How to Use the Breathing Timer MCP in Mastra AI

Q: Can I use the Mastra AI for structured Breathing Timer guidance?

Yes. You define your steps and then use generatebreathingschedule to build a reliable sequence that handles potential failures gracefully, guaranteeing continuity.

Q: What data does the Mastra AI need from the Breathing Timer MCP Server?

It uses parameters like those retrieved by querybreathingparameters, which define things like ideal inhale and exhale counts for various techniques.

Q: How do I ensure data integrity with the Mastra AI's Breathing Timer?

You can verify timings using calculatesinglecycleduration. This guarantees that every calculated cycle adheres exactly to the specified time metrics.

Build reliable Breathing Timer workflows with Mastra AI.

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Setup Breathing Timer with Mastra AI

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Guaranteed Schedules for the Mastra AI

Don't let a failing step ruin your routine. Use `generate_breathing_schedule` to build complex, multi-stage breathing sessions. If one part of the schedule fails or needs adjustment, the built-in workflow engine handles retries automatically. It ensures that the user always gets a guided experience, even if an external dependency hiccups.

Validating Breathing Timer Parameters with Mastra AI

The `query_breathing_parameters` tool gives you immediate access to all default timing settings for any technique. This is key when building complex workflows because it lets your agent validate requirements before attempting a cycle. It's the perfect guardrail for reliable, multi-step deployments.

Calculating Cycle Durations in Mastra AI

Need precise timing? `calculate_single_cycle_duration` accurately determines the total time for any breathing pattern. This function is vital when your workflow needs to ensure that transitions happen at exact, measured intervals. It minimizes risk by guaranteeing accurate math across all steps.

Setup guide

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

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

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

Mastra AI uses its built-in workflow engine. If generating a schedule fails, it can automatically retry the call or switch to an alternative method without human intervention.

Yes. You define your steps and then use `generate_breathing_schedule` to build a reliable sequence that handles potential failures gracefully, guaranteeing continuity.

It uses parameters like those retrieved by `query_breathing_parameters`, which define things like ideal inhale and exhale counts for various techniques.

The reliability is high. Since it manages state transitions and retries, your entire Breathing Timer process runs reliably from start to finish.

You can verify timings using `calculate_single_cycle_duration`. This guarantees that every calculated cycle adheres exactly to the specified time metrics.

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