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whosaid

by sblattjversion 1.15.2i★ –iRuns on your computer
Registry nameio.github.sblattj/whosaid

Install

Overview

Description from the maker (original English)

Local speaker-attributed transcription and meeting search for Apple Silicon. Audio stays on the Mac.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Design, images & audio

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: WHOSAID_WORKSPACE

You need

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "whosaid": {
      "command": "uvx",
      "args": [
        "whosaid"
      ],
      "env": {
        "WHOSAID_WORKSPACE": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add whosaid --env WHOSAID_WORKSPACE=your-value -- uvx whosaid

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "whosaid": {
      "command": "uvx",
      "args": [
        "whosaid"
      ],
      "env": {
        "WHOSAID_WORKSPACE": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "whosaid": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "whosaid"
      ],
      "env": {
        "WHOSAID_WORKSPACE": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

  • WHOSAID_WORKSPACE env
    Absolute path to the meetings workspace the search tools read

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account sblattj, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Design, images & audioi

  • More stars than 0% of the other 2204 servers in this category
  • Published to the registry more recently than 71% of the other 2204 servers in this category
  • Basic checks equal to or better than 100% of the other 2204 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is whosaid safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.15.2) reached the registry 13 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Figma Context MCP, Claude Real Video, Figma MCP Server

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.

Runs on your computer★ 16,165MITUpdated 5 months ago
Install

Claude Real Video

by HUANGCHIHHUNGLeo

Let any LLM watch a video locally — and search everything it has ever watched.

Runs on your computer★ 2,284MITUpdated 2 months ago
Install

Figma’s official server gives AI your design data so it can turn designs into code or describe them accurately. Connects to Figma’s cloud.

Runs in the cloud★ 2,152Updated 13 months ago
Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

whosaid

Local, speaker-attributed transcription for Apple Silicon — who said what, on your Mac, nothing leaves the machine.

whosaid pairs Whisper speech-to-text with speaker diarization to turn a meeting, interview, call, or podcast recording into a transcript that says *who spoke when* — running fully offline and on-device on an Apple Silicon Mac, with no cloud service, no API keys, and no Hugging Face token. Think of it as whisper + speaker labels + voice-based speaker recognition, in one command.

Example output (meeting.speakers.txt):

[00:00:04] Alice: Thanks for jumping on, I know it's late for you.

[00:00:11] SPEAKER_01: No problem at all, happy to make it work. [00:00:19] Alice: Let's start with the roadmap for next quarter. [00:00:27] SPEAKER_01: Sounds good, I've got a few updates on that.

Why whosaid

  • Meetings, interviews, calls, podcasts — get a transcript where every turn is attributed to a person, not just a wall of text.
  • Privacy by construction — audio, text, and voice embeddings never leave your Mac. The only cloud step is one you opt into: [summarizer] engine = "claude" sends each transcript's text to Anthropic to draft action items. Leave it unset and nothing is sent.
  • Your name on your own lines — a one-time ~45s voice enrollment teaches whosaid your voice, so your turns read as your name instead of SPEAKER_00.
  • Tells you how many people spoke — the number of distinct speakers is auto-detected and reported up front, with per-speaker turn counts and talk time.
  • Speaker cards to identify who's who — for every speaker, whosaid writes a card of that voice's most representative snippets, so you can read a few lines and know who was talking.
  • Remembers people you name — identify a speaker once with whosaid relabel, and their voiceprint is saved to a private local registry so they're auto-named in every future transcript.
  • Fast on long recordings — recordings over ~15 min are diarized in parallel windows and stitched back into consistent speakers by voiceprint, so an 80-minute meeting is minutes, not tens of minutes, recovering the same speakers as a single-pass run.
  • No accounts, no API keys, no Hugging Face token — every model comes from an open, ungated source.
  • Search everything you have recorded. whosaid index builds a local full-text (and, with Ollama, meaning) index over every transcript in a meeting workspace; whosaid search finds the turn, whosaid context shows the minute around it, and whosaid graph answers who committed to what, when. See Search your meetings.
  • Hands-free from Voice Memos. whosaid watch install puts a launchd agent on the Voice Memos folder (or any folder): stop recording, and a few minutes later the meeting is transcribed, summarized, and searchable. See Hands-free ingest.
  • Usable from an AI agent, too. whosaid mcp exposes transcribe, relabel, doctor, and the read-only workspace search tools as MCP tools for Claude Code, Claude Desktop, Kiro, and other MCP clients, with the same local-only guarantee as the CLI.

