Questions about PodPast.ai
35 questions covering what PodPast.ai is, who it's for, how integrations work, technical architecture, pricing, and privacy.
What is PodPast.ai?
- What is PodPast.ai?
- PodPast.ai is a personal knowledge vault that ingests YouTube videos and podcast RSS feeds, transcribes every episode, and exposes the full corpus to Claude and ChatGPT via semantic search and a Model Context Protocol (MCP) server. You can query across everything you've ever listened to, with timestamped citations back to the source episode.
- Who is PodPast.ai built for?
- PodPast.ai is built for knowledge workers who consume large volumes of long-form audio and video — researchers, journalists, founders, investors, content creators, and Claude Pro users who want their podcast library integrated into their LLM workflow. The target user listens 5–15 hours per week and regularly needs to locate a specific quote or claim they heard months ago.
- What problem does PodPast.ai solve?
- The average knowledge worker spends 11.2 hours per week listening to podcasts but retains less than 20% of what they hear without a retrieval system. PodPast.ai solves the retrieval problem: every word you've ever listened to becomes instantly queryable, with citations that point back to the exact moment in the original episode.
- When was PodPast.ai founded?
- PodPast.ai was founded in 2025 and is based in the United States. The product is built on FastAPI, Supabase with pgvector, Deepgram nova-2, Claude Sonnet via MCP, and a Next.js frontend deployed on Vercel. The API is hosted on Railway.
- Is PodPast.ai affiliated with Anthropic, Google, or any major platform?
- No. PodPast.ai is an independent product. It uses Claude's API and the Model Context Protocol, which is an open standard developed by Anthropic, but PodPast.ai is not affiliated with or endorsed by Anthropic. It uses YouTube's public caption API but is not affiliated with Google or YouTube.
Use cases
- How do researchers use PodPast.ai?
- Researchers add expert interview podcasts, conference talk recordings, and academic lecture series to their vault. When writing papers or reports, they can query across hundreds of hours of source material to find specific claims, locate the expert who made a particular argument, and generate a citation with the episode name and timestamp — ready to include in a literature review or footnote.
- How do journalists use PodPast.ai?
- Journalists add their own recorded interviews as well as public podcasts relevant to their beat. PodPast.ai lets them verify what a specific source said in a past interview, find every episode where a particular person was mentioned, and search across competing coverage to identify narrative gaps. The timestamp citations are particularly useful for fact-checking — you can go directly to the original audio.
- How do founders and VCs use PodPast.ai?
- Founders and investors add podcasts covering market analysis, founder interviews, and investor commentary. They can query across their entire research library — 'what have investors said about AI infrastructure margins over the past 6 months?' — and get synthesized answers with citations. This is more efficient than re-listening or reading transcripts manually.
- How do content creators use PodPast.ai?
- Content creators add their own podcast or YouTube back-catalogue and use PodPast.ai to avoid repeating themselves. Before recording a new episode, they can check whether they've already covered a topic in detail, pull exact quotes from prior episodes to reference, and find timestamps for clip creation without scrubbing through raw audio.
- How do students use PodPast.ai?
- Students add recorded lectures, course podcasts, and educational YouTube channels. PodPast.ai creates a searchable knowledge base across an entire semester or course of study. When revising for exams or writing essays, students can locate a specific explanation or definition without re-watching lengthy lecture recordings.
- How do Claude Pro users specifically benefit from PodPast.ai?
- Claude Pro users benefit most from the MCP integration. Instead of pasting transcript excerpts manually into Claude, the PodPast MCP server lets Claude retrieve relevant transcript chunks automatically when you ask a research question. This effectively gives Claude access to your entire podcast library as a persistent knowledge source, without consuming your context window with irrelevant content.
- Can PodPast.ai be used for company meeting recordings or internal audio?
- Not currently. PodPast.ai is designed for public podcast RSS feeds and YouTube channels. Support for private audio file uploads (mp3, mp4, wav) is on the roadmap for a future release. Until then, only publicly accessible feeds and YouTube URLs can be added to a vault.
Claude & ChatGPT integration
- How does the Claude MCP integration work?
- PodPast.ai runs a local MCP server that communicates with Claude Desktop via stdio transport. Once configured, Claude can call four tools: search_pod (semantic search), ask_pod (grounded answer synthesis), add_to_pod (add a new feed), and get_pod_info (vault status). Claude decides when to call these tools based on your conversation — you don't have to invoke them manually.
- Does PodPast.ai work with Claude Projects?
- Yes. MCP servers configured in Claude Desktop are available within Claude Projects conversations. You can create a Project focused on a specific research area, add relevant documents to the Project, and simultaneously have access to your full PodPast vault via MCP — giving you both curated and broad retrieval in one interface.
- Does PodPast.ai work with Claude Code?
- Yes. Claude Code reads the same MCP configuration as Claude Desktop. This is useful for engineering-adjacent research tasks — for example, indexing technical podcasts about system design or database architecture and then querying them from within a Claude Code session while working on related code.
- Does PodPast.ai work with ChatGPT Plus?
- Not yet. Native Claude MCP integration is the primary integration channel. ChatGPT support via a Custom GPT action connected to the PodPast REST API is in development and planned for a future release. Sign up for the mailing list to be notified when it ships.
- What data does Claude see when it uses PodPast.ai?
- Claude receives only the transcript chunks that PodPast.ai returns in response to a specific search query — typically 3–10 chunks of 150–200 words each, with metadata (episode name, feed name, timestamp, URL). Claude does not have access to your entire vault in a single context window; it receives retrieval results on demand per query.
- Can I use PodPast.ai without Claude?
