How to Use the YesNo MCP in Mastra AI

Q: Can YesNo handle conditional logic in Mastra AI?

Yes. You can use the random output of getdecision to determine which path your workflow takes, enabling advanced branching and retry mechanisms.

Q: Is the decision from YesNo useful for testing in Mastra AI?

Yes. You'll use getdecision to simulate unpredictable inputs, letting you test how your entire workflow handles random outcomes.

Build reliable workflows with random decision points using Mastra AI.

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Create your Vinkius account to connect YesNo 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 YesNo with Mastra AI

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Decision Branching in Workflows

Need your workflow to react to chance? Use `get_decision` as a conditional step. If the tool returns 'No,' you can trigger an automatic retry sequence; if it's 'Yes,' you proceed normally. This makes complex, multi-step processes that need failure handling or random pathing.

Handling Ambiguity with `get_decision`

Sometimes a decision isn't clear. The `get_decision` tool provides 'Maybe,' allowing your Mastra AI workflow to gracefully pause or notify an admin for human review. It handles the random element, which is great when you can't predict the next step but need the process to continue.

Simulating Random Inputs

If your workflow requires a simulated vote or chance input, `get_decision` fills that gap. It returns a random yes/no/maybe decision and includes an accompanying GIF for logging purposes. This lets you test complex branching logic without needing real-world inputs.

Setup guide

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

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

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

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Common questions about YesNo MCP in Mastra AI

Yes. You can use the random output of `get_decision` to determine which path your workflow takes, enabling advanced branching and retry mechanisms.

It does. The tool fits easily into a multi-step sequence, serving as a decision point that guides the flow before subsequent actions are taken.

The server provides simple textual decisions (yes/no/maybe) along with GIF metadata. This is random, chance-based data that your workflow can consume.

Yes. You'll use `get_decision` to simulate unpredictable inputs, letting you test how your entire workflow handles random outcomes.

It touches simple textual decisions and GIF metadata. Since it's generating random choices, the impact on sensitive user data is minimal.

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