How to Use the LambdaTest MCP in Mastra AI

Q: How do I build a retry loop for failed LambdaTest runs using Mastra AI?

Use getsessiondetails to check the status, then write a conditional step in your workflow. If the status is failed, the agent triggers a retry and uses updatesessionstatus to update the log.

Q: Can Mastra AI agents automatically query the LambdaTest platform matrix?

Yes, the agent calls listsupportedplatforms to find valid OS and browser versions. This ensures your self-healing workflows only select active configurations when spinning up new test sessions.

Q: Can I require human approval before updating a session status using the MCP Server?

Yes, you can configure Mastra AI to pause before running updatesessionstatus. The workflow waits for a manual override in your Slack or terminal before marking a test as passed.

Run self-healing browser test workflows by connecting Mastra AI agents directly to the LambdaTest grid.

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Setup LambdaTest with Mastra AI

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Automated pipeline recovery with Mastra AI

`list_automation_builds` retrieves the current state of your CI pipeline so Mastra AI can monitor for failures. If a build fails, the agent automatically triggers a diagnostic run to isolate the broken environment. By using conditional branching, the Mastra AI agent queries this MCP Server to retry the failed tests on alternative configurations. You don't have to manually restart pipelines because the agent handles the recovery logic.

Self-healing test runs via this MCP Server

`get_session_details` extracts the exact error code and screenshot metadata from a broken browser run. The Mastra AI agent analyzes this payload to determine if the failure was a network flake or a real code bug. If it detects a temporary environment issue, the system uses `update_session_status` to reset the run. This automated loop prevents false alarms from blocking your deployment queue.

Deep log analysis and error classification

`get_test_logs` fetches the raw console output from your remote browser sessions for immediate analysis. Mastra AI processes these logs through its workflow steps, categorizing errors by severity. The system then routes the parsed logs to the responsible team. This eliminates the need for QA engineers to manually dig through thousands of lines of terminal output.

Setup guide

Set up LambdaTest MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All LambdaTest tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "lambdatest-mcp-client",
  servers: {
    "lambdatest-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "LambdaTest Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to LambdaTest tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent LambdaTest transactions"
);
console.log(result.text);

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Common questions about LambdaTest MCP in Mastra AI

Use `get_session_details` to check the status, then write a conditional step in your workflow. If the status is failed, the agent triggers a retry and uses `update_session_status` to update the log.

Yes, the agent calls `list_supported_platforms` to find valid OS and browser versions. This ensures your self-healing workflows only select active configurations when spinning up new test sessions.

The server runs in a dedicated V8 sandbox on Vinkius, which handles connection pooling. Mastra AI can execute concurrent calls to `list_test_sessions` without overloading your API limits.

Yes, you can configure Mastra AI to pause before running `update_session_status`. The workflow waits for a manual override in your Slack or terminal before marking a test as passed.

No, credentials and session logs are processed in memory by the MCP Server and never stored. All communication between your agent and the cloud grid is encrypted in transit and wiped immediately after execution.

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