How to Use the Chord Progression Analyzer MCP in Mastra AI

Q: Can I require human approval for context lookups with Mastra AI?

Yes. You can set up requireToolApproval when calling the contextual tools, ensuring a person reviews the suggested emotional or stylistic metadata before final output.

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Connect Chord Progression Analyzer MCP to Mastra AI

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Setup Chord Progression Analyzer with Mastra AI

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Perplexity

Validate Harmonic Structure in Workflows

Start a complex workflow by using `analyze_roman_numerals` to convert chords into functional Roman numerals. If the initial conversion fails or yields ambiguous results, your Mastra AI agent can trigger a retry with different input parameters. This process ensures that even if chord inputs are tricky, your multi-step musical analysis won't crash. The workflow continues gracefully after successful data mapping.

Conditional Progression Classification

You can design conditional branches around `classify_progression`. For example, if the progression is identified as a pre-chorus lift, the next step automatically calls another tool to enrich that specific finding. If it's a verse section, it follows an alternative path. This makes your music analysis incredibly adaptive. It handles complex decision trees based on harmonic output.

Human-in-the-Loop Context Review

When the agent hits `lookup_musical_context`, you can use Mastra AI's human-in-the-loop approval. The system pauses, presents the suggested emotional intent to a human reviewer, and only proceeds with the final analysis after that explicit sign-off. This is perfect for professional music production tools where accuracy matters and automated guessing isn't enough.

Setup guide

Set up Chord Progression Analyzer 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 Chord Progression Analyzer 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: "chord-progression-analyzer-mcp-client",
  servers: {
    "chord-progression-analyzer-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

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

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Common questions about Chord Progression Analyzer MCP in Mastra AI

You integrate it into a multi-step workflow. For instance, the agent first runs `analyze_roman_numerals`, then uses those results to feed the classification step. The entire process is managed by Mastra AI's engine.

Yes. Because it supports automatic retries and conditional branching, your workflow handles failures in the harmonic analysis gracefully, ensuring a complete result every time.

It is designed for that. You can chain multiple tools together—like classification followed by context lookup—to build highly detailed and reliable musical analysis pipelines.

The MCP handles structured musical theory data, specifically chord names, Roman numeral functions, and associated stylistic/emotional metadata. This is all designed for robust workflow handling.

Yes. You can set up `requireToolApproval` when calling the contextual tools, ensuring a person reviews the suggested emotional or stylistic metadata before final output.

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