AcoustID MCP. Identify any song by its unique audio fingerprint.
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AcoustID: Identify music from audio fingerprints. This server lets you search for songs using their unique audio fingerprints, or look up recordings by name, artist, or MusicBrainz ID.
You can also submit new fingerprints to expand the database or pull full metadata on known tracks.
What your AI agents can do
Get recording metadata
Get all associated MusicBrainz recordings, artists, release groups, and fingerprints linked to a specific AcoustID.
Lookup by fingerprint
Identify a song by submitting an audio fingerprint and its duration, returning matching recordings and confidence scores.
Search by mbid
Find all AcoustID fingerprints linked to a specific MusicBrainz ID.
Pass an audio fingerprint and duration to get matching recordings, titles, and match confidence scores.
Retrieve all associated details—artists, release groups, and fingerprints—for a specific AcoustID.
Find every AcoustID fingerprint linked to a known MusicBrainz recording ID.
Look up recordings using general information like the song title and/or artist name.
Add new audio fingerprints to the database using the Chromaprint string and audio duration.
Ask AI about this MCP
Supported MCP Clients
Gemini Waiting for input…
019d8412get recording metadata
Get all associated MusicBrainz recordings, artists, release groups, and fingerprints linked to a specific AcoustID.
019d8412lookup by fingerprint
Identify a song by submitting an audio fingerprint and its duration, returning matching recordings and confidence scores.
019d8412search by mbid
Find all AcoustID fingerprints linked to a specific MusicBrainz ID.
019d8412search by recording
Search for recordings by general song title and/or artist name to find a matching AcoustID.
019d8412submit fingerprint
Submit a new audio fingerprint to the database, optionally including the recording name and artist.
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What you can do with this MCP connector
This server lets you identify songs using their unique audio fingerprints. You can also look up recordings by name, artist, or MusicBrainz ID. You'll get full metadata on known tracks or submit new fingerprints to expand the database.
lookup_by_fingerprint takes an audio fingerprint and its duration. It returns matching recordings, titles, and match confidence scores.
search_by_recording lets you search for recordings using general song title and/or artist name to find a matching AcoustID.
search_by_mbid finds every AcoustID fingerprint linked to a known MusicBrainz recording ID.
get_recording_metadata retrieves all associated details—artists, release groups, and fingerprints—for a specific AcoustID.
submit_fingerprint lets you add new audio fingerprints to the database using the Chromaprint string and audio duration, and you can optionally include the recording name and artist.
How AcoustID MCP Works
- 1 Subscribe to the AcoustID server. No API key is needed for initial lookups.
- 2 Start by providing the necessary data—either an audio fingerprint, a MusicBrainz ID, or a song name.
- 3 Your AI client calls the appropriate tool, and the server returns the matching recording details, metadata, or a confirmation of submission.
The bottom line is that you get a structured data payload about music, regardless of whether you know the song name or just have a snippet of audio.
Who Is AcoustID MCP For?
Music tech developers, audio researchers, and streaming service builders need this. If your product needs to recognize music from a snippet of audio, or if you need to map audio data back to large music databases, this is for you. You're the person building the next generation of audio recognition.
Integrates song identification into audio players or streaming services by using the lookup_by_fingerprint tool.
Analyzes audio fingerprints and MusicBrainz data to track music usage or research content provenance using get_recording_metadata.
Builds search features that allow users to find recordings by known metadata, like searching by artist name using search_by_recording.
What Changes When You Connect
- Identify Unknown Tracks: Pass an audio fingerprint directly to
lookup_by_fingerprintand instantly get song titles, artists, and match confidence scores. You don't need to know the name to find the song. - Build Complete Data Maps: Use
get_recording_metadatato pull every piece of associated data—artists, release groups, and all fingerprints—for a given AcoustID. This builds a full record of a track. - Handle Known IDs: If you have a MusicBrainz ID,
search_by_mbidlets you find all associated fingerprints. This is crucial when a song has multiple versions or remixes. - Improve Database Coverage: Use
submit_fingerprintto feed new audio fingerprints into the database. This expands the server's knowledge base and increases its identification accuracy. - Search by Familiar Terms: Need to find a song but only know the artist and a vague title?
search_by_recordinghandles that, returning the necessary AcoustID for deeper lookups.
Real-World Use Cases
Tracking a Viral Clip
A content manager uploads a short, viral audio clip. Instead of manually cross-referencing the audio, the agent runs the clip through lookup_by_fingerprint. The agent returns the song title, artist, and match confidence, allowing the manager to immediately identify the track's source and usage rights.
Mapping Album Content
A researcher needs to know every possible fingerprint associated with a specific album from the 90s. They use search_by_mbid with the album's MusicBrainz ID. This returns a comprehensive list of all associated AcoustIDs, making it possible to analyze the full body of work.
