How to Use the Platform.ly MCP in Mastra AI

Q: Can Mastra AI retry failed Platform.ly deal creations?

Yes. If createnewsalesdeal times out, the built-in workflow engine waits and tries the exact same payload again based on your backoff settings.

Build resilient Platform.ly MCP workflows with Mastra AI that automatically retry failed CRM updates.

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Connect Platform.ly MCP to Mastra AI

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Setup Platform.ly with Mastra AI

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Mastra AI Workflow Automation

The `search_contact_by_email` tool acts as the first step in your Mastra AI onboarding sequence. If the query returns nothing, your workflow branches automatically to `create_new_contact` using the target project ID. You configure exponential backoff on these calls. If the Platform.ly API drops the request, Mastra pauses and tries again, ensuring you never lose a lead during high-traffic marketing events.

Conditional Deal Routing

Your agent uses `create_new_sales_deal` to push qualified leads into specific Platform.ly funnels. You dictate the exact conditions—like requiring a specific lead score—before the workflow executes the command. To keep records clean, the system triggers `add_note_to_contact` immediately after the deal opens. A human-in-the-loop approval step stops the agent from spamming your sales board with junk data.

Dynamic Audience Segmentation

The `list_project_segments` and `apply_tag_to_contact` tools give your Mastra AI agent direct control over marketing lists. The agent evaluates user behavior, pulls the available tags, and assigns them accordingly. This MCP setup allows for complex conditional logic. If a user downgrades their account, the workflow fires `remove_tag_from_contact` and immediately moves them to a churn-recovery segment.

Setup guide

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

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

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

Initialize an MCPClient with your server URL and call listTools(). Spread the resulting array directly into your Mastra agent configuration.

Yes. If `create_new_sales_deal` times out, the built-in workflow engine waits and tries the exact same payload again based on your backoff settings.

Set the requireToolApproval flag on destructive actions like `remove_tag_from_contact`. The workflow pauses execution until an admin clicks approve.

Your agent evaluates the array of returned IDs. You write conditional branches to merge the data or pick the most recent entry before calling `update_existing_contact`.

The managed infrastructure routes your deal stages, pipeline IDs, and prospect notes through ephemeral memory. The container wipes all state completely after the workflow completes its final step.

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