BrowserStack 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 BrowserStack as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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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 BrowserStack. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in BrowserStack?"
)
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 BrowserStack MCP Server
Connect your BrowserStack Automate account to any AI agent and take full control of your automated cross-browser testing pipeline through natural conversation.
LlamaIndex agents combine BrowserStack 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
- Project Management — List all test projects and drill down into specific project details
- Build Tracking — Surface your recent automation builds, their statuses (running, failed, passed), and duration
- Session Deep Dive — Retrieve the granular executions of a specific test session, including OS and browser stats
- Log Extraction — Automatically dump and analyze the raw Selenium/Appium logs of a failed session
- Quota & Plan — View your current plan's parallel session usage and testing queue length
- Environment Specs — List all supported OS/browser combinations required to configure your capabilities
The BrowserStack 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 BrowserStack to LlamaIndex via MCP
Follow these steps to integrate the BrowserStack 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 BrowserStack
Why Use LlamaIndex with the BrowserStack MCP Server
LlamaIndex provides unique advantages when paired with BrowserStack through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine BrowserStack tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain BrowserStack tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query BrowserStack, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what BrowserStack tools were called, what data was returned, and how it influenced the final answer
BrowserStack + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the BrowserStack MCP Server delivers measurable value.
Hybrid search: combine BrowserStack real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query BrowserStack 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 BrowserStack for fresh data
Analytical workflows: chain BrowserStack queries with LlamaIndex's data connectors to build multi-source analytical reports
BrowserStack MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect BrowserStack to LlamaIndex via MCP:
delete_build
json`. Delete a BrowserStack build by ID
delete_session
json`. Delete a BrowserStack session by ID
get_build
json`. Returns session details, OS/browser combos, results, and logs. Get all sessions within a BrowserStack automation build
get_plan
json`, including parallel sessions allowed, team parallel sessions used, queued sessions, and plan name. Essential for managing execution concurrency. Get current BrowserStack plan details and parallel session usage
get_project
json`. This includes name, group ID, and recent builds associated with the project. Get full details of a BrowserStack project including linked builds
get_session
json`. Includes name, OS, browser, status, reason, duration, video URL, and log URLs. Get full details of a specific BrowserStack session
get_session_logs
Useful for debugging failed test steps. Get text execution logs of a BrowserStack session
list_browsers
json`. Returns OS names/versions, browser names/versions required for configuring automation desired capabilities. List all supported OS/browser combinations on BrowserStack
list_builds
json`. Returns build names, IDs, statuses (running/done/timeout/failed), durations, and session counts. Useful for tracking test suite execution. List recent builds on BrowserStack Automate
list_projects
json`. Returns project names, IDs, and build counts. Used to organize automation runs. List all projects on BrowserStack Automate
Example Prompts for BrowserStack in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with BrowserStack immediately.
"List my recent automation builds and summarize their outcomes."
"Fetch the logs for the failed session in build e4da3b."
"Check how many parallel sessions our current plan allows."
Troubleshooting BrowserStack MCP Server with LlamaIndex
Common issues when connecting BrowserStack to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpBrowserStack + LlamaIndex FAQ
Common questions about integrating BrowserStack 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 BrowserStack 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 BrowserStack to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.