How to Use the Chord Constructor MCP in Google ADK

Q: Is Chord Constructor useful for large datasets in Google ADK?

Yes. By converting raw notation using parsechordstring, the MCP standardizes complex data points, making them ready to be queried and analyzed against your BigQuery tables.

Q: Can I chain tools using Chord Constructor with Google ADK?

You can. Your agent might first use determineharmonicrole to find a structural point, then feed that information into the voicing toolset to generate specific notes for that spot.

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Connect Chord Constructor MCP to Google ADK

Create your Vinkius account to connect Chord Constructor to Google ADK 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 Chord Constructor with Google ADK

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Determine harmonic role for structured data

The `determine_harmonic_role` tool identifies a chord's functional purpose within any specified key, giving your agent structural depth. Instead of just seeing notes, the agent sees function—is this V or IV? This is vital when building large-scale musical datasets. It helps you categorize and organize massive amounts of music data stored in BigQuery. You can write rules that say, 'If the chord has a dominant role here, then the next section must resolve it.'

Convert notation into usable components

You start with `parse_chord_string`, which takes raw musical notation and converts it to structured data. It returns the root, intervals, and a clean name for every chord you feed it. This process is key because your agent can't work on messy text; it needs organized facts. This function ensures that whether the input came from a legacy file or a modern stream, the ADK receives standardized, machine-readable musical theory components.

Generate varied chord voicings and inversions

The agent uses `generate_voicings` to create specific note arrangements for both 'open' and 'closed' textures. This tool tells the system exactly how a chord should be voiced, which is critical for accurate musical reproduction. It also runs through all possible permutations using `get_chord_inversions`, calculating every way a chord can serve as a bass note. This gives your Google ADK agent massive control over voicing variation.

Setup guide

Set up Chord Constructor MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Chord Constructor tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Chord Constructor_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Chord Constructor tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Chord Constructor MCP in Google ADK

The MCP allows your agent to perform complex music theory calculations, like determining harmonic roles or generating inversions. It brings structured musical knowledge into your existing cloud workflows.

Yes. By converting raw notation using `parse_chord_string`, the MCP standardizes complex data points, making them ready to be queried and analyzed against your BigQuery tables.

You can. Your agent might first use `determine_harmonic_role` to find a structural point, then feed that information into the voicing toolset to generate specific notes for that spot.

Try running it on known musical passages. Feed in a chord string and ask your agent not just for its role, but also for all possible inversions, giving you both structure and texture.

This MCP processes structural musical theory components, specifically reading and processing raw musical chord symbols and their resulting structured note intervals.

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