How to Use the Zingtree MCP in Mastra AI

Q: How does Zingtree help with form data when using Mastra AI?

The getsessionformdata tool collects all entered fields for a given session. Your agent uses this data to fill out required steps in your workflow, ensuring that no user input is lost during process retries.

Q: Which trees can I list using Mastra AI?

You run listtrees to get a complete catalog of all Zingtree components available organization-wide. This helps your developer define the scope and boundaries for your workflow execution engine.

Q: What variables does Zingtree provide when using Mastra AI?

The listtreevariables function returns a comprehensive list of all variables used throughout any tree. Your agent checks this list to ensure that every input your workflow needs is defined and available.

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Connect Zingtree MCP to Mastra AI

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Setup Zingtree with Mastra AI

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Manage Session Data Flow

Use `get_session_details` to pull detailed records for a specific user interaction. This allows your multi-step workflow to know exactly who the user is and what they were doing when the process started. Mastras AI uses this data point at critical decision points. If the initial check fails, the agent knows which session record to reference when executing the retry logic.

Map Out Tree Structures

Need to understand how a complex process is wired together? Call `get_tree_structure` to get the full structure of any Zingtree component. Your workflow engine can then interpret this map. This structured output allows Mastra AI to build conditional branches automatically. The agent doesn't just run; it understands the dependencies between steps.

Search and Validate Workflow Content

Before sending a payment or triggering an action, you must verify necessary information. `search_all_trees` lets your workflow check for text within all decision trees. This acts as a mandatory pre-flight validation step. If the search fails to find required terms, Mastra AI can trigger an immediate alert and notify an admin, preventing failed deployments.

Setup guide

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

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

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

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Common questions about Zingtree MCP in Mastra AI

The `get_session_form_data` tool collects all entered fields for a given session. Your agent uses this data to fill out required steps in your workflow, ensuring that no user input is lost during process retries.

You run `list_trees` to get a complete catalog of all Zingtree components available organization-wide. This helps your developer define the scope and boundaries for your workflow execution engine.

The `list_tree_variables` function returns a comprehensive list of all variables used throughout any tree. Your agent checks this list to ensure that every input your workflow needs is defined and available.

Mastras AI supports automatic retries with exponential backoff. If a tool call like `get_session_details` temporarily fails, the agent automatically waits and tries again until it succeeds or exhausts attempts.

This MCP Server handles critical operational data: user session details, submitted form inputs, and the structural definition of decision trees. It's built for reliable execution.

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