How it compares

Looking for a MacWhisper, whisperX, or aTrain alternative? If you want speaker-attributed transcription that runs fully offline on Apple Silicon and can put real *names* on voices — not just SPEAKER_00 labels — that's the gap whosaid fills. Here's how it stacks up:

whosaidwhisperXplain mlx-whispercloud transcription APIs
Speaker labelsYesYesNoVaries by provider
Names speakers by voiceYes (enrollment)NoNoNo
Remembers speakers across meetingsYes — persistent local voiceprint registryNoNoNo
Runs fully offlineYesPartial — needs a gated model downloadYesNo
Parallel diarization on long audioYesNo— (no diarization)Varies by provider
Needs an account / tokenNoYes — Hugging Face token for gated pyannote modelsNoYes — API key
Install weightffmpeg + uv, ephemeral environmentstorch + pyannote + the full HF stackmlx-whisper onlyNone (network client only)

Quickstart

git clone https://github.com/sblattj/whosaid && cd whosaid   # get the code

./bootstrap.sh # check deps, download models, install ~/.local/bin/whosaid whosaid enroll # ~45s reading a printed passage — teaches whosaid your voice whosaid path/to/meeting.m4a # transcribe + diarize + label -> meeting.speakers.txt (and friends)

If ~/.local/bin is not on your shell's PATH, add it or invoke the installed command by its absolute path. WHOSAID_INSTALL_DIR=/another/bin ./whosaid install selects another install directory. The installed command is a symlink to the checkout, so updating the checkout updates the command without copying or duplicating the implementation.

whosaid's helper scripts need Python 3.11 or newer, because whosaid.toml is read with tomllib. The launcher picks one interpreter: $WHOSAID_PYTHON if it is set, otherwise the first of python3, python3.13, python3.12 and python3.11 on your PATH that is 3.11+, otherwise uv python find '>=3.11'. It skips the stock macOS python3 (3.9) automatically. If no interpreter qualifies, commands that run Python stop with an error; uv python install 3.13 fixes that. whosaid doctor shows which interpreter was picked.

Homebrew is optional when uv, ffmpeg, and ffprobe are already installed. The launcher and watcher search ~/.local/bin, ~/bin, and ~/homebrew/bin as well as the usual system prefixes. Setup can install a pinned, checksum-verified Apple Silicon uv archive into ~/.local/bin. Homebrew FFmpeg installation requires a bottle; a nonstandard prefix will not silently trigger a source build.

For a Mac without Homebrew, or one where no bottle is available, use:

./bootstrap.sh --build-ffmpeg

This builds pinned FFmpeg source into user-local ffmpeg and ffprobe executables. It needs Apple's Command Line Tools (xcode-select --install if missing), compilation time, and free disk space, but no administrator-owned install prefix or GPG installation. The source archive is checked with macOS shasum against a checksum verified from FFmpeg's signed release. Existing usable tools are retained. Setup then warms the Python environments and downloads the models as usual.

