Applitools 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 Applitools 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 Applitools. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Applitools?"
)
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 Applitools MCP Server
Connect your Applitools Eyes testing suite to your AI agent and manage your entire visual regression pipeline without opening the dashboard. Allow your agent to spot UI changes, validate baselines, and assess testing health dynamically.
LlamaIndex agents combine Applitools 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
- Batch Observability — Query active test batches to view aggregated statuses (Passed, Failed, Unresolved) and completion rates
- Session & Results analysis — Drill down into specific test sessions to examine failed step images, match levels, and browser differences
- Baseline Management — List your "golden" graphical baselines bound to applications or specific Git branches
- Actionable Maintenance — Authorize the agent to delete outdated baselines or discard legacy batches to keep your workspace clean
- Key Validation — Ensure connectivity against your visual AI engine before pipeline triggers
The Applitools 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 Applitools to LlamaIndex via MCP
Follow these steps to integrate the Applitools 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 Applitools
Why Use LlamaIndex with the Applitools MCP Server
LlamaIndex provides unique advantages when paired with Applitools through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Applitools tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Applitools tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Applitools, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Applitools tools were called, what data was returned, and how it influenced the final answer
Applitools + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Applitools MCP Server delivers measurable value.
Hybrid search: combine Applitools real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Applitools 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 Applitools for fresh data
Analytical workflows: chain Applitools queries with LlamaIndex's data connectors to build multi-source analytical reports
Applitools MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Applitools to LlamaIndex via MCP:
delete_baseline
Use when a baseline is outdated or a page has been redesigned. Delete an Applitools test baseline
delete_batch
Does NOT affect baselines. Use with caution — this is irreversible. Delete an Applitools test batch
get_batch
Use batch ID from list_batches. Get full details of an Applitools batch
get_batch_stats
Returns passed/failed/unresolved/new counts without full test data. Get summary statistics for an Applitools batch
get_session
Provide batch ID and session ID. Get details of a test session within an Applitools batch
list_baselines
Returns baseline IDs, names, and env configs. Filter by app name. List visual baselines for an app on Applitools
list_batches
Batches group related test sessions. Returns batch IDs, names, statuses (Passed/Unresolved/Failed), and test counts. Each batch has a unique ID used to query its results. List all test batches on Applitools Eyes
list_branch_baselines
Use to inspect branch-specific visual states. List baselines for a specific branch on Applitools
list_results
List all test results in an Applitools batch
validate_key
Use to verify connectivity before running tests. Validate the Applitools API key
Example Prompts for Applitools in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Applitools immediately.
"List the most recent visual test batches in Applitools."
"Get me the exact session results for our unresolved batch ID b_991x."
"List the baselines assigned specifically to fixing the 'feature/dark-mode-header' branch."
Troubleshooting Applitools MCP Server with LlamaIndex
Common issues when connecting Applitools to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpApplitools + LlamaIndex FAQ
Common questions about integrating Applitools 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 Applitools 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 Applitools to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.