Skip to main content

Local CrispASR transcription workflow for Codex and MCP agents.

Project description

crispasr-agent-transcriber

Local-only transcription for Codex and MCP-based AI agents, powered by CrispASR. No cloud uploads, no API keys required for transcription.

GitHub Release | npm installer | PyPI package | MCP Registry

What it does

Give it a local audio or video file. It:

  1. Probes the spoken language (English or Chinese) using CrispASR's FireRed LID.
  2. Starts a local CrispASR server with the right backend -- Cohere Transcribe for English, Qwen3-ASR for Chinese.
  3. Extracts audio from video with ffmpeg when needed.
  4. Calls CrispASR's /v1/audio/transcriptions endpoint.
  5. Writes the transcript and metadata to disk.
  6. For video understanding, captures synchronized keyframes and writes an agent-readable manifest.

Everything runs on your machine. Media never leaves it.

Quick install for Codex

The plugin includes the Codex Skill, command-line tool, and MCP server. Media stays on your computer. Model files are never downloaded during install/update; use the explicit models command when you want the installer to fetch them.

1. Install prerequisites

Install Node.js 20 or newer, uv, and ffmpeg. The installer uses uv to provide Python.

node --version
uv --version
ffmpeg -version

2. Run the installer

npx @emiyakatuz/crispasr-agent-transcriber@latest install

The installer:

  • downloads the matching GitHub Release and verifies its SHA-256 checksum;
  • installs the plugin under ~/plugins/crispasr-agent-transcriber;
  • installs the Python and MCP dependencies;
  • detects CUDA, Vulkan, or CPU and installs the best CrispASR build;
  • registers the plugin in the Codex Personal marketplace;
  • preserves existing models, binaries, and outputs during updates.

3. Add the local models

Download the recommended local English, Chinese, and language-detection bundle:

npx @emiyakatuz/crispasr-agent-transcriber@latest models

The command downloads only approved GGUF files into:

~/plugins/crispasr-agent-transcriber/models/

Then verify the installation:

npx @emiyakatuz/crispasr-agent-transcriber@latest doctor

4. Enable the plugin

With a Codex build that supports plugin commands, run:

codex plugin add crispasr-agent-transcriber@personal

If the CLI has no codex plugin command, open the Codex desktop Plugins view and install CrispASR Transcriber from the Personal marketplace. Start a new conversation, then ask:

Transcribe C:\path\to\sample.mp4 with CrispASR using auto language detection.
Save a verbose JSON transcript and an SRT subtitle file.

Update or uninstall

npx @emiyakatuz/crispasr-agent-transcriber@latest update
npx @emiyakatuz/crispasr-agent-transcriber@latest uninstall

Uninstall preserves local models, CrispASR binaries, and outputs. Use uninstall --purge-data only when those files should also be deleted. See Plugin installation for manual installation and troubleshooting.

Direct command-line use

After installation, you can run the transcription script without Codex:

Set-Location (Join-Path $HOME "plugins\crispasr-agent-transcriber")
uv run python scripts/transcribe.py sample.mp4 --profile auto `
  --manage-server `
  --models-dir models `
  --format verbose_json

Use with other AI agents

The MCP server is the cross-agent interface. Any agent that supports MCP stdio can run the released package directly from GitHub:

uvx --from "crispasr-agent-transcriber[mcp] @ git+https://github.com/EmiyaKatuz/crispasr-agent-transcriber.git@v0.4.0" crispasr-agent-mcp

Use the same command and arguments in Claude Desktop, Cursor, or another MCP client. See AI agent integrations for a generic MCP configuration and Codex CLI command.

Maintainer publishing

End users do not need the release steps. Maintainers should follow the publishing guide for Codex Marketplace, PyPI, MCP Registry, and cross-agent distribution.

Required models

Install/update never downloads models. Use the explicit models command or download these three recommended GGUF files into a local directory such as models/:

Purpose Local file Variant / size Model page File page
English ASR cohere-transcribe-q4_k.gguf Q4_K, smaller default Cohere Transcribe 03-2026 GGUF Download
Chinese ASR qwen3-asr-1.7b-q4_k.gguf Q4_K, smaller default Qwen3-ASR 1.7B GGUF Download
Language detection firered-lid-q4_k.gguf Q4_K default FireRed LID GGUF Download

Optional model IDs include english-q5-0, english-q5-1, english-q6, english-q8, english-f16, chinese-q8, chinese-f16, lid-q2, lid-q8, and lid-f16. Download a specific option with:

npx @emiyakatuz/crispasr-agent-transcriber@latest models --model-id english-q8

All three upstream model families are Apache 2.0 licensed.

For automatic English/Chinese routing, pass both ASR paths. The language probe runs first, and only the matching model is loaded:

--english-model models\cohere-transcribe-q4_k.gguf
--chinese-model models\qwen3-asr-1.7b-q4_k.gguf
--lid-backend firered --lid-model models\firered-lid-q4_k.gguf

For an explicit english or chinese profile, --model remains available as a single-model override.

CrispASR binary management

The tool auto-detects, installs, and updates the CrispASR binary from GitHub releases.

Flag Effect
--install-crispasr Download latest platform binary to bin/
--update-crispasr Upgrade to newest release
--crispasr-status Show installed version + update availability
--crispasr-bin-dir PATH Custom directory (default ./bin)
--crispasr-bin PATH Exact path to crispasr.exe

When --manage-server is set and no binary is found, it auto-installs before starting the server.