Onboarding New Data
Your system finds a newly recorded track that needs to be added to the index. The agent runs the audio through submit_fingerprint, providing the Chromaprint and duration. The server generates a new AcoustID, integrating the track into the database for future lookups.
Debugging a Song Link
A developer receives an AcoustID but needs to know the full scope of the recording. They call get_recording_metadata using the ID. This provides a complete data package, including related artists and release groups, which is necessary for accurate application logic.
The Tradeoffs
Searching by Metadata Only
Assuming that search_by_recording will find a song when you only provide a partial, misspelled title or artist name. This can lead to missed hits or incomplete data sets.
→
If you have a fingerprint, use lookup_by_fingerprint first. If you have the official ID, use search_by_mbid. Only use search_by_recording when those specific identifiers are missing.
Ignoring Fingerprint Confidence
Accepting the first match returned by lookup_by_fingerprint without checking the match confidence score. This risks using inaccurate data, especially for noisy or low-quality audio.
→
Always check the match confidence score. If the score is low, use search_by_recording to verify the title/artist combination before trusting the fingerprint match.
Treating AcoustID as an Endpoint
Trying to use a random AcoustID as a search parameter in search_by_recording. The tools are specialized, not interchangeable.
→
Use get_recording_metadata when you have an AcoustID. If you have a name, use search_by_recording. Never mix the input parameters between tools.
When It Fits, When It Doesn't
Use this server if your core task involves music identification—determining what song an unknown audio snippet belongs to, or linking raw audio data to known music catalog records. You need lookup_by_fingerprint when you only have the audio. You need search_by_mbid when you have the ID but not the audio. You need search_by_recording when you have the name/artist but no ID. Don't use this if your goal is general media analysis, like video processing or image tagging; those require different services. If you only need simple text lookups, use a standard database query tool instead.
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 server provides 5 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Trying to find a song when all you have is a 10-second snippet.
Today, if you encounter a piece of music and don't know the title, you usually have to guess. You search Google, then YouTube, then maybe Reddit, manually copy-pasting fragments of audio or descriptions into different search boxes until someone tells you what it is. It's a painful, fragmented process that wastes time and relies on luck.
With the AcoustID MCP Server, you just pass the audio fingerprint to the agent. The agent calls `lookup_by_fingerprint` and immediately returns the song title, artist, and all the associated IDs. You get the answer in a single step.
AcoustID MCP Server: Get full song data from a single query.
Previously, getting all the data for a track required multiple manual steps: first, searching by name to get the AcoustID; second, using that ID to find the MusicBrainz ID; and finally, querying a third service to get the full metadata. It was a three-part workflow just to get the artist's release group.
Now, you call `get_recording_metadata` and get the full data package. Everything is connected in one step. It simplifies complex music data into one clear output.
Common Questions About AcoustID MCP
How do I use the AcoustID MCP Server to identify a song by fingerprint? +
You use the lookup_by_fingerprint tool. You must provide the Chromaprint fingerprint string and the audio duration in seconds. The server then returns matching recordings, titles, and match confidence scores.
What is the difference between `search_by_recording` and `search_by_mbid`? +
search_by_recording takes human-readable inputs (name/artist). search_by_mbid requires a specific MusicBrainz ID and returns all associated fingerprints for that ID.
Can I add new songs to the AcoustID database using `submit_fingerprint`? +
Yes. The submit_fingerprint tool accepts the fingerprint string, duration, and optional name/artist, then returns the newly created AcoustID, expanding the database.
How do I get all metadata for a specific AcoustID? +
Call get_recording_metadata with the AcoustID. This retrieves all associated metadata, including related artists and release groups.
When should I use the `lookup_by_fingerprint` tool instead of `search_by_recording`? +
Use lookup_by_fingerprint when you have the raw audio fingerprint string. This tool takes the fingerprint and audio duration, returning matching recordings with match confidence scores. search_by_recording requires you to search by a known title or artist name.
How does the `get_recording_metadata` tool work with multiple AcoustIDs? +
You pass the AcoustID to get_recording_metadata to retrieve all associated details. It returns all linked MusicBrainz recordings, artists, release groups, and fingerprints for that specific AcoustID.
Is there a limit on how many fingerprints I can submit using `submit_fingerprint`? +
The listing data doesn't specify a hard rate limit. However, the tool requires the Chromaprint fingerprint string and audio duration. You'll need to check the official AcoustID documentation for current usage limits.
Can I use `search_by_mbid` to find multiple audio fingerprints for a single song? +
Yes. search_by_mbid finds all AcoustID fingerprints linked to a given MusicBrainz recording. This is useful for gathering multiple fingerprints for the same song across different sources.
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).
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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