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Tanod Podcast Transcript
x402
Tanod Podcast Transcript is a paid API for AI agents from tanod.dev, paid per call via x402, $0.02/call, status unknown (last checked 2026-10-28).
Transcribes a 5–600 second window of a podcast episode from its RSS feed URL, returning timestamped text, SRT, and VTT captions
Price / call$0.02
Success—
StatusUnknown
How this service works
Podcast transcript: transcribe a podcast episode from its RSS feed, a window of up to 10 minutes as text, timed segments, SRT and WebVTT (mlpeek by Tanod, faster-whisper). Use when an agent must transcribe up to 10 minutes of a podcast episode picked from its RSS feed.
Output
A JSON object containing: plain transcript text, SRT and VTT caption strings, an array of timestamped word segments (start/end seconds + text), episode metadata (title, GUID, published date, duration, enclosure URL), show metadata (title, link), detected language and confidence, the Whisper model used, and window metadata (start_s, end_s, duration_s, next_start_s, method, exact flag). A truncated flag indicates if output was cut short.
Example use cases
Transcribe specific podcast moment
“I want to know exactly what was said between minute 60 and 70 of episode 501 of the Lex Fridman Podcast — the RSS feed is https://lexfridman.com/feed/podcast/. Give me the transcript text and the SRT file.”
Translate foreign-language podcast to English
“Can you grab the latest episode of this Spanish podcast (RSS: https://example.com/podcast.xml) and transcribe it in English? I want the full 10-minute window starting from the beginning translated to English.”
Extract captions for podcast clip
“I need VTT captions for the first 5 minutes of the episode titled 'Future of AI' from this podcast feed: https://mypodcast.com/rss.xml — starting at second 0, 300 seconds long.”
Technical details
Endpoint
POSThttps://tanod.dev/v1/audio/podcast-transcript?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to extract spoken content from a podcast episode identified by its public RSS feed URL, especially when you need timestamped captions (SRT/VTT) or want to seek to a specific time window within a long episode. It is ideal for agents that have already located a podcast feed (e.g., via /v1/podcast/search) and need the actual transcript. Prefer this over generic audio-to-text APIs when you need paginated windowed access to long episodes, RSS-native episode selection by GUID or episode number, and built-in English translation — all at a flat $0.02/call rate with no signup.
Side effects
- Invalid or unreachable RSS feed URL returns an error
- Episode not found by GUID, number, or title returns null result
- Audio file unreachable or DRM-protected fails transcription
- start_s beyond episode duration returns empty or error
- duration_s outside 5-600 range is rejected by schema validation
- Conflicting episode selectors (guid + episode_number simultaneously) may cause unexpected episode selection
- Language detection may be inaccurate for short or noisy audio segments
- Byte-range seeking means start_s can be off by a few seconds for VBR audio
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| guid | — | Pick the episode by its feed guid. Use at most one of guid, episode_number and episode_title; none picks the latest episode with audio. |
| season | — | With episode_number: the itunes:season number. |
| start_s | number | Where the window starts, in seconds from the beginning of the episode (default 0). |
| feed_url | string | Public http(s) URL of the show's RSS feed (find it with /v1/podcast/search). |
| language | — | Optional spoken language as an ISO 639-1 code (default: detected). |
| duration_s | integer | Window length in seconds, 5-600 (default 600, the 10-minute limit of one call). |
| episode_title | — | Pick the newest episode whose title contains this text (case-insensitive; an exact title wins). |
| episode_number | — | Pick the episode by its itunes:episode number. |
| translate_to_english | boolean | true: text, segments, srt and vtt in English (Whisper translate). Same price. |
Output
Schema · Response
{
"type": "json",
"example": {
"srt": "1\n01:00:00,000 --> 01:00:01,240\nPlanker won't mind.\n\n2\n01:00:01,240 --> 01:00:04,000\nIn fact, the producers of clinkers,\n\n",
"vtt": "WEBVTT\n\n01:00:00.000 --> 01:00:01.240\nPlanker won't mind.\n\n01:00:01.240 --> 01:00:04.000\nIn fact, the producers of clinkers,\n\n",
"show": {
"link": "https://lexfridman.com/",
"title": "Lex Fridman Podcast"
},
"text": "Planker won't mind. In fact, the producers of clinkers, the labs love when you spend tokens in vain.",
"model": {
"id": "faster-whisper-base",
"source": "Systran/faster-whisper-base",
"compute": "int8",
"revision": "ebe41f70d5b6dfa9166e2c581c45c9c0cfc57b66"
},
"window": {
"note": "the start is located from the file's average bitrate and can be off by a few seconds",
"end_s": 3660.5,
"exact": false,
"method": "byte-range",
"start_s": 3600,
"duration_s": 60.5,
"next_start_s": 3660.5
},
"episode": {
"guid": "https://lexfridman.com/?p=6506",
"link": "https://lexfridman.com/dhh-2/",
"title": "#501 – DHH: Future of Programming, AI, Agentic Engineering, Vibe Coding & Linux",
"season": null,
"episode": null,
"enclosure": {
"url": "https://media.blubrry.com/takeituneasy/ins.blubrry.com/takeituneasy/lex_ai_dhh_2.mp3",
"type": "audio/mpeg",
"length": 249955445
},
"published": "2026-08-26T21:47:04Z",
"duration_s": 19317
},
"language": "en",
"segments": [
{
"end": 3601.24,
"text": "Planker won't mind.",
"start": 3600
},
{
"end": 3604,
"text": "In fact, the producers of clinkers,",
"start": 3601.24
}
],
"operation": "podcast-transcript",
"truncated": false,
"input_bytes": 879899,
"untrusted_content": true,
"language_probability": 0.9996
}
}Tags
x402
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