How to Use the Workvivo MCP in Mastra AI

Q: How does Mastra AI handle failures when accessing Workvivo data?

It's designed for resilience. If a tool call, like getemployeeprofile, fails due to network issues or temporary API limits, the client automatically retries with backoff.

Q: Can I chain listing Workvivo posts using Mastra AI?

Yep. You can first use listworkvivoposts to get a batch of IDs, and then build a subsequent step that loops through those IDs calling getpostdetails for each one.

Q: What is the best way to manage Workvivo space data with Mastra AI?

Start by listing all spaces using listcollaborationspaces. Then, your workflow can pick a specific space and use getspacedetails to gather deep context for subsequent actions.

Q: If I update an employee profile via MCP Server using Mastra AI, what precautions should I take?

Always wrap the call in a check. Use getemployeeprofile first to validate the existing data structure and ensure your new input matches required fields before writing.

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Connect Workvivo MCP to Mastra AI

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Setup Workvivo with Mastra AI

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Conditional Space Checks

Need to know if a space exists before continuing? Call `get_space_details` first. If the data is missing or incorrect, your workflow can branch and retry using Mastra AI's built-in logic. You also get details for specific calendar entries with `get_event_details`. This makes it perfect for multi-step workflows that depend on confirming an event exists.

Guaranteed Content Publishing

Want to post content, but only if the user is active? You can wrap `create_social_post` in a conditional step. If posting fails (e.g., rate limit), Mastra AI automatically retries with exponential backoff. This reliable publishing mechanism handles the complexities of sending messages on behalf of your users.

Scheduled Event Listing

Set up a workflow that needs to know about upcoming company events. Use `list_company_events` to pull all scheduled dates from Workvivo. You can also combine this with `list_employees`. The Mastra AI client pulls both lists and lets your developer write complex logic around the combined dataset.

Setup guide

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

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

const result = await agent.generate(
  "List recent Workvivo 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 Workvivo. 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.

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Common questions about Workvivo MCP in Mastra AI

It's designed for resilience. If a tool call, like `get_employee_profile`, fails due to network issues or temporary API limits, the client automatically retries with backoff.

Yep. You can first use `list_workvivo_posts` to get a batch of IDs, and then build a subsequent step that loops through those IDs calling `get_post_details` for each one.

Start by listing all spaces using `list_collaboration_spaces`. Then, your workflow can pick a specific space and use `get_space_details` to gather deep context for subsequent actions.

Always wrap the call in a check. Use `get_employee_profile` first to validate the existing data structure and ensure your new input matches required fields before writing.

You handle various structures, from detailed employee records to event data. For instance, `get_event_details` provides structured calendar information.

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