How to Use the LambdaTest MCP in LlamaIndex

Q: What happens if LambdaTest updates their platform list?

Your agent re-runs listsupportedplatforms to refresh the index. This keeps your knowledge base current with the latest device additions.

Index your LambdaTest results into a searchable knowledge base using LlamaIndex for intelligent testing insights.

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Connect LambdaTest MCP to LlamaIndex

Create your Vinkius account to connect LambdaTest 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 LambdaTest with LlamaIndex

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Index test results for semantic search

Turn your historical test data into a searchable index. By calling `list_automation_builds` and `list_test_sessions`, you populate your vector store with live API data. This makes your past test runs queryable. You can ask your agent about patterns in test failures across different browser versions supported by the platform.

Query platform compatibility across projects

Use `list_supported_platforms` to ground your agent's knowledge in real device availability. It helps you verify if a specific environment is available before running a test. Your agent avoids hallucinations by checking the live device list. It understands exactly what hardware is ready for your next suite.

Retrieve diagnostic logs into your index

Fetch execution logs with `get_test_logs` and store them directly in your knowledge base. This allows for semantic lookups of past error messages. When a new test fails, the agent searches for similar logs from the past. It finds the solution based on historical data rather than guessing.

Setup guide

Set up LambdaTest 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 LambdaTest 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 LambdaTest tools.",
)
response = await agent.run("List recent LambdaTest data")

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Common questions about LambdaTest MCP in LlamaIndex

It fetches test metadata and logs, then vectorizes them. This allows you to ask natural language questions about your testing history.

Yes, you can index data from various builds and sessions. Your agent treats the entire history as a single, searchable knowledge base.

Your test logs are processed locally within your index. The data remains under your control and is not shared with any external parties.

You use the tool arguments to fetch specific build IDs. This ensures only relevant data enters your knowledge base.

Your agent re-runs `list_supported_platforms` to refresh the index. This keeps your knowledge base current with the latest device additions.

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