Metriport VS TranscriptFetch
Compare Metriport VS TranscriptFetch and see what are their differences
Next-generation real-time digital avatar infrastructure | Affordable, Accessible, Alive
featured
Metriport
Docus.ai
Rita Personal Data
Hecco AI
SelectStar
Vedex
Katonic MLOps Platform
Proxy Manager for Google Chrome
TranscriptFetch
SocialFetch.dev
TranscriptAPI.com
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.
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.
text field for feeding a model or a search indexsegments array with per-cue start times and durations, so subtitles and jump-to-moment links are a formatting step rather than another integration100 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.
Metriport TranscriptFetchNo TranscriptFetch videos yet. You could help us improve this page by suggesting one.
TranscriptFetch's answer:
Most short-form video has no caption track to download. TikTokโs 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.
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.
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.
TranscriptFetch's answer:
It started with discovering there is no good way to get the text of a video. YouTubeโs official Data API will confirm a caption track exists and then refuse to hand it over, because captions.download requires the video ownerโs 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.
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.
Based on our record, Metriport seems to be more popular. It has been mentiond 24 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.
โข Cronometer With these initial integrations, we plan to add many more to this list, including Garmin, Apple Health, and Google Fit in the near term. We work very closely with our customers, so if thereโs an integration you need thatโs not currently on roadmap, weโre more than happy to add it and build it into our API. Because weโre also open-source, developers can fork our code and build their own custom... - Source: Hacker News / over 3 years ago
As some of you may have already saw, over the summer we made the difficult decision to pivot our business, and go after a similar problem in the healthcare space, with the main goal to make healthcare data more accessible. For those interested in finding out more about this, you can check out this recent write up about us, or check out our newly revamped website. Source: over 3 years ago
Sweet, feel free to check it out here and let us know what you think :). Source: about 4 years ago
My friend and I are both Apple Watch owners and we made an app this year to get better insights into our data, but now we're looking at other wearables out there to see what else is possible in terms of unique data and insights. Curious to see hear from those in this community of why they chose to go with Whoop! Source: about 4 years ago
5 months ago, we made a post here telling the story of what we learned from quitting our jobs to build and release Metriport from scratch in 11 weeks. We wanted to follow up since that post, as a lot has happened since then, including getting featured on TechCrunch and more recently getting accepted into Y Combinator's S22 batch of startups. Source: about 4 years ago
Docus.ai - Upload health records, consult both AI & Top Human Doctors
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.
Rita Personal Data - Collect, view and control your data
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.
Hecco AI - Your personal health intelligence engine
SelectStar - Select Star (https://selectstar.com) is an automated data discovery platform that analyzes & documents your data.