How to Use the zipperHQ MCP in Mastra AI

Q: What are the best tools for running video analytics in Mastra AI?

Start with getvideoanalytics to get specific metrics. Then, use listvideos to gather all potential videos you need to run that analysis on.

Q: Can I automate finding contact data using zipperHQ and Mastra AI?

Absolutely. You can list contacts with listcontacts, then loop through the results, calling getcontactviews for each one to build a comprehensive report.

Q: When should I use the MCP Server for initial connection checks in Mastra AI?

You should call checkzipperstatus at the start of your workflow deployment. This verifies that all subsequent steps—like running reports or listing contacts—will actually connect successfully.

Build resilient, multi-step video workflows for zipperHQ using Mastra AI.

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Connect zipperHQ MCP to Mastra AI

Create your Vinkius account to connect zipperHQ 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 zipperHQ with Mastra AI

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Monitor Video Interactions

The `get_video_analytics` tool lets your workflow check the performance of any specific communication. You can build a conditional branch that only triggers if views exceed 50. Pair this with `list_contacts` to ensure you're analyzing data for every active recipient. This makes sure your automated process covers all bases.

Discover Communications History

Need to track a client interaction? Use `search_videos` to find relevant content using keywords, or pull the last 10 videos with `get_recent_videos`. These functions provide specific inputs for your multi-step workflow. If you need to review past meetings, `list_recordings` gathers all screen recordings into a single list that your agent can process.

Manage Account Credentials

The `get_account` tool pulls basic ZipperHQ account details. Your workflow needs this to know which account it's operating on before running any commands. For full visibility, you can use `list_videos` to retrieve all video emails associated with the account ID. This data is crucial for starting a reliable process.

Setup guide

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

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

const result = await agent.generate(
  "List recent zipperHQ 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 zipperHQ. 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 zipperHQ MCP in Mastra AI

Mastra AI's workflow engine automatically handles failures. It supports retries using exponential backoff and can notify an admin if the connection to zipperHQ keeps failing.

Start with `get_video_analytics` to get specific metrics. Then, use `list_videos` to gather all potential videos you need to run that analysis on.

Absolutely. You can list contacts with `list_contacts`, then loop through the results, calling `get_contact_views` for each one to build a comprehensive report.

The server touches contact communication data (names, IDs) and specific video performance metrics. You'll be working with structured records of user interactions.

You should call `check_zipper_status` at the start of your workflow deployment. This verifies that all subsequent steps—like running reports or listing contacts—will actually connect successfully.

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