ACRCloud Music Recognition MCP for AI. Identify any song from an audio file or link.
Works with every AI agent you already use
…and any MCP-compatible client








Connect to your AI in seconds.
ACRCloud Music Recognition instantly identifies songs and pulls rich metadata from audio files or URLs. Use this MCP to get deep details on tracks, artists, and albums, including direct streaming links for Spotify and YouTube.
What your AI can do
Get track by isrc
Looks up a track's details using its unique ISRC code.
Identify music from url
Determines the song identity from any provided audio file URL, like MP3 or WAV.
Search albums
Finds music albums when given an artist name or album title.
Send an audio file URL and get the song title, artist, album, and detailed metadata instantly.
Input a track's ISRC code to pull precise and reliable metadata for that specific recording.
Query the database using only the song title, artist name, or even fragments of lyrics.
Search for entire artist discographies or browse albums by title to explore related tracks.
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ACRCloud Music Recognition MCP: 5 Tools Available
These five tools allow you to identify music, search artists and albums, or retrieve specific track data using unique codes, all from one place.
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 ACRCloud Music Recognition on VinkiusGet Track By Isrc
Looks up a track's details using its unique ISRC code.
Identify Music From Url
Determines the song identity from any provided audio file URL, like MP3 or WAV.
Search Albums
Finds music albums when given an artist name or album title.
Search Artists
Searches and lists available artists by their professional name.
Search Tracks
Finds specific songs using a mix of artist names, track titles, or partial lyrics.
Security and governance baked right in.
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.
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.
- Import from OpenAPI, Swagger, or YAML specs
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- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
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Make Your AI Do More
Start with ACRCloud Music Recognition, then connect any of our 5,000+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,000+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
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- Works with Claude, ChatGPT, Cursor, and more
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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.
Tracking down unknown music is usually a mess of copy-pasting and dead ends.
Right now, if you hear a song or download an audio file, finding out who made it means opening multiple tabs. You check Google for the title, then open Spotify to see the artist's discography, then maybe cross-reference Wikipedia for metadata. It’s slow, and sometimes you only find partial information.
With this MCP, your agent does all that work instantly. Hand it a URL or an audio clip, and it returns everything—artist, album, track details, and multiple direct streaming links—in one clean output.
The ACRCloud Music Recognition MCP delivers full media metadata.
You eliminate the need for manual checks across different platforms. Instead of running separate searches, you tell your agent to identify a song from an audio file URL and get all associated data points at once.
Now, when you analyze music content, you don't guess or approximate; you get complete, verifiable metadata automatically.
What your AI can actually do with this
This connector lets your agent listen to music—whether you hand it a file link or just tell it what sounds like background noise—and figure out exactly what that track is. It pulls more than just the title; you get the artist's full discography, the album details, and even professional data points like confidence scores.
If you’re building any kind of media app, this is crucial for tagging content or checking copyright metadata. You connect it via Vinkius to your preferred AI client and suddenly your agent can interact with a global music database using natural conversation. It's a huge leap from manually searching five different databases; now, all that data just flows through one place.
019d8412-6cbe-71ba-b2e2-19e893b5b77e Here's how it actually works
The bottom line is that your AI client takes raw audio or basic data points and outputs a complete, verifiable music profile.
You initiate a request, giving your agent either an audio URL or specific metadata like an ISRC code.
The MCP routes the data through ACRCloud's recognition service and global database lookup tools.
Your agent gets back structured JSON containing all the verified details: artist names, multiple streaming links, album dates, and track codes.
Who is this actually for?
Anyone who deals with media files needs this. Content creators dealing with background music copyright checks are prime candidates. Music app developers need it for core functionality. Digital archivists needing to index large libraries of audio recordings also rely on this.
Checks unfamiliar music in a video clip or podcast segment, ensuring they know the artist and track details before posting.
Integrates accurate track identification into a prototype app, allowing users to search for songs using only an audio sample.
Processes large batches of unknown recorded audio files, generating metadata and links for proper cataloging.
What Changes When You Connect
You don't have to manually check five different APIs. Use identify_music_from_url once, and you get the artist details necessary for subsequent searches using search_albums or search_artists.
The system handles deep metadata retrieval automatically. When a song is identified, it pulls not just the name but also multiple streaming links (Spotify, YouTube) in one go.
Need to verify data accuracy? Run get_track_by_isrc with a unique code for guaranteed metadata reliability, bypassing reliance on names or URLs.
It's powerful enough for developers. You can build structured workflows that first use search_artists and then pipe the results into search_tracks, creating complex data paths.
