Ollama
LM Studio
Hugging Face
Jan.ai
LangChain
GPT4All
Claude AI
OpenAI
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.
Ollama TranscriptFetchOllama is recommended for businesses and teams seeking an efficient project management solution. It is especially useful for remote teams, startups, and any organization looking to enhance collaboration and project tracking capabilities.
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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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I didn't want a cloud API key for a side project, so I ran Ollama locally on an old CPU-only laptop. This is where the framework knowledge from above collided with the actual, physical limits of local inference โ and where I learned the most. - Source: dev.to / 5 days ago
Ollama running on the inference box, serving your model of choice. - Source: dev.to / 5 days ago
The problem was the ergonomics. Ollama makes running local models genuinely easy, but I wanted a smoother terminal workflow โ streaming chat that didn't feel clunky, safe file editing, and the ability to run real multi-file agent tasks without leaving my shell. - Source: dev.to / 8 days ago
If you don't have it, get it. Seriously. Itโs the easiest way to get an open source llm mac experience going. Go to ollama.com and download the macOS app. Install it. Simple. - Source: dev.to / 10 days ago
Tools4AI is a 100% Java agentic AI framework that turns any annotated Java method into an AI-callable action. Ollama runs open models like Llama 3.1 and Phi-4 locally and exposes an OpenAI-compatible API. Point Tools4AI at http://localhost:11434/v1 and you get a fully offline, on-premise AI agent โ no data ever leaves your network. In this tutorial we build an insurance claims triage agent that reads a claimant's... - Source: dev.to / 11 days ago
LM Studio - Discover, download, and run local LLMs
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.
Hugging Face - The AI community building the future. The platform where the machine learning community collaborates on models, datasets, and applications.
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.
Jan.ai - Run LLMs like Mistral or Llama2 locally and offline on your computer, or connect to remote AI APIs like OpenAIโs GPT-4 or Groq.
LangChain - Framework for building applications with LLMs through composability