Can AI replace TranscriptAPI?

KINDA · weekend project

price $5/moyou'd save $60/yrbuild time one sittingcategory 🛠️ dev toolsreplaced by 0 peoplebuild unverified

The happy path is genuinely a one-sitting build: the open-source youtube-transcript-api library fetches a caption track in a few lines, and wrapping it in FastAPI gives you a working personal endpoint. The honest gap is reliability. YouTube rate-limits and IP-blocks caption scraping at any real volume, so the DIY version works until it suddenly does not, and there is no fix without a rotating proxy pool you must rent and operate. The paid product is not selling the parsing; it is selling the unblocked pipe, plus search and playlist endpoints on top.

the prompt

Build me a small YouTube transcript API service, a personal stand-in for TranscriptAPI.
Requirements:
- Python 3.11 stack: FastAPI, uvicorn, and the youtube-transcript-api library; no
  database, one file plus a README is fine.
- GET /transcript?video=<id-or-url>: extract the video id, fetch the caption track,
  return JSON with the full text plus timestamped segments.
- Support lang= with a sensible fallback to the first available track, and report
  which track was actually used in the response.
- Clean JSON errors: 404 when captions are disabled or missing, 502 when YouTube
  blocks the fetch; never a bare 500.
- Read an optional comma-separated PROXIES var from .env and rotate per request;
  with none set, run direct.
- GET /health returning version and uptime.
- A tiny CLI example in the README: curl the endpoint, jq out the text.
- Keep it stateless and private: no accounts, no API keys, no telemetry, no storage.
- README must be honest about the failure mode: at any real volume YouTube
  rate-limits and IP-blocks caption fetches, and this build has no defense.
- Out of scope, deliberately: the rotating proxy pool and anti-blocking
  infrastructure, channel/playlist/search endpoints, bulk throughput, and SLAs.
  That reliability layer is the thing the paid product actually sells.

$ open in your agent (prompt prefilled, you press enter) or copy it raw

why people still pay

The parse was never the hard part. Holding a durable, unblocked pipe into YouTube captions at volume is an operations problem that costs real money to run, and buying it for 5 USD a month is cheaper than renting proxies and babysitting them.

what you lose

xstaying unblocked when YouTube rate-limits caption fetches

xsearch, channel and playlist endpoints

xreliability at bulk volume

xan SLA and support when YouTube changes something

prior art · use these instead of building, if you'd ratheryoutube-transcript-apiopen-source Python library for the core caption fetch↗