P
phonology024/babelscribe
Free offline speech-to-text & subtitles (SRT/VTT) in 99 languages on any GPU — AMD, NVIDIA, Intel, Apple. Whisper via whisper.cpp + MCP server for Claude, Codex, Gemini CLI.
no SECURITY.md
View on GitHub ↗Link checked 2026-11-12 · HTTP 200 · opens the vendor's own site
Install & config
- Copy the command above
- Paste it as one entry under
mcpServersinclaude_desktop_config.json— local servers take command + args (example: clients) - Restart your client
Client config (built from the install command this repo gives)
{
"mcpServers": {
"phonology024-babelscribe": {
"command": "uvx",
"args": ["babelscribe", "mcp"]
}
}
}Parsed from the README we fetched on 2026-10-26; we have not executed it.
command/args come from the install command the repository states. When it is ambiguous, the project README wins.
VS Code (.vscode/mcp.json - the key is servers)
{
"servers": {
"phonology024-babelscribe": {
"command": "uvx",
"args": ["babelscribe", "mcp"]
}
}
}Same server, but VS Code keeps it under <code>servers</code>.
Claude Code (command line)
claude mcp add --transport stdio phonology024-babelscribe -- uvx babelscribe mcp
Claude Code does not read a config file; add the server with this command.
Key names differ by client: Clients & CLI
- Star count
- 8 ★ · phonology024/babelscribe · read from the GitHub search API · (checked 2026-11-13 20:00:50)
- Source
- collected from the punkpeye/awesome-mcp-servers list · type: MCP server
- Harvest history
- first seen 2026-10-23 · last seen 2026-11-14 · seen 26× · listed by 23 sources
- Score
- score 2,300 · 8 ★ · 23 sources · mcp
- Install
uvx babelscribe mcp
FAQ (answers come from our records)
How do I install it?
The repository provides this install command:
uvx babelscribe mcp. It comes from the repository itself; we cannot guarantee it runs as-is in your client.Who is it for?
We filed it under these tags: MCP 服务. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
repository
phonology024/babelscribe;first catalogued 2026-10-23;last seen 2026-11-14。There is no official certification or quality rating here — we record sources and dates only.# babelscribe — free, offline speech-to-text and subtitles on any GPU (AMD, NVID
以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →
babelscribe turns any audio or video file into subtitles (SRT, VTT) and text, in any of Whisper's 99 languages, on your
own graphics card — AMD Radeon, NVIDIA, Intel Arc or Apple Silicon — or the CPU. No CUDA needed, no cloud, free (MIT).
It runs OpenAI Whisper through whisper.cpp with Vulkan, CUDA or Metal, and works
from the command line, from Python, or from AI apps (Claude, Codex, Antigravity, Gemini CLI, Cursor) as an MCP server.
bash
pip install babelscribe # Python 3.9+
babelscribe interview.mp4 # auto-detects language, picks your best GPU -> interview.srt + interview.json
babelscribe is a thin, friendly layer on top of whisper.cpp. It exists because
getting fast Whisper on a non-NVIDIA card (e.g. an AMD Radeon on Windows) still means building whisper.cpp with the
Vulkan SDK yourself. babelscribe downloads a prebuilt whisper-cli for your system and handles the rest.
| Your hardware | Backend used | Prebuilt asset |
| AMD / NVIDIA / Intel GPU on Windows | Vulkan | windows-x64-vulkan |
| NVIDIA on Windows | Vulkan (same build) | windows-x64-vulkan |
| NVIDIA on Linux (alternative) | CUDA | linux-x64-cuda (--flavor cuda) |
| AMD / NVIDIA / Intel GPU on Linux | Vulkan | linux-x64-vulkan |
| Apple Silicon | Metal | macos-arm64-metal |
| No usable GPU | CPU | -cpu (--flavor cpu) |
A 19-minute English TED talk transcribes in 48 seconds on an AMD Radeon RX 9070 XT with 1.5% word error — see the benchmark below.
## Use it from an AI app (MCP) — no terminal needed
babelscribe is also an MCP server, so any AI app that supports local MCP servers can
transcribe files on your computer with your GPU. Ask in plain words — "make Thai subtitles for the newest video in
my Downloads" — and the app finds the file, transcribes it, writes .srt / .txt next to it, and can then proofread names,
translate or summarise the text for you.
Tools: transcribe (file → subtitles + text), findmedia (newest audio/video in Downloads, Videos, Desktop, …),
listdevices, listlanguagesandmodels.
Claude Desktop (one click): download babelscribe.mcpb from the latest release
and double-click it (or Settings → Extensions → Install extension).
