Vinkius
AcoustID

AcoustID MCP for AI. Identify any song using its audio fingerprint.

Claude Claude
ChatGPT ChatGPT
Cursor Cursor
Gemini Gemini
Windsurf Windsurf
VS Code VS Code
JetBrains JetBrains
Vercel Vercel
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AcoustID MCP on Cursor AI Code EditorAcoustID MCP on Claude Desktop AppAcoustID MCP on OpenAI Agents SDKAcoustID MCP on Visual Studio CodeAcoustID MCP on GitHub Copilot AI AgentAcoustID MCP on Google Gemini AIAcoustID MCP on Lovable AI DevelopmentAcoustID MCP on Mistral AI AgentsAcoustID MCP on Amazon AWS Bedrock

Connect to your AI in seconds.

AcoustID identifies songs using audio fingerprints—it's basically Shazam for developers. You feed it a clip, and it returns full metadata, like the artist, album, and MusicBrainz ID.

Need to search recordings by name or find all associated fingerprints? This MCP handles it, giving you deep access to music library data without needing an API key for basic lookups.

What your AI can do

Get recording metadata

Gets full details for a recording—like artists and release groups—using an existing AcoustID.

Lookup by fingerprint

Identifies a song by taking an audio fingerprint string and the clip's duration.

Search by mbid

Finds all associated fingerprints for a specific MusicBrainz ID, useful if you know the recording but not the fingerprints.

+ 2 more capabilities included
Identify songs from audio clips

Submit an audio fingerprint, and the MCP returns matching recordings with confidence scores, titles, and artists.

Find metadata for a specific recording

Retrieve all associated details—like the original artist, album name, and release groups—using a known AcoustID.

Search recordings by text criteria

Look up records using general search terms like an artist's name or a song title.

Find fingerprints for a given ID

Use a MusicBrainz ID to retrieve every associated audio fingerprint, which is useful for batch processing.

Contribute new data

Submit new audio fingerprints to expand the database with information about unknown songs.

Included with Plan

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AI Agent

AcoustID: 5 Tools for Audio Metadata Search

These five tools let you interact with the entire AcoustID database, allowing you to search recordings by name, find fingerprints from an ID, or submit new audio data.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using AcoustID on Vinkius

Get Recording Metadata

Gets full details for a recording—like artists and release groups—using an existing AcoustID.

Lookup By Fingerprint

Identifies a song by taking an audio fingerprint string and the clip's duration.

Search By Mbid

Finds all associated fingerprints for a specific MusicBrainz ID, useful if you know...

Search By Recording

Locates matching recordings by providing general text like an artist or song name.

Submit Fingerprint

Adds a new audio fingerprint to the system, requiring the chromaprint string and...

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Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

Claude AI

Claude AI

1

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

2

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

3

Start a conversation

Open a new chat. The AcoustID integration is available immediately — no restart needed.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

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Start building

Make Your AI Do More

Start with AcoustID, then connect any of our 5,100+ other servers whenever your AI needs more. One click, no limits.

  • Use this MCP plus 5,100+ others, all in one place
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  • Works with Claude, ChatGPT, Cursor, and more
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AcoustID MCP server cover

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by AcoustID. 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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Works with Claude, ChatGPT, Cursor, and more

The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.

This connection provides 5 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.

Tracing an Unknown Song's Provenance

Right now, finding out what song was playing at a party or in a movie scene means opening multiple web tabs: Google Search for the title, then Shazam to check fingerprints, and maybe another site just to verify the album art. It's manual work that involves copy-pasting IDs from one service into another.

With this MCP, you feed your agent the audio clip once. Your AI client handles all the cross-referencing—it runs the fingerprint match, retrieves metadata via `get_recording_metadata`, and gives you a complete dossier on the track without ever leaving the chat window.

AcoustID MCP: Getting Full Music Records

The process of finding all related data used to take multiple steps: first, running a basic search by name, then taking the resulting IDs and manually feeding those into separate lookup tools. It was slow and required keeping track of five different identifiers.

Now, you can use `search_by_mbid` or `get_recording_metadata` to pull all associated details in one go. The data flow is clean: you give the ID, you get the complete record. That’s it.

What your AI can actually do with this

This connector lets your agent identify songs just by listening to a short audio clip. You don't need to know the title or artist; you just submit a fingerprint and get immediate results. It pulls rich metadata, linking the song directly to its MusicBrainz ID and providing details about the release group.

The system also allows you to search for recordings using general criteria, like an artist name, or look up all associated fingerprints if you already have a known MusicBrainz ID. If you're building anything audio-related, connecting this MCP through Vinkius means your AI client has immediate access to thousands of music records and metadata types.

Plus, you can even submit new fingerprints if you find a song that needs adding to the database.

Built · Hosted · Managed by Vinkius AcoustID - Identify Songs by Audio Fingerprint MCP
Server ID 019d8412-3efc-723b-94d8-d4dc5a993ef1
Vinkius Inspector
Compliance Grade A+
Score 100/100
Vinkius Inspector Badge — Score 100/100

Questions you might have

How do I identify a song using AcoustID MCP? +

You run lookup_by_fingerprint by providing the chromaprint fingerprint string and the audio duration in seconds. The system returns matching records, titles, and artists.

What is the best way to search for a song using AcoustID MCP? +

If you only know the name or artist, use search_by_recording. This tool handles general text inputs and finds relevant records across the database.

Can I get full metadata using AcoustID MCP? +

Yes. Use get_recording_metadata with an existing AcoustID to retrieve comprehensive details, including artist names and release group information.

How do I add a song fingerprint using AcoustID MCP? +

You use the submit_fingerprint tool. You must provide the chromaprint fingerprint string and audio duration; you can optionally include name and artist for better indexing.

Does search_by_mbid work if I don't know the fingerprints? +

Yes, that is exactly what it does. If you have a MusicBrainz ID but no specific fingerprint, search_by_mbid retrieves all associated audio fingerprints for you.

If I know a MusicBrainz ID but not the fingerprints, how do I use `search_by_mbid`? +

It finds all associated AcoustID fingerprints for that single MusicBrainz recording. This is useful because it lets you gather every available fingerprint linked to the known song record.

When I run `search_by_recording`, what specific IDs do I receive for a found track? +

You get the matching recording's AcoustID, MusicBrainz ID, title, and artist name. This initial search gives you key identifiers needed to perform more detailed metadata lookups.

Does `lookup_by_fingerprint` require both the fingerprint string and audio duration? +

Yes, it requires both parameters to run successfully. You must provide the Chromaprint fingerprint and the precise audio length in seconds for a match attempt.

Do I need an API key? +

No! AcoustID's public API works without authentication using a default client key for basic lookups.

How does audio fingerprinting work? +

AcoustID uses Chromaprint (fpcalc) to generate a fingerprint from audio. This fingerprint is matched against the database to identify the song. You need to run fpcalc on an audio file to get the fingerprint string.

What is MusicBrainz? +

MusicBrainz is an open music encyclopedia that collects music metadata. AcoustID links audio fingerprints to MusicBrainz recordings, enabling song identification through the MusicBrainz ID (MBID).

Built & Managed by Vinkius 30s setup 5 tools

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