Forget vague searching. If you only have a few lyrics fragments, search_tracks lets your agent pinpoint songs when name searches fail.
See it in action
Checking Copyright for a Video Project
A content creator has background music from an unknown source. They send the audio snippet to their agent, which uses identify_music_from_url. The result confirms the artist and album, letting them check copyright status immediately.
Building a Media Directory Index
An archivist needs to index 1,000 unknown recordings. They feed the audio URLs into their agent, which uses identify_music_from_url for every file, generating a structured database of metadata and streaming links.
Finding a Deep Cut Track
A music enthusiast knows an obscure song but only remembers two lines of the chorus. They ask their agent to search using search_tracks with those lyrics, finding the exact track when title searches would fail.
Cross-Verifying Track Data
A developer wants to confirm a song's details. First, they use identify_music_from_url. Then, they take the resulting ISRC and run it through get_track_by_isrc for absolute metadata confirmation.
The honest tradeoffs
Using only name searches
Asking your agent to search by artist, then searching again by track title. This is redundant because the data often overlaps.
First, use identify_music_from_url on a sample of the music. The resulting metadata gives you both the artist and track name simultaneously for reliable data.
Ignoring unique identifiers
Relying solely on search results when the song's ISRC code is available. Name searches can be ambiguous.
If you have an ISRC, always start there. Run get_track_by_isrc first to get the most precise details without any ambiguity.
Treating tools as separate steps
Manually copy-pasting metadata from one search result into a spreadsheet, then manually checking links.
Let your agent handle it. Use the MCP to pipe all results—from identify_music_from_url through to finding streaming links—into structured output automatically.
When It Fits, When It Doesn't
Use this MCP if your core need is mapping unknown or partial audio data (URLs, fingerprints, lyrics) to a comprehensive music profile. It's the right choice when you need immediate identification and rich metadata retrieval from various angles.
Don't use this if you only want simple database access; for instance, if you already have an ISRC code, running get_track_by_isrc is more direct than using a full search. Also, don't rely on it for filtering by genre or release year, as those advanced filters aren't available in the current toolset. Use this when identification and metadata breadth are your top priorities.
Questions you might have
How does the ACRCloud Music Recognition MCP work with URLs? +
It takes an audio file URL and runs advanced fingerprinting to identify the song. It tells you the artist, album, and track details without needing manual searching.
What is the difference between search_tracks and identifying from a URL? +
identify_music_from_url works with actual audio samples to figure out the song. search_tracks requires you to provide keywords like names or lyrics, so it searches existing records.
Can I use get_track_by_isrc for everything? +
While highly accurate, get_track_by_isrc only works if you already have the unique International Standard Recording Code. It's a lookup tool, not an identification tool.
Does ACRCloud Music Recognition support finding songs by lyrics? +
Yes, use search_tracks. You can provide partial lyric fragments, and the MCP will query the database to find matching tracks.
What credentials do I need when using the `identify_music_from_url` tool? +
You must provide your ACRCloud Access Key and Secret to connect this MCP. These keys are generated in your personal ACRCloud dashboard, not here. Your agent uses them to authenticate every request, ensuring only authorized calls reach the service.
Are there rate limits when calling multiple tools like `search_albums` or `search_artists`? +
Yes, ACRCloud enforces usage limits for API requests. The MCP handles standard throttling and returns specific HTTP error codes if you exceed your allowed calls per minute. You'll need to check the official documentation for exact quotas.
When I run `get_track_by_isrc`, what specific metadata fields should I expect in the response? +
The response includes comprehensive data points like full artist name, release date, album title, and multiple streaming links. You get structured JSON containing confidence scores and platform IDs for Spotify, YouTube, and more.
What happens when `search_tracks` or other search tools fail to find a match? +
The tool doesn't throw an error; it returns a clean, empty data structure. Your AI client can then check for null results and prompt the user with helpful suggestions instead of failing entirely.
How do I get ACRCloud credentials? +
Sign up at the ACRCloud Console, create a 'Music Recognition' project, and you will find your Access Key, Secret, and Host in the project settings.
Which audio formats are supported for identification? +
ACRCloud supports most common audio formats including MP3, WAV, AAC, and OGG. The agent will download the file from the provided URL and send it for fingerprinting.
Can I find the ISRC code for a specific track? +
Yes! When you identify a song or search for metadata, the acr_music_search tool returns industry-standard identifiers like ISRC, allowing you to track specific recordings across different systems.
We've already built the connector for ACRCloud Music Recognition. Just plug in your AI agents and start using Vinkius.
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