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lsmman

io.github.lsmman/fetchive

Official
by lsmman

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
FETCHIVE_DB_PATHNoWhere your archive index and transcript cache live~/.fetchive/fetchive.db
FETCHIVE_LANGUAGESNoPreferred caption languages, best firstko,en
FETCHIVE_TRANSPORTNohttp for a hosted deploymentstdio
FETCHIVE_ENABLE_STTNoSet to false to never fall back to speech-to-texttrue
FETCHIVE_BATCH_WORKERSNoConcurrent extractions. YouTube dislikes more3
FETCHIVE_WHISPER_MODELNoLarger is slower and more accuratebase
WEBSHARE_PROXY_PASSWORDNoEnables the proxy step. Without these it is skipped
WEBSHARE_PROXY_USERNAMENoEnables the proxy step. Without these it is skipped
FETCHIVE_MAX_STT_DURATIONNoRefuse to transcribe anything longer, in seconds3600
FETCHIVE_QUOTE_WORD_LIMITNoLongest verbatim quote allowed out of the server15

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

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
archive_batchA

Parse every link out of pasted text (a KakaoTalk or Slack export, a bare list, anything), skip what is already archived, extract YouTube transcripts, and prepare a page payload for each one. Returns a batch ID immediately; extraction runs in the background. Poll get_batch_status.

get_batch_statusA

Progress for a running or finished batch. When state is 'completed', ready_to_save holds one payload per item that is ready to write to the workspace, and items explains anything that failed or was skipped.

ingest_linksA

Pull every URL out of a text blob and classify it by platform, without archiving anything. Useful for showing the user what was found first.

extract_youtube_scriptA

Get the transcript for one YouTube video, trying caption APIs, yt-dlp, and local speech-to-text in turn. Reports which method worked and why the others did not. Cached, so asking twice is free.

summarise_pendingA

Write summaries and tags for items a batch has extracted but not yet summarised, using your own model. Call this after archive_batch reports items in needs_summary, and call it repeatedly until remaining reaches zero. Works a few items at a time on purpose: a thousand transcripts cannot go through one request.

add_summaryA

Record a summary and tags for one extracted item. Use this after summarise_pending hands you a prompt to write yourself. The summary is checked for copying the source before it is kept, and the item then appears in ready_to_save.

search_archiveA

Full-text search across everything archived — transcripts and article bodies, not just titles. Use this to answer questions about what the user has already saved, or to find the source of a half-remembered idea. Returns matching excerpts with the workspace page link where one was recorded.

check_duplicateA

Has this URL already been archived? Matches the canonical form of the URL, and if a title is supplied also compares it against archived titles to catch re-uploads and mirrors.

record_archivedA

Tell Fetchive that a URL has been saved to the workspace, and where. Call this after every successful save — it is the only way duplicate detection learns what exists.

forget_archivedA

Remove a URL from the archive index, so it counts as new again. Use when the page it points to was deleted from the workspace. Does not touch the workspace itself.

format_for_notionA

Shape one link into a page payload: properties, the workspace's existing tag vocabulary, and instructions for classifying against it. Quotes are capped and transcripts are never included verbatim.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

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