How to Use the Chorus.ai (ZoomInfo) MCP in Mastra AI

Q: How do I use Chorus.ai (ZoomInfo) tools within a Mastra AI workflow?

You add the Vinkius MCP Server URL when you configure the MCPClient in your Mastra AI project. Mastra then makes the tools available to your agents, so you can call getmeetingtranscript or listchorususers as steps in your workflow.

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Connect Chorus.ai (ZoomInfo) MCP to Mastra AI

Create your Vinkius account to connect Chorus.ai (ZoomInfo) 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 Chorus.ai (ZoomInfo) with Mastra AI

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Automate Call Review Workflows

Create an agent that automatically reviews new sales calls. Set up a Mastra AI workflow that runs on a schedule, calls `list_chorus_meetings` to find new recordings, and then pulls the transcript for each one using `get_meeting_transcript`. Your agent can scan the text for competitor names fetched from `list_tracked_competitors`. If a match is found, the workflow can trigger a notification in Slack. Mastra's engine handles automatic retries, so a temporary network blip won't break your process.

Use Conditional Logic for Coaching

Build smarter coaching bots. A Mastra AI agent can check new meetings and use `get_meeting_moments` to see if 'next steps' were defined. If that key moment is missing, the workflow branches. The agent can then flag the call and assign a task to a sales manager for review. This goes beyond simple automation; it's building a process with conditional logic that responds to the actual content of your sales calls.

Build Reliable Data Syncs with this MCP Server

Sync your Chorus.ai data to an internal database without worrying about failed jobs. You can create a workflow that periodically calls `list_chorus_meetings` and `get_meeting_details` to pull the latest call metadata. Mastra AI's built-in exponential backoff and retry mechanisms mean your sync job is resilient. If the connection to the MCP Server fails, the agent will wait and try again, ensuring your data pipeline doesn't break.

Setup guide

Set up Chorus.ai (ZoomInfo) 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 Chorus.ai (ZoomInfo) 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: "chorusai-zoominfo-mcp-client",
  servers: {
    "chorusai-zoominfo-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

const result = await agent.generate(
  "List recent Chorus.ai (ZoomInfo) 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 Chorus.ai. 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 Chorus.ai (ZoomInfo) MCP in Mastra AI

You add the Vinkius MCP Server URL when you configure the `MCPClient` in your Mastra AI project. Mastra then makes the tools available to your agents, so you can call `get_meeting_transcript` or `list_chorus_users` as steps in your workflow.

Yes, that's one of its core strengths. Mastra AI has built-in support for automatic retries with exponential backoff. If a tool call fails due to a temporary issue, your workflow won't crash; it will intelligently retry the operation.

Mastra AI supports human-in-the-loop workflows. You can configure a step that requires approval before proceeding, like before sending a summary of a sensitive call found via `get_meeting_details`. The workflow will pause until it gets the green light.

No. You get a single endpoint token from Vinkius for the MCP Server. You provide this to your Mastra AI client, and it handles the secure connection. You don't need to manage OAuth flows or refresh tokens yourself.

Your Chorus.ai data—like meeting details and transcripts—is fetched through a secure, token-based Vinkius endpoint. The MCP Server itself runs in a zero-trust environment. Your Mastra AI agent, running in your own infrastructure, is the only thing that receives the data.

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