How to Use the Applitools MCP in LlamaIndex

Q: Can I search through my visual baselines?

Yes. You run listbaselines and index the returned names and environment configs. Then you just ask your agent which baselines exist for a specific app.

Q: What happens when I delete a batch?

Calling deletebatch removes the test batch permanently. It does not affect your baselines, but you lose the historical record of those specific test runs.

Index your visual test results and query UI baselines using LlamaIndex.

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Connect Applitools MCP to LlamaIndex

Create your Vinkius account to connect Applitools to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Applitools with LlamaIndex

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Query the Applitools MCP Server

LlamaIndex turns your visual test history into a searchable knowledge base. Instead of just fetching data, your agent indexes the output from `list_batches` directly into a vector store. You ask questions about past UI regressions and get answers grounded in real API data. This approach eliminates hallucinations about your test status. When you ask why a specific build failed, the agent retrieves the exact failed counts from `get_batch_stats` and cross-references them with indexed historical data. You get facts, not guesses.

Build RAG apps for visual testing

Combine live API data with your internal documentation. Your RAG application pulls branch-specific visual states using `list_branch_baselines` and compares them against your design system guidelines. The agent reads both sources to evaluate the UI changes. Developers create unified indexes that track visual drift over time. By regularly calling `list_results` and storing the output, you build a historical record of every UI diff. Your application then answers complex queries about which components break most often.

Inspect session context

Finding the root cause of a visual bug requires context. Your agent uses `get_session` to pull deep details about a specific test run and adds that information to the working index. It maps the session ID to the exact environment configuration. You avoid clicking through dashboards to find what went wrong. The agent calls `validate_key` to check connectivity, then pulls the full session data to explain the failure. It synthesizes the technical details into a readable summary.

Setup guide

Set up Applitools MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Applitools MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Applitools tools.",
)
response = await agent.run("List recent Applitools data")

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Common questions about Applitools MCP in LlamaIndex

Install llama-index-tools-mcp and initialize BasicMCPClient. Wrap it in McpToolSpec and pass the async tool list to your FunctionAgent.

Yes. You run `list_baselines` and index the returned names and environment configs. Then you just ask your agent which baselines exist for a specific app.

Calling `delete_batch` removes the test batch permanently. It does not affect your baselines, but you lose the historical record of those specific test runs.

It lets you build semantic search over your UI testing history. You ask natural language questions about past visual bugs and get answers based on indexed API responses.

Branch configurations and batch statistics remain completely private. The Vinkius MCP infrastructure relies on zero-trust architecture, ensuring your test run details only exist during the active query execution before being wiped.

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