI) MCP Server delivers measurable value.
Hybrid search: combine Hyperbrowser (Web Infra for AI) real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Hyperbrowser (Web Infra for AI) 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 Hyperbrowser (Web Infra for AI) for fresh data
Analytical workflows: chain Hyperbrowser (Web Infra for AI) queries with LlamaIndex's data connectors to build multi-source analytical reports
Hyperbrowser (Web Infra for AI) MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Hyperbrowser (Web Infra for AI) to LlamaIndex via MCP:
create_session
Returns a connection URL and session details. Pass optional JSON config for proxy, stealth, browser version, etc. Create a new Hyperbrowser remote session
extract_data
g., "Extract product name and price"). Optionally pass JSON schema. The platform will render, extract, and return clean JSON. Use Hyperbrowser LLM capabilities to extract structured data
get_scrape_job
When status is completed, the response will contain the HTML payload and metadata. Get status/results of a Hyperbrowser scraping job
get_session
Returns duration, connection endpoints, and current health/status. Get status of a specific Hyperbrowser session
list_sessions
Pass optional status (active, completed, failed) to filter. List active or past Hyperbrowser sessions
page_content
Get raw HTML content synchronously via Hyperbrowser
page_screenshot
Returns image metadata or URL. Take a managed screenshot via Hyperbrowser
run_script
The browser will execute and return the evaluation result. Execute JS script inside a running Hyperbrowser session
start_scrape
Returns a job ID. Use get_scrape_job to poll for completion. Pass target URL and optional JSON config. Start a Hyperbrowser async scraping job
stop_session
Terminate an active Hyperbrowser session
Example Prompts for Hyperbrowser (Web Infra for AI) in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Hyperbrowser (Web Infra for AI) immediately.
"Extract the latest pricing and features from 'https://example.com/pricing'"
"Take a full-page screenshot of 'https://news.ycombinator.com'"
"List all my active Hyperbrowser sessions"
Troubleshooting Hyperbrowser (Web Infra for AI) MCP Server with LlamaIndex
Common issues when connecting Hyperbrowser (Web Infra for AI) to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpHyperbrowser (Web Infra for AI) + LlamaIndex FAQ
Common questions about integrating Hyperbrowser (Web Infra for AI) 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 Hyperbrowser (Web Infra for AI) 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 Hyperbrowser (Web Infra for AI) to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.