Software Alternatives, Accelerators & Startups

ListenBrainz VS TranscriptFetch

Compare ListenBrainz VS TranscriptFetch and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

ListenBrainz logo ListenBrainz

Open source music website that allows users to import their listen history.

TranscriptFetch logo TranscriptFetch

Video & web data API for AI: transcripts from YouTube, TikTok, Instagram, plus any page as clean Markdown. Falls back to AI transcription when captions are missing. Built for RAG and agents.
  • ListenBrainz Landing page
    Landing page //
    2023-06-10
  • TranscriptFetch Home
    Home //
    2026-08-01
  • TranscriptFetch Dashboard
    Dashboard //
    2026-08-01

TranscriptFetch is one API for getting text out of video and web content.

Send a URL from YouTube, TikTok, Instagram, X or Facebook and get back clean, timestamped text. Send any web page and get clean Markdown. One endpoint, one response shape, one API key.

The part that actually matters

Most short-form video has no caption track to download. TikTok's auto-captions are opt-in per upload, Instagram never publishes a downloadable track, and a large share of captions on both platforms are burned into the video frames where no parser can read them.

When there is no caption track, TranscriptFetch transcribes the audio instead. Same endpoint, same response, so your code never branches on which method produced the text.

What you get back

  • A joined text field for feeding a model or a search index
  • A segments array with per-cue start times and durations, so subtitles and jump-to-moment links are a formatting step rather than another integration
  • Consistent output whether the text came from captions or speech recognition

Built for pipelines and agents

  • MCP server so Claude, Cursor and other MCP clients can fetch transcripts as a tool mid-conversation
  • Python and JavaScript SDKs
  • Batch endpoint for up to 50 videos in a single call
  • Channel, playlist and keyword-search endpoints for ingesting at scale

Pricing

100 free credits on signup, no card required. One credit per successful response. Failed, blocked and empty results are never charged, which matters on short-form video where a meaningful share of any batch is music with no speech in it.

ListenBrainz

Pricing URL
-
$ Details
Release Date
-

TranscriptFetch

$ Details
freemium $5.0 / Monthly (Basic, 500 credits)
Release Date
2026 May
Startup details
Country
United States
State
Texas
Founder(s)
Chandler Casey
Employees
1 - 9

ListenBrainz features and specs

  • Open Source
    ListenBrainz is an open-source platform, allowing users to contribute to its development and improvement.
  • Privacy-Focused
    The platform emphasizes user privacy by allowing anonymity and providing transparency about collected data.
  • Community Driven
    As part of the MetaBrainz Foundation, ListenBrainz benefits from a community-driven approach, encouraging collaboration and innovation.
  • Integration with MusicBrainz
    It integrates seamlessly with MusicBrainz, providing enriched data insights and comprehensive music metadata.
  • Data Export
    Users can export their listening data, offering flexibility in how they handle their music listening history.

Possible disadvantages of ListenBrainz

  • Less Mainstream Integration
    Compared to other music tracking services, ListenBrainz might have limited integration with popular music streaming platforms.
  • Complex Setup
    Some users might find the setup process and integration with their existing music players non-intuitive or complex.
  • Limited Standalone Features
    On its own, ListenBrainz may lack some features users expect from more comprehensive music analytics services.
  • Smaller User Base
    The platform might have a smaller community of users compared to more established commercial music services, which could impact social features.

TranscriptFetch features and specs

  • Fast Transcript Retrieval
    TranscriptFetch is designed to quickly extract transcripts from YouTube videos, saving users time compared to manually transcribing content.
  • Simple Interface
    The tool typically offers a straightforward, user-friendly interface where users can paste a video link and receive a transcript without complicated steps.
  • Useful for Content Repurposing
    Transcripts can be used to create blog posts, subtitles, summaries, or social media content, making it valuable for content creators and marketers.
  • Time-Saving for Research
    Researchers and students can use transcripts to quickly review video content without watching the entire video, improving efficiency.
  • Accessibility Support
    Providing text versions of video content can help make information more accessible to people with hearing impairments or those who prefer reading.

Category Popularity

0-100% (relative to ListenBrainz and TranscriptFetch)
Music Streaming
100 100%
0% 0
Transcription
0 0%
100% 100
Music
100 100%
0% 0
AI
0 0%
100% 100

Questions & Answers

As answered by people managing ListenBrainz and TranscriptFetch.

What makes your product unique?

TranscriptFetch's answer:

Most short-form video has no caption track to download. TikTokโ€™s auto-captions are opt-in per upload, Instagram never publishes a downloadable track, and many captions on both are burned into the video frames where no parser can read them. TranscriptFetch transcribes the audio when no caption track exists, on the same endpoint, with the same response shape. Your code never branches on which method produced the text. It also covers YouTube, TikTok, Instagram, X and Facebook plus any web page as clean Markdown, so a pipeline spanning several sources is one integration rather than five.