- Yes. PodPast.ai has a web-based search interface that lets you run semantic searches and view results directly in the browser, without Claude. The REST API is also available on the Pro plan for integration with any tool or workflow. Claude MCP is the most seamless integration but is not required to use the product.
- Is the MCP server open source?
- The MCP server package (@podpast/mcp-server) is available on npm and the source is published on GitHub. It is provided under the MIT license. You can inspect exactly what data is sent to Claude and what calls are made to the PodPast API.
Technical
- What transcription model does PodPast.ai use?
- PodPast.ai uses a priority stack: YouTube's built-in captions and RSS transcript tags are fetched first (both free). If no pre-existing transcript is available, Deepgram nova-2 is used for audio-only episodes. Free tier accounts receive 120 Deepgram credit minutes per month. nova-2 achieves 85–92% word accuracy on conversational speech.
- What embedding model does PodPast.ai use for semantic search?
- PodPast.ai uses OpenAI's text-embedding-3-small model to generate 256-dimensional vector embeddings for each transcript chunk. The same model is used to embed search queries at retrieval time, ensuring consistent semantic space. Embeddings are stored in a Supabase PostgreSQL database using the pgvector extension.
- How large are the transcript chunks?
- Each chunk is approximately 150–200 words, aligned to sentence boundaries where possible. Chunks overlap by about 30 words to prevent relevant content from being split across chunk boundaries. Each chunk stores its start timestamp, end timestamp, episode ID, feed ID, and speaker label (when speaker diarization is available from Deepgram).
- What is the technical stack behind PodPast.ai?
- Backend: FastAPI (Python) on Railway. Database: Supabase PostgreSQL with pgvector extension for vector search. Transcription: Deepgram nova-2. Embeddings: OpenAI text-embedding-3-small. Payments: Stripe. Frontend: Next.js 15 App Router on Vercel. MCP server: TypeScript npm package. The backend API is at api.podpast.ai.
- Does PodPast.ai store audio files?
- No. Audio files are never downloaded or stored. For YouTube videos, only the caption track text is fetched. For audio-only RSS episodes requiring Deepgram, the streaming URL is passed directly to Deepgram's API over HTTPS and discarded immediately after transcription. PodPast.ai stores only the resulting transcript text and vector embeddings.
- How many simultaneous transcriptions can run at once?
- Free tier: 5 simultaneous transcriptions. Solo and Pro tiers: higher concurrency limits with priority queue access. For large feeds with hundreds of episodes, transcription runs in parallel batches. You receive an in-app notification when each batch completes.
- What RSS feed formats does PodPast.ai support?
- PodPast.ai supports standard podcast RSS 2.0 feeds with enclosure elements. It also reads the iTunes podcast namespace extensions for episode metadata. Atom feeds are not currently supported. For RSS feeds that include a transcript:url or podcast:transcript tag (as defined by the Podcasting 2.0 namespace), PodPast.ai fetches the transcript directly without using Deepgram.
Pricing
- What does PodPast.ai cost?
- Free: $0/month — unlimited feeds, 120 Deepgram minutes, full Claude MCP access. Solo: $12/month or $99/year — 600 Deepgram minutes, priority queue, weekly RSS polling. Pro: $24/month or $199/year — unlimited Deepgram minutes, REST API, team sharing for up to 3 seats. No credit card required for the free tier.
- What counts as a Deepgram credit minute?
- One Deepgram credit minute equals one minute of audio processed by Deepgram nova-2. YouTube captions and RSS podcast:transcript tags are free and do not count against your minute balance. Most mainstream podcasts and all YouTube videos have free caption sources available. Deepgram minutes are only consumed for audio-only feeds with no pre-existing transcript.
- Is there a refund policy?
- Yes. You may request a full refund within 7 days of your first paid charge if you have consumed fewer than 100 Deepgram minutes in that billing period. Contact support@podpast.ai. Annual plan refunds are calculated on a pro-rated basis within 30 days of purchase.
- Is there a founders' lifetime deal?
- A founders' lifetime deal is planned for the first 100 users who upgrade to the Pro plan before the public launch. Details will be sent to the mailing list. Sign up on the homepage to be notified when the deal opens.
Privacy & legal
- Where is my data stored?
- Transcripts and vector embeddings are stored in a Supabase PostgreSQL database hosted in the United States. Audio files are never stored — PodPast.ai processes transcription in real time and discards the audio URL immediately. You can delete your entire vault and account data at any time from your account settings.
- Does PodPast.ai share my transcript data with third parties?
- No, with two narrow exceptions: Deepgram processes the audio URL for transcription (audio is not stored by Deepgram after processing), and OpenAI processes the transcript text to generate embeddings. Neither provider stores your data beyond the duration of the API call. PodPast.ai does not sell, rent, or share transcript data with any other party.
- Is it legal to ingest copyrighted podcast content?
- PodPast.ai operates as a personal knowledge tool for private use, analogous to taking notes while listening. Each user is responsible for ensuring they have the right to ingest content they add. PodPast.ai vaults are private by default — transcript data is not made publicly accessible. Public redistribution of copyrighted transcript content via the platform is prohibited by the Terms of Service.
- How does PodPast.ai handle DMCA takedown requests?
- PodPast.ai has a designated DMCA agent and follows the safe harbor process under 17 U.S.C. §512. Copyright holders may submit takedown notices to dmca@podpast.ai with the required elements as defined in §512(c)(3). Valid takedowns result in removal of the specified content from the platform. See the DMCA policy page for the full process.
- Can I delete my account and all my data?
- Yes. You can delete your account and all associated data — including transcripts, vector embeddings, feed configurations, and account information — from the Settings → Account → Delete Account page. Deletion is permanent and irreversible. Stripe payment records are retained as required by law but are not linked to your content data after deletion.