How to Use the Dashly MCP in Mastra AI

Q: Can Mastra AI automatically reply to Dashly conversations?

It can. Just define an agent with access to sendreply and set your conditional logic. The agent will wait for your trigger and then dispatch the message.

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Connect Dashly MCP to Mastra AI

Create your Vinkius account to connect Dashly 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 Dashly with Mastra AI

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Mastra AI workflow for Dashly

Chain `list_conversations` into a decision engine that determines which support tickets need immediate attention. Mastra AI handles the logic while the tool handles the data retrieval. If a conversation requires a human, use the agent to call `send_reply` and update the status. You build a loop that acts on data without you needing to monitor the feed.

Conditional Dashly actions in Mastra AI

Set up a flow that checks user status with `get_user_details` before firing a message. If the user matches your criteria, the agent executes the reply automatically. This prevents spamming users who don't need help. The agent checks the properties, confirms the state, and only then uses the tool to push the update.

Event tracking for Mastra AI

Use `track_event` to log user milestones within your multi-agent workflow. It lets your agents record exactly what the user did during the support session. You can then branch your workflow based on these events. If the user hits a specific milestone, the agent triggers a follow-up action to keep the conversation moving.

Setup guide

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

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

const result = await agent.generate(
  "List recent Dashly transactions"
);
console.log(result.text);

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Common questions about Dashly MCP in Mastra AI

Import the client into your agent definition and add the server to your configuration. The agent automatically detects the tools, letting you call them within your workflow steps.

It can. Just define an agent with access to `send_reply` and set your conditional logic. The agent will wait for your trigger and then dispatch the message.

Mastra AI handles the backoff logic for you. If a tool call fails, the framework retries based on your defined policy, keeping your support flow stable.

You provide the server URL and your token during the client setup. The connection is ephemeral, meaning we don't keep persistent sessions open longer than necessary.

It accesses user contact records, custom properties, and message logs. This data stays within your secure agent environment and is never logged by our infrastructure.

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