How to Use the Workast MCP in Mastra AI

Q: How do I handle task updates in Workast and Mastra AI?

You use the updatetask tool. Because of the built-in workflow engine, you can wrap this call with retries. If the update fails temporarily, the system tries again automatically until it succeeds or hits a hard limit.

Q: What if I need to create multiple spaces in Workast using Mastra AI?

Simply define a sequence of calls to createspace. The workflow will execute each call, waiting for confirmation before moving to the next. This makes batch operations reliable.

Q: Can I check team information with Workast using Mastra AI?

Yes. Your multi-step process can use getteaminfo as a required validation step. If the data returned doesn't match expected criteria, your agent stops and raises a controlled error.

Q: Does Workast support task deletion with Mastra AI?

Yes. The deletetask tool is available. Because it’s part of the MCP Server, you can build workflows that require explicit confirmation before running this destructive action.

Build resilient Workast workflows that self-correct using Mastra AI.

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Perplexity

Complex Multi-Step Logic with Mastra AI

You build full workflows that handle failures gracefully. If the initial check fails, your agent can automatically retry by calling a different tool or executing conditional logic. This is how you manage complex tasks: A workflow might first call `get_user` to verify status, then attempt an action via `update_task`, and only proceed if the result passes validation.

Project Lifecycle Management with Mastra AI MCP Server

Workast's project tools let you manage the whole cycle. You can reliably create new projects by calling `create_space` and then immediately set up initial work items using `create_task`. The workflow engine ensures these steps happen in order, handling any connection drops or API rate limits along the way.

Team Data Validation with Mastra AI

Need to make sure a user belongs to an active team before proceeding? The agent calls `get_team_info` and checks the status. If the team is inactive, the workflow can branch and notify an admin. Alternatively, you can check specific users using `list_users` or getting details with `get_user` within a resilient loop.

Setup guide

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

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

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

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Common questions about Workast MCP in Mastra AI

You use the `update_task` tool. Because of the built-in workflow engine, you can wrap this call with retries. If the update fails temporarily, the system tries again automatically until it succeeds or hits a hard limit.

Simply define a sequence of calls to `create_space`. The workflow will execute each call, waiting for confirmation before moving to the next. This makes batch operations reliable.

Yes. Your multi-step process can use `get_team_info` as a required validation step. If the data returned doesn't match expected criteria, your agent stops and raises a controlled error.

Yes. The `delete_task` tool is available. Because it’s part of the MCP Server, you can build workflows that require explicit confirmation before running this destructive action.

The server manages project metadata like task statuses, team compositions, and user account details. These are the core structured records you're building workflows around.

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