Commands

CommandWhat it does
./bootstrap.sh [--yes] [--build-ffmpeg] (also whosaid setup)Capability check, dependency install, model pre-download, and command installation. --build-ffmpeg selects the verified user-local source build when FFmpeg tools are missing. Idempotent — safe to re-run.
whosaid install [--force]Install/update the command symlink in ~/.local/bin (or WHOSAID_INSTALL_DIR). Refuses to replace an unrelated command, and refuses (unless --force) to install from a checkout under /tmp, /private/tmp, /var/tmp, or $TMPDIR — that symlink would dangle once the OS cleans the temp directory up.
whosaid enroll [Name]Records ~45s from the mic reading a printed passage, saves voices/ .wav. See Speaker identity: enrollment clips vs. the registry.
`whosaid enroll --from FILE [--ss T] [--t D\--to T] [--force]`Extracts a clip from an existing recording instead of the mic (extract → verify → save, no interaction). --ss/--t/--to accept seconds or M:SS/H:MM:SS; same ≥15s/non-silent bar as mic enrollment.
whosaid record [--label L]Foreground mic capture to recordings/ [-label].m4a, then transcribes automatically.
whosaid record --app A [--no-mic] [--label L]Capture one app's audio (Zoom, a browser, ...) through ScreenCaptureKit, plus the mic, to a stereo recordings/ [-label].m4a (left = mic, right = the app), then transcribe it. A is a bundle ID, an app name, or a unique part of either; whosaid record --list-apps lists them. Needs macOS 15+, Xcode Command Line Tools (a small Swift helper, lib/record_app.swift, is built on first use into ~/.cache/whosaid) and Screen & System Audio Recording permission for your terminal. No virtual audio device. --no-mic records the app alone. With --me NAME (or $WHOSAID_OWNER), the voice heard only on the mic is named NAME and app-side voices never are. If macOS kills the capture it restarts in place.
whosaid record --browser [--cdp-port P] [--target T] [--leave-selector CSS] [--max-seconds N] [--leave] [--no-mic] [--into DIR] [--label L]Record one browser meeting tab (Teams web, Meet, Zoom web) through the Chrome DevTools port to a stereo .m4a (left = mic, right = the tab). Needs no Screen Recording permission and stops by itself when the call ends. Without --into it saves under recordings/ and transcribes; with --into DIR it only saves and prints the path. See Record a browser meeting tab.
whosaid … [flags]The default command: transcribe + diarize + label one or more audio files. --reuse-asr skips Whisper when / .json already exists and re-diarizes only (errors if the json is missing; not valid with --no-diarize). whosaid transcribe … is the same command written explicitly (matching the whosaid_transcribe MCP tool name).
whosaid relabel SPEAKER_02=Jane …Put real names on clusters after reading the speaker cards. Rewrites the transcript + cards and saves each named voiceprint to the local registry for future transcripts — refusing (unless --force) to overwrite an existing registry entry the new cluster doesn't match (similarity below the match threshold, default 0.50). No re-transcription.
whosaid relabel SPEAKER_04=Alice --blendAverage the cluster into Alice's saved print instead of replacing it, to strengthen the print from a new recording. Same similarity guard as a normal relabel. See Speaker identity: enrollment clips vs. the registry.
whosaid relabel SPEAKER_04=Alice --no-save [--note TEXT]Transcript-only label: renames the cluster in the transcript + cards and never writes to the registry. For a speaker the conversation makes obvious but whose cluster is a poor voiceprint — a long mixed cluster saved as that person would degrade their enrolled print. The label is kept in the sidecar (local_labels), survives relabel --auto and whosaid samples, and each card is marked Alice_Example (transcript-only label; registry untouched). See Speaker identity: enrollment clips vs. the registry.

| whosaid relabel --auto [--forget NAME ...] [--fold-unknown] | Re-apply naming to an existing transcript with no assignments: re-runs registry matching + the absorb pass over the cached sidecar (and the voices/ enrollment clips, as transcribe does) and rewrites the transcript + cards. Picks up voices enrolled after the transcript was made, and drops auto-assigned names whose registry entry and clip are gone. --forget NAME (repeatable) clears NAME from this meeting first; it can come back if NAME is still enrolled and matches. Add --fold-unknown to repair anonymous phantom clusters in cached auto-diarization; it requires --auto and does not assign an identity.

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