How to Use the Wolai MCP in Mastra AI

Q: How do I check the schema for Wolai databases using Mastra AI?

You run getdatabase as the first step in your workflow. This ensures that every subsequent action, like querying or creating a row, knows exactly what data format it needs to follow.

Q: Does Mastra AI handle multiple Wolai pages for me?

Yes. You can build a loop that uses listpages and then runs a separate step inside the loop for every page, executing actions like calling getpage on each one sequentially.

Q: What if my Wolai database query fails? Can Mastra AI help?

Absolutely. You wrap your querydatabase call in a multi-step workflow block. If it fails (e.g., timeout), the system retries with exponential backoff, giving you resilience.

Q: Is listing users reliable when using Mastra AI?

The listusers tool is built for reliability within a workflow engine. It provides an authoritative list of all workspace members, which your agent can then use to validate permissions before making changes.

Build resilient workflows with Mastra AI that manage Wolai content automatically.

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Connect Wolai MCP to Mastra AI

Create your Vinkius account to connect Wolai 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 Wolai with Mastra AI

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Perplexity

Complex Workflow Management with MCP Server

To build a complex data pipeline, your agent can use `get_database` to check the required schema first. If the structure is wrong, it knows to trigger an alert instead of failing. This conditional logic handles failures gracefully. When updating content, the workflow can call `create_page`, and if that fails due to permissions, Mastra AI's built-in retries handle the backoff automatically before notifying a human.

Automated Wolai Content Updates with Mastra AI

You can build a multi-step process using `create_database_row`. For instance, first check if user data exists via `query_database`, and *only* if it doesn't, then create the row. This conditional branching prevents redundant writes. Another workflow could use `list_users` to validate who should receive a page update before calling `create_page`.

Robust Wolai Information Retrieval with Mastra AI

If you need data from multiple sources, your agent runs a sequence: it first calls `get_workspace_info`, then uses `list_databases` to narrow down the scope. This sequential approach ensures all necessary context is gathered before querying. The workflow can use `list_blocks` on a page and if certain blocks are missing, trigger an escalation path rather than just failing.

Setup guide

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

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

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

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Common questions about Wolai MCP in Mastra AI

You run `get_database` as the first step in your workflow. This ensures that every subsequent action, like querying or creating a row, knows exactly what data format it needs to follow.

Yes. You can build a loop that uses `list_pages` and then runs a separate step inside the loop for every page, executing actions like calling `get_page` on each one sequentially.

Absolutely. You wrap your `query_database` call in a multi-step workflow block. If it fails (e.g., timeout), the system retries with exponential backoff, giving you resilience.

The `list_users` tool is built for reliability within a workflow engine. It provides an authoritative list of all workspace members, which your agent can then use to validate permissions before making changes.

The server handles structured user and content details. Specifically, it manages `database rows` and `user list` information, which are critical for identity management in Wolai.

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