How to Use the Texter MCP in Mastra AI

Q: How does Texter work with mastra-ai for retrying messages?

You map the sendtextermessage tool within a workflow. If the initial message fails, your agent can execute a retry step using exponential backoff logic defined in your flow.

Q: What is the best way to list available departments with Texter and mastra-ai?

You use listtexterdepartments early in your workflow. This allows your agent to validate that a department exists before attempting any message sending actions.

Q: Can I use Texter with mastra-ai to close or resolve a chat?

Yes, the resolvetexterchat tool lets you programmatically close a conversation. This is useful in workflows that transition a lead from 'active follow-up' to 'resolved/archived'.

Q: How do I confirm chat labels using Texter with mastra-ai?

Use listtexterlabels to fetch all available labels for the account. Your workflow can then use this list to determine if a required label exists before calling addlabeltotexterchat.

Build resilient, multi-step workflows that recover from failure using mastra-ai.

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Setup Texter with Mastra AI

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Claude

Perplexity

Automated Workflow Messaging

The `send_texter_message` tool fits right into complex sequences. If a primary action fails—say, the first SMS attempt hits an error code—your workflow can automatically retry or switch to `send_texter_template`. This handles the retries and conditional branching needed for high-stakes drip campaigns.

Stateful Chat Management

Need to keep track of a lead's journey? You can use `list_texter_chats` at the start of a workflow, check which chats are active, and then decide if you need to call `resolve_texter_chat`. This ensures your multi-step agent doesn't try to act on stale or closed chat records.

Error Handling for Chat Details

`get_texter_chat_details` lets you pull all the necessary context before proceeding. If the required parameters are missing, your agent can catch that error and trigger a manual alert instead of failing completely. It builds resilience into your communication automation.

Setup guide

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

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

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

You map the `send_texter_message` tool within a workflow. If the initial message fails, your agent can execute a retry step using exponential backoff logic defined in your flow.

You use `list_texter_departments` early in your workflow. This allows your agent to validate that a department exists before attempting any message sending actions.

The server touches text messages (SMS/WhatsApp content), chat IDs, and user labels. Always ensure your workflow handles temporary storage of PII securely between steps.

Yes, the `resolve_texter_chat` tool lets you programmatically close a conversation. This is useful in workflows that transition a lead from 'active follow-up' to 'resolved/archived'.

Use `list_texter_labels` to fetch all available labels for the account. Your workflow can then use this list to determine if a required label exists before calling `add_label_to_texter_chat`.

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