How to Use the Chord Constructor MCP in Pydantic AI

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Connect Chord Constructor MCP to Pydantic AI

Create your Vinkius account to connect Chord Constructor to Pydantic 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 Chord Constructor with Pydantic AI

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Perplexity

Pinpoint functional role and context

The `determine_harmonic_role` tool accurately identifies a chord's function within its key. If your agent needs to write music that sounds structurally correct, this is the bedrock. It tells you if the chord belongs in the subdominant or dominant area. Because Pydantic AI validates everything at runtime, you never get bad data back here. The structure of the harmonic role output is always predictable and type-safe.

Structure raw musical notation

Use `parse_chord_string` to convert messy chord names into clean, structured components. It returns the root, intervals, and a normalized name for every input string. This ensures that when your agent works with music data, it's always dealing with predictable Python objects. This makes the entire process less about guesswork and more about guaranteed computational accuracy.

Define complex inversions and textures

The system handles chord arrangement using `generate_voicings`, returning structured data for both 'open' and 'closed' musical textures. It specifies the exact note placement needed. Furthermore, it calculates every possible bass-note variation with `get_chord_inversions`. This gives your agent a complete map of all viable harmonic options for any given chord.

Setup guide

Set up Chord Constructor MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "chord-constructor-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Chord Constructor tools.",
)

result = await agent.run("List recent Chord Constructor transactions")
print(result.output)

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Common questions about Chord Constructor MCP in Pydantic AI

The MCP provides reliable, structured access to advanced music theory. Since your agent uses Pydantic AI, it gets guaranteed type-safe outputs for every chord analysis or voicing request.

Yes. You can reliably chain tools: get a chord's role, use that information to generate voicings, and then adjust the bass note using inversions—all knowing the output will be correct.

You can. The agent's strength is linking specialized knowledge. For example, you might use `parse_chord_string` to get the notes, then pass those structured notes to determine their harmonic role.

Give it a difficult chord passage and ask your agent for both its functional role and all available inversions. You'll get a fully validated, comprehensive musical map.

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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