Why should a person choose your product over its competitors?

TranscriptFetch's answer:

Three reasons. Coverage: one API key and one response shape across five video platforms and the open web, instead of stitching together a library per platform. Reliability: requests run through rotating infrastructure, so code that works locally keeps working from a server, which is where most open-source approaches break. Billing that matches reality: one credit per successful response, with failed, blocked and empty results never charged. That last point matters on short-form video, where a meaningful share of any batch is music with no speech in it. There is also an MCP server, so AI agents can fetch transcripts as a tool without a custom integration.

How would you describe the primary audience of your product?

TranscriptFetch's answer:

Developers and technical teams building on video and web content. The common cases are RAG and retrieval pipelines that need video as text, AI agents that need to read a link mid-conversation, content teams repurposing short-form video at scale, and media monitoring and research tools. It is an API first, so the buyer is usually the person writing the integration rather than an end user. The free browser tools exist for one-off transcripts and for evaluating output quality before writing any code.

What's the story behind your product?

TranscriptFetch's answer:

It started with discovering there is no good way to get the text of a video. YouTubeโ€™s official Data API will confirm a caption track exists and then refuse to hand it over, because captions.download requires the video ownerโ€™s OAuth token. The popular open-source libraries work until you deploy them, at which point platforms start refusing datacenter IPs. And YouTube is the easy case: TikTok and Instagram publish no caption file at all. Every workaround solved one platform, worked locally, and broke in production. TranscriptFetch is the version that handles the failure cases as first-class behaviour rather than edge cases.

Which are the primary technologies used for building your product?

TranscriptFetch's answer:

Next.js with TypeScript and Tailwind on the front end and API layer, Clerk for auth with SHA-256 hashed API keys, Neon Postgres with Drizzle ORM, Redis for caching, and Stripe for billing. The extraction layer is a Python and FastAPI service. Speech-to-text uses Whisper-class models. The MCP server is published in the official Model Context Protocol registry with a DNS-verified namespace.

User comments

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Social recommendations and mentions

Based on our record, ListenBrainz seems to be more popular. It has been mentiond 47 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

ListenBrainz mentions (47)

  • I archived 10 years of memories using Spotify
    Https://listenbrainz.org/ or last.fm are better if you actually want to track these things. - Source: Hacker News / 7 months ago
  • 2002: Last.fm and Audioscrobbler Herald the Social Web
    Https://listenbrainz.org/ is an open source scrobbler, with the advantage that it leverages the musicbrainz database and connects listens to artist and track IDs instead of names, avoiding duplicate confusion. You can keep last.fm and submit to both of you like. - Source: Hacker News / 8 months ago
  • Goodbye, Slopify
    For people moving off Spotify, have a look at https://listenbrainz.org. You can sync your listens to there and it will give you weekly recommendations. From my experience so far they are decent. Note they don't host songs themselves, but will auto-search youtube/bandcamp/etc. And play the closest match. So YMMV. - Source: Hacker News / over 1 year ago
  • The Open Music Encyclopedia
    It really is an incredible resource, and Picard is a wonderful app. Very satisfying getting a library properly tagged! Takes a while, but totally worth it. Shoutout to ListenBrainz as well, their scrobbling service: https://listenbrainz.org/. - Source: Hacker News / almost 2 years ago
  • Analyzing Spotify Stream History
    There's also ListenBrainz, run by the MusicBrainz org, which offers similar functionality without API restrictions or other paid features that Last.FM tries to push. https://listenbrainz.org/ If you wish to use your scrobble data at all programmatically this is a far better tool to use. - Source: Hacker News / over 2 years ago
View more

TranscriptFetch mentions (0)

We have not tracked any mentions of TranscriptFetch yet. Tracking of TranscriptFetch recommendations started around Aug 2026.

What are some alternatives?

When comparing ListenBrainz and TranscriptFetch, you can also consider the following products

Last.fm - The world's largest online music service. Listen online, find out more about your favourite artists, and get music recommendations, only at Last.fm

SocialFetch.dev - Social media scraping API for public profiles, posts, comments, videos, transcripts, and metrics from TikTok, Instagram, YouTube, X, LinkedIn, and more. Pay-as-you-go credits, 100 free to start.

MusicBrainz - A community-maintained open source database and encyclopedia of music information.

TranscriptAPI.com - Get YouTube video transcripts with a simple API call or through Model Context Protocol. Fast, reliable, and easy to integrate into your applications.

stats.fm - With the click of a button you'll be logged with your Spotify account and you'll instantly gain access to a valhalla of cool stats and insights.

Maloja - Simple self-hosted music scrobble database to create personal listening statistics.