How to Use the Veraset MCP in Mastra AI

Q: Can I verify dataset definitions for Veraset with Mastra AI?

Yes. Use getdatasetschema to retrieve full column definitions and data types. This is key for building reliable, typed workflows within the agent's state.

Q: What happens if a multi-step Veraset process gets stuck? (Mastra AI)

If an active query stalls, your workflow can invoke getquerystatus to monitor progress. If it hits a wall, you or the agent can manually stop it using cancelrunningquery.

Q: Does Mastra AI support listing available datasets in Veraset?

It does. The agent uses listmobilitydatasets to get a comprehensive list of all accessible mobility data sources before attempting any query execution.

Q: If I need raw files from Veraset, what mechanism should Mastra AI use?

The system provides generatedownloadlink. This tool creates a temporary pre-signed URL for an S3 file download, which is perfect for passing to external systems.

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Connect Veraset MCP to Mastra AI

Create your Vinkius account to connect Veraset 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 Veraset with Mastra AI

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Reliable SQL Execution and Retries

Run complex queries against mobility datasets, knowing that the workflow engine handles failure. If a query fails, your agent can automatically retry the task with exponential backoff. Start by calling `execute_sql_query` to get a unique ID, then let Mastra AI manage the execution and status checks via `get_query_status`.

Multi-Step Data Processing

Your agent can build complex workflows that check data availability before acting. It first calls `list_mobility_datasets` to see what's there, then checks the schema using `get_dataset_schema`. This sequential approach guarantees that each step—like getting a sample with `get_dataset_sample`—has the necessary inputs.

Controlled Data Output

You're in charge of how data leaves Veraset. Your agent can decide if it needs to retrieve results using `get_query_results`, or if a dedicated download link is better via `generate_download_link`. The system also allows for manually canceling tasks with `cancel_running_query` when a step fails and needs correction.

Setup guide

Set up Veraset 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 Veraset 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: "veraset-mcp-client",
  servers: {
    "veraset-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

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

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Common questions about Veraset MCP in Mastra AI

The agent framework handles failure gracefully. If an SQL query fails, it automatically retries the task using exponential backoff before notifying you that a human needs to step in.

Yes. Use `get_dataset_schema` to retrieve full column definitions and data types. This is key for building reliable, typed workflows within the agent's state.

If an active query stalls, your workflow can invoke `get_query_status` to monitor progress. If it hits a wall, you or the agent can manually stop it using `cancel_running_query`.

It does. The agent uses `list_mobility_datasets` to get a comprehensive list of all accessible mobility data sources before attempting any query execution.

The system provides `generate_download_link`. This tool creates a temporary pre-signed URL for an S3 file download, which is perfect for passing to external systems.

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