How to Use the Browse AI MCP in Mastra AI

Q: How does Mastra AI handle failed Browse AI extractions?

Your workflow can catch errors from triggerrobotrun and use Mastra's built-in retry engine. It will automatically attempt the scrape again without crash-stopping your entire agent pipeline.

Q: Can I schedule recurring Browse AI monitors using Mastra AI?

Yes, your agent can call createmonitor to schedule periodic scraping tasks. You can manage these schedules directly inside your workflow code.

Q: How do I check my Browse AI scraper list inside Mastra AI?

You use the listrobots tool provided by this MCP Server to fetch all available scrapers. Your agent can then loop through them to find the one matching your workflow's current target site.

Q: Can I require human approval before starting a scraping run?

Yes. You can configure Mastra's tool approval feature on triggerrobotrun. This pauses the workflow and waits for a manual confirmation before the scraper actually starts.

Build resilient, self-healing web scraping workflows with Mastra AI and the Browse AI integration.

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Connect Browse AI MCP to Mastra AI

Create your Vinkius account to connect Browse AI to Mastra AI 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 Browse AI with Mastra AI

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Resilient Extraction Workflows in Mastra AI

Build multi-step workflows that automatically retry failed extractions. If a scraping job fails, your Mastra agent catches the error, waits, and uses `trigger_robot_run` to try again with exponential backoff. You can program the workflow to monitor the progress by calling `get_run_status`. If the job takes too long, the workflow can branch to notify your team before trying a different scraper.

Automated Scraping Monitor Management

Let your agent manage your tracking schedules dynamically. By calling `create_monitor`, your workflow can set up new monitoring schedules based on user behavior or external triggers. The agent can audit active schedules using `list_active_monitors` using this MCP Server to ensure you aren't running redundant tasks. This keeps your operating costs low without manual oversight.

Dynamic Webhook Routing with MCP Server

Link your scraping events directly to your backend pipelines. Your agent can configure webhooks by calling `list_robot_webhooks` to see where data is currently being sent. If a webhook is outdated or pointing to a dead endpoint, the agent cleans it up using `remove_webhook`. This keeps your data pipelines clean and prevents broken network requests.

Setup guide

Set up Browse AI 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 Browse AI 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: "browse-ai-alternative-mcp-client",
  servers: {
    "browse-ai-alternative-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Browse AI. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

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Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Browse AI MCP in Mastra AI

Your workflow can catch errors from `trigger_robot_run` and use Mastra's built-in retry engine. It will automatically attempt the scrape again without crash-stopping your entire agent pipeline.

Yes, your agent can call `create_monitor` to schedule periodic scraping tasks. You can manage these schedules directly inside your workflow code.

You use the `list_robots` tool provided by this MCP Server to fetch all available scrapers. Your agent can then loop through them to find the one matching your workflow's current target site.

Yes. You can configure Mastra's tool approval feature on `trigger_robot_run`. This pauses the workflow and waits for a manual confirmation before the scraper actually starts.

Vinkius processes all requests through isolated, zero-trust containers. Your robot configurations and scraped payloads are decrypted only in memory during the execution phase, ensuring no data leaks to third parties.

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