Everything else runs the same command — uv fetches babelscribe for you:
uvx babelscribe mcp
| App | How to add it |
| Claude Code | claude mcp add babelscribe -- uvx babelscribe mcp |
| OpenAI Codex CLI | codex mcp add babelscribe -- uvx babelscribe mcp, then in ~/.codex/config.toml under [mcpservers.babelscribe] set tooltimeoutsec = 3600 and startuptimeoutsec = 120 (defaults are 60 s / 10 s — too short for a long video or the first model download) |
| Google Antigravity | agent panel → ⋯ → MCP Servers → Manage MCP Servers → View raw config, add the JSON below |
| Gemini CLI | add the JSON below to ~/.gemini/settings.json |
| Cursor | add the JSON below to ~/.cursor/mcp.json |
| VS Code (Copilot) | .vscode/mcp.json: same entry under "servers" with "type": "stdio" |
json
"mcpServers": {
"babelscribe": { "command": "uvx", "args": ["babelscribe", "mcp"], "timeout": 3600000 }
(timeout is in milliseconds and only some apps read it.) Already installed with pip? Use "command": "babelscribe", "args": ["mcp"].
Web-only chat apps (e.g. grok.com, chatgpt.com) can only reach servers on the internet, not your computer, so they can't use your GPU or files.
own graphics card — AMD Radeon, NVIDIA, Intel Arc or Apple Silicon — or the CPU. No CUDA needed, no cloud, free (MIT).
It runs OpenAI Whisper through whisper.cpp with Vulkan, CUDA or Metal, and works
from the command line, from Python, or from AI apps (Claude, Codex, Antigravity, Gemini CLI, Cursor) as an MCP server.
bash
pip install babelscribe # Python 3.9+
babelscribe interview.mp4 # auto-detects language, picks your best GPU -> interview.srt + interview.json
babelscribe is a thin, friendly layer on top of whisper.cpp. It exists because
getting fast Whisper on a non-NVIDIA card (e.g. an AMD Radeon on Windows) still means building whisper.cpp with the
Vulkan SDK yourself. babelscribe downloads a prebuilt whisper-cli for your system and handles the rest.
| Your hardware | Backend used | Prebuilt asset |
| AMD / NVIDIA / Intel GPU on Windows | Vulkan | windows-x64-vulkan |
| NVIDIA on Windows | Vulkan (same build) | windows-x64-vulkan |
| NVIDIA on Linux (alternative) | CUDA | linux-x64-cuda (--flavor cuda) |
| AMD / NVIDIA / Intel GPU on Linux | Vulkan | linux-x64-vulkan |
| Apple Silicon | Metal | macos-arm64-metal |
| No usable GPU | CPU | -cpu (--flavor cpu) |
A 19-minute English TED talk transcribes in 48 seconds on an AMD Radeon RX 9070 XT with 1.5% word error — see the benchmark below.
## Use it from an AI app (MCP) — no terminal needed
babelscribe is also an MCP server, so any AI app that supports local MCP servers can
transcribe files on your computer with your GPU. Ask in plain words — "make Thai subtitles for the newest video in
my Downloads" — and the app finds the file, transcribes it, writes .srt / .txt next to it, and can then proofread names,
translate or summarise the text for you.
Tools: transcribe (file → subtitles + text), findmedia (newest audio/video in Downloads, Videos, Desktop, …),
listdevices, listlanguagesandmodels.
Claude Desktop (one click): download babelscribe.mcpb from the latest release
and double-click it (or Settings → Extensions → Install extension).
Everything else runs the same command — uv fetches babelscribe for you:
uvx babelscribe mcp
| App | How to add it |
| Claude Code | claude mcp add babelscribe -- uvx babelscribe mcp |
| OpenAI Codex CLI | codex mcp add babelscribe -- uvx babelscribe mcp, then in ~/.codex/config.toml under [mcpservers.babelscribe] set tooltimeoutsec = 3600 and startuptimeoutsec = 120 (defaults are 60 s / 10 s — too short for a long video or the first model download) |
| Google Antigravity | agent panel → ⋯ → MCP Servers → Manage MCP Servers → View raw config, add the JSON below |
| Gemini CLI | add the JSON below to ~/.gemini/settings.json |
| Cursor | add the JSON below to ~/.cursor/mcp.json |
| VS Code (Copilot) | .vscode/mcp.json: same entry under "servers" with "type": "stdio" |
json
"mcpServers": {
"babelscribe": { "command": "uvx", "args": ["babelscribe", "mcp"], "timeout": 3600000 }
(timeout is in milliseconds and only some apps read it.) Already installed with pip? Use "command": "babelscribe", "args": ["mcp"].
Web-only chat apps (e.g. grok.com, chatgpt.com) can only reach servers on the internet, not your computer, so they can't use your GPU or files.
Listed badge (optional)
Copy this line into the README if you want the listing mark. Optional, and it does not affect being listed.
[](https://anclum.com/en/s/phonology024-babelscribe/)
- Source
- awesome · https://github.com/phonology024/babelscribe
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