transcribe_chapterize_media
Transcription and chapterization of long-form media (YouTube, podcasts, direct audio/video) for content marketing teams, podcast publishers, edu tech, journalists and accessibility/compliance. Pipeline: • YouTube → timedtext captions (keyless) + oEmbed metadata + native timecode chapters from des...
This record as markdown: /tools/io-github-getgapup-gapup-mcp/transcribe-chapterize-media.md
What transcribe_chapterize_media does on Gapup Mcp
AI agents call transcribe_chapterize_media to retrieve information from Gapup Mcp without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
url | string | Yes | YouTube URL, podcast RSS feed URL, or direct MP3/MP4 URL. Example: "https://www.youtube.com/watch?v=jNQXAC9IVRw" |
lang | string | — | ISO 639-1 language hint (e.g. "en", "fr", "de"). Default "auto". |
async | boolean | — | If true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client ti |
chapters_max | number | — | Maximum number of chapters. Default 8. |
output_format | string | — | Transcript format. Default "json". |
include_summary | boolean | — | Include extractive summary. Default true. |
Parameters from the server's own tool schema.
Why transcribe_chapterize_media is rated Low
This tool retrieves and processes existing media content (captions, metadata, RSS feeds) to produce transcripts and chapter markers. It reads/fetches data from external sources without creating, modifying, or deleting any data. The pipeline is entirely read-oriented: fetching captions, parsing RSS, and applying NLP segmentation. Misuse potential is low as it only consumes publicly available media metadata.
From the tool's definition Transcription and chapterization of long-form media (YouTube, podcasts, direct audio/video)... YouTube → timedtext captions (keyless) + oEmbed metadata... Podcast RSS → episode description + duration + timecodes
Risk signalsAccepts URL/endpoint input (url)
Attacks that exploit this kind of access
The rule that runs transcribe_chapterize_media safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Gapup Mcp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For transcribe_chapterize_media, this is the rule to start with:
transcribe_chapterize_media is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Gapup Mcp, apply this rule, and every transcribe_chapterize_media call is checked against it from then on.
Questions about transcribe_chapterize_media
Transcription and chapterization of long-form media (YouTube, podcasts, direct audio/video) for content marketing teams, podcast publishers, edu tech, journalists and accessibility/compliance. Pipeline: • YouTube → timedtext captions (keyless) + oEmbed metadata + native timecode chapters from description • Podcast RSS → episode description + duration + timecodes if embedded in show notes • Direct media → partial (requires Whisper API via OPENAI_API_KEY + force_whisper:true) • Chapters: native YouTube timecodes preferred; heuristic TF-IDF segmentation as fallback • Summary: extractive TF-IDF top-sentences (no LLM required) • Language detection: character-set heuristic (CJK→zh, kana→ja, hangul→ko, accents→fr/de/es) Output formats: json (full structured object) | text (plain transcript) | srt | vtt SLA: ≤15s budget total. Cache: 24h TTL. It is categorised as a Read tool in the Gapup Mcp MCP Server, which means it retrieves data without modifying state.
transcribe_chapterize_media accepts 6 parameters: url, lang, async, chapters_max, output_format, include_summary. Required: url. The full parameter table on this page comes from the server's own tool schema.
Register the Gapup MCP server in PolicyLayer and add a rule for transcribe_chapterize_media: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Gapup Mcp. Nothing to install.
transcribe_chapterize_media is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the transcribe_chapterize_media rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for transcribe_chapterize_media. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
transcribe_chapterize_media is provided by the Gapup MCP server (https://mcp.gapup.io/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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