WinDirStat
WizTree
TreeSize
SpaceSniffer
GrandPerspective
Baobab Disk Usage Analyzer
DaisyDisk
ncdu
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.
WinDirStat 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.
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Why not treemaps rather than sunburst visualizations? E.g., https://windirstat.net/? The treemap visualization is more space filling. - Source: Hacker News / about 2 years ago
Something that helps me is If you want to reformat, Winderstat scans your drive and shows you the size of every folder, plus a visual representation so you see whats taking up more space exactly. Source: almost 3 years ago
Not xcom specific advice, but this tool is pretty nifty: https://windirstat.net/. Source: about 3 years ago
Just install https://windirstat.net and search for a big clusters of files. Source: about 3 years ago
There's a utility called WinDirStat that can visualize the storage on your drive to make tracking down large files easier. Source: about 3 years ago
WizTree - WizTree quickly finds the files and folders using the most space on your hard drive. It scans the MFT (Master File Table) instead of crawling the entire disk which makes it very fast.
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.
TreeSize - TreeSize tells you where precious disk space has gone to.
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.
SpaceSniffer - SpaceSniffer is a freeWare (donations are welcome) and portable tool application that lets you understand how folders and files are structured on your disks.
GrandPerspective - GrandPerspective is a small utility application for Mac that graphically shows the disk usage...