Can I trigger a browser task with a different starting URL?

Yes! Use the `run_task` tool and provide the Task ID. In the `overrides` field, you can pass a JSON object like `{"url": "https://newsite.com"}` to change the starting point dynamically.

How do I see the screenshot captured by a task?

Simply ask the agent to `get_run` and provide the Run ID. Once the status is 'finished', the response will include a `screenshot_url` that you can click to view the image.

Does the integration allow taking a quick screenshot without a saved task?

Yes. Use the `take_screenshot` action and provide the URL. It will create a simplified run that captures the page and returns the result URL once processed.

Browserbear MCP Server for LlamaIndex 10 tools — connect in under 2 minutes

Name: Browserbear
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Browserbear as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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 Browserbear. "
            "You have 10 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Browserbear?"
    )
    print(response)

asyncio.run(main())

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* 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 Browserbear MCP Server

Connect your Browserbear (Roborabbit) account to any AI agent and orchestrate your browser automation, web scraping, and visual monitoring workflows through natural conversation.

LlamaIndex agents combine Browserbear tool responses with indexed documents for comprehensive, grounded answers. Connect 10 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

Task Oversight — List and retrieve detailed metadata for all your saved browser automation tasks.
Automation Execution — Trigger task runs with dynamic overrides (like URL or form data) and monitor their progress.
Visual Captures — Take high-quality screenshots of any URL with customizable dimensions and wait times.
Data Extraction — Retrieve scraped structured data and screenshot URLs directly into your workspace.
Run Management — List, inspect, and delete history of your automation runs.
Project Coordination — Access and organize your tasks across multiple projects and track account usage.

The Browserbear 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 Browserbear to LlamaIndex via MCP

Follow these steps to integrate the Browserbear 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 Browserbear

Why Use LlamaIndex with the Browserbear MCP Server

LlamaIndex provides unique advantages when paired with Browserbear through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Browserbear tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Browserbear tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Browserbear, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Browserbear tools were called, what data was returned, and how it influenced the final answer

Browserbear + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Browserbear MCP Server delivers measurable value.

Hybrid search: combine Browserbear real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Browserbear 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 Browserbear for fresh data

Analytical workflows: chain Browserbear queries with LlamaIndex's data connectors to build multi-source analytical reports

Browserbear MCP Tools for LlamaIndex (10)

These 10 tools become available when you connect Browserbear to LlamaIndex via MCP:

create_task

Create a new browser automation task

delete_run

Delete a task run record

get_account_usage

Retrieve account usage statistics

get_run

Get status and results of a task run

get_task

Get details of a specific task

list_projects

List all projects in the account

list_runs

List all task runs

list_tasks

List all browser automation tasks

run_task

Trigger a run for a specific task

take_screenshot

Take a quick screenshot of a URL

Example Prompts for Browserbear in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Browserbear immediately.

"List all my browser automation tasks."

"Take a screenshot of https://vinkius.com at 1280x800 resolution."

"Run task task_123 and override the starting URL to https://google.com."

Troubleshooting Browserbear MCP Server with LlamaIndex

Common issues when connecting Browserbear to LlamaIndex through the Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Browserbear + LlamaIndex FAQ

Common questions about integrating Browserbear MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Browserbear tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.