How to Use the Zenvia Conversion MCP in Mastra AI

Q: How do I check account status for Zenvia Conversion using Mastra AI?

You call getaccount. The built-in workflow engine ensures that this data retrieval is reliable, even if the initial connection has transient issues. It provides a definitive status update.

Q: Can Zenvia Conversion messages be sent with Mastra AI?

Yes, you can send both direct messages (sendmessage) and templated messages (sendtemplate). The framework manages the full lifecycle of these communications, including retries.

Q: How do I list all prospects using Mastra AI?

You run listprospects. Since this is a workflow, if the initial call fails, the system automatically retries the listing process until it succeeds.

Q: Is Zenvia Conversion capable of grouping leads with Mastra AI?

You can use listgroups to retrieve available groups. The agent then uses this context when building a communication workflow across multiple related contacts.

Build resilient Zenvia Conversion workflows with Mastra AI's robust workflow engine.

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Setup Zenvia Conversion with Mastra AI

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Automate Lead Creation

If you need to capture a new lead, use `create_lead`. The agent handles the submission of contact details and comments into Zenvia Conversion. This tool supports complex workflows, letting you retry submissions if they fail. It's perfect for building multi-step processes where an initial data entry needs validation before proceeding.

Retrieve Prospect Details

Need specific information on a target? `get_prospect` pulls all detailed records about a lead in Zenvia Conversion. Mastra AI can wrap this tool in a workflow that runs automatically, for example, checking the status before sending anything. You also get access to `list_interactions`, which lets you trace every message and action taken on a prospect.

Execute Communications

Sending messages is reliable. Use `send_message` for direct communication, or use `send_template` if the content is standardized (HSM). The workflow engine guarantees delivery attempts and handles retries with exponential backoff. If you need to communicate across different groups, `list_groups` helps define the scope of your message blast.

Setup guide

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

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

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

You call `get_account`. The built-in workflow engine ensures that this data retrieval is reliable, even if the initial connection has transient issues. It provides a definitive status update.

Yes, you can send both direct messages (`send_message`) and templated messages (`send_template`). The framework manages the full lifecycle of these communications, including retries.

The server handles core contact details, prospect profiles, and message history. These are the primary data types you'll manipulate when building workflows in Zenvia Conversion.

You run `list_prospects`. Since this is a workflow, if the initial call fails, the system automatically retries the listing process until it succeeds.

You can use `list_groups` to retrieve available groups. The agent then uses this context when building a communication workflow across multiple related contacts.

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