pepys-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| PEPYS_API_KEY | Yes | Your Pepys API key (pk_live_…) | |
| PEPYS_API_BASE | No | Base URL for the Pepys API (default https://pepys.co/api/v1) | https://pepys.co/api/v1 |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| prompts | {
"listChanged": true
} |
| resources | {
"listChanged": true
} |
| completions | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| transcribeA | Transcribe hours-long audio or video into an accurate, speaker-labeled (diarized), timestamped transcript with correctly-timed SRT/VTT captions – work a general model can't do on a raw file. Accepts a file_ref from upload_file or a url (YouTube, podcast episode, RSS feed, Google Drive/Dropbox share). Audio is never used to train models. Returns { job_id, status }; fetch the result with get_transcription. |
| get_transcriptionA | Fetch a transcription by job_id: full text, per-speaker timestamped segments, summary, duration_seconds, billed_minutes, and language. Set wait_ms (up to 25000) to long-poll so short clips come back in one call; otherwise poll until status is 'done'. |
| upload_fileA | Upload local audio/video the agent is holding (as base64 bytes or a file path) and get back a file_ref to pass to transcribe. Use this when the media has no public URL. Requires the Pepys R2 storage backend. |
| list_transcriptionsA | List this account's recent transcription jobs with their job_id, status, title, and duration, so you can resume, fetch, or export an earlier result instead of re-transcribing. |
| list_podcast_episodesA | Given a podcast RSS feed or Apple Podcasts show URL, list its episodes (title, publish date, episode_guid, audio_url) so you can pick exactly which one to transcribe. |
| transcribe_podcast_feedA | Batch-transcribe a whole podcast feed in one call – fan out every episode, or the latest N, to individual jobs. Returns a set of job_ids. Paid capability (throughput/abuse gate). |
| export_transcriptA | Export a finished transcript as SRT, VTT, TXT, Markdown, or JSON, with correct caption timings. Segment-level export is free; word-level-timed export (word_level:true) is a paid unlock. (DOCX/PDF are available in the Pepys web app.) |
| search_transcriptA | Search inside a long transcript for a phrase and get back only the matching timestamped segments – locate a quote or topic in an hours-long recording without loading the whole transcript into context. |
| get_credit_balanceA | Return the account's remaining transcription credits (in minutes) so you can check headroom before starting a large batch and avoid running out mid-run. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| transcribe_and_summarize | Transcribe a recording with Pepys and produce a structured summary. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 9 tools
Each tool targets a distinct operation: uploading, transcribing (single/batch), fetching results, exporting, searching, listing, and credit checking. No functional overlap exists, allowing clear selection.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., get_transcription, list_transcriptions, upload_file). The verb transcribe is used alone for the primary action, but its derived tools (transcribe_podcast_feed) remain consistent.
With 9 tools, the set is well-scoped for a transcription server. Each tool serves a distinct and necessary purpose without redundancy, fitting the typical optimal range of 3-15 tools.
The tool set covers the full transcription workflow: upload, transcribe (single and batch), fetch, export, search, and credit management. The only minor gap is the absence of a delete/reset tool, but this is not essential for the core use case.