GPU detection

On install and update, the tool checks your hardware:

  1. CUDA -- nvidia-smi available, or CUDA_PATH / CUDA_HOME set, or CUDA in PATH -> downloads crispasr-*-cuda variant.
  2. Vulkan -- vulkaninfo or VULKAN_SDK set (only when CUDA is absent) -> downloads crispasr-*-vulkan variant.
  3. CPU -- fallback when no GPU toolkit is detected.

macOS always uses the universal binary.

Profiles

Profile Backend ASR model Language hint
english cohere Cohere Transcribe 03-2026 en
chinese qwen3-1.7b Qwen3-ASR 1.7B zh
auto determined by LID determined by LID detected

auto mode runs FireRed language detection on the media, then routes English to Cohere or Chinese to Qwen3-1.7B. Mixed or uncertain content stops with a clear error asking you to re-run with --profile english or --profile chinese.

Usage

Managed server (tool starts CrispASR for you)

uv run python scripts/transcribe.py sample.wav `
  --profile auto `
  --manage-server `
  --models-dir models `
  --format srt `
  --out-dir outputs

Add --keep-server to leave the server running after transcription.

Manual server (you start CrispASR)

# Terminal 1 -- start the server
crispasr --server --backend cohere `
  -m models\cohere-transcribe-q4_k.gguf `
  --port 8080

# Terminal 2 -- transcribe
uv run python scripts/transcribe.py sample.mp4 `
  --profile english `
  --server-url http://127.0.0.1:8080 `
  --format verbose_json

If the running server's backend doesn't match the selected profile, the tool prints the exact command you need to start the correct server.

Output formats

--format File extension Contents
text .txt Plain transcript
verbose_json .json Full response with segments
srt .srt SubRip subtitles
vtt .vtt WebVTT subtitles

A .metadata.json sidecar is always written alongside the transcript.

Video files

Video files are detected automatically. ffmpeg extracts the audio track to a temporary mono 16 kHz WAV before sending it to CrispASR. The temporary file is deleted when transcription finishes.

All CLI flags

--profile auto|english|chinese
--format text|verbose_json|srt|vtt|json
--out-dir PATH
--server-url URL
--allow-remote-server
--manage-server
--keep-server
--model PATH               Local GGUF override for an explicit profile
--english-model PATH       Cohere model selected after English detection
--chinese-model PATH       Qwen3-ASR model selected after Chinese detection
--models-dir PATH          Directory containing approved local GGUF models
--allow-model-auto-download
--lid-model PATH           Local LID model path
--lid-backend firered|silero|ecapa|whisper
--host HOST                Managed server host (default 127.0.0.1)
--port PORT                Managed server port (default 8080)
--language CODE            Language hint for transcription
--prompt TEXT              Initial prompt/context
--vad                      Enable voice activity detection
--diarize                  Enable speaker diarization
--diarize-method METHOD
--hotwords WORD,WORD       Comma-separated hotwords
--no-timestamps
--preprocess auto|always|never
--api-key KEY              If CRISPASR_API_KEYS is enabled
--crispasr-bin-dir PATH
--crispasr-bin PATH
--install-crispasr
--update-crispasr
--crispasr-status
--list-models
--download-models
--model-id MODEL_ID
--overwrite-models

MCP server

uv sync --extra mcp
uv run --extra mcp crispasr-agent-mcp

Exposed tools:

Tool Description
crispasr_health Check CrispASR server health
crispasr_backends List available backends
crispasr_detect_language Run language detection on a file
crispasr_list_models List approved model choices and local install status
crispasr_download_models Explicitly download approved model files
crispasr_resolve_model_paths Return recommended local model paths
transcribe_audio Transcribe an audio file
transcribe_video Transcribe a video file
understand_video Transcribe a video, capture synced keyframes, and return an agent context
transcribe_folder Batch-transcribe a folder

Security model

  • No cloud uploads. Media files stay on the local filesystem.
  • No remote servers by default. --server-url only accepts localhost unless --allow-remote-server is explicitly passed.
  • No URL inputs. Only local file paths are accepted. URLs, S3, and other remote schemes are rejected.
  • No shell injection. ffmpeg is called with argument lists and shell=False. No user-controlled strings are interpolated into shell commands.
  • No implicit model downloads. Install/update never downloads models, and CrispASR model auto-download (-m auto) requires --allow-model-auto-download. The models command and crispasr_download_models tool download only allowlisted Hugging Face files.
  • Temporary files are cleaned up. Converted WAV files and LID probe windows are deleted when transcription finishes.
  • Binary downloads are explicit. CrispASR binary installs only from the official CrispStrobe/CrispASR GitHub releases.
  • Verified plugin releases. The npm installer requires the plugin ZIP to match the SHA-256 value published in the same GitHub Release.
  • Narrow installer writes. The installer manages only its plugin directory and the named Personal marketplace entry. Updates preserve local models, binaries, and outputs.
  • Generated understanding stays local. Video keyframes, manifests, and agent context files are written under the selected output directory and are ignored by Git.

Verify

uv run pytest
uv run ruff check .  # zero lint warnings

License

This project is licensed under the MIT License.

Third-party components and attribution

This tool orchestrates several independently-licensed projects. It does not bundle, fork, or redistribute their code -- it downloads pre-built binaries and calls them as subprocesses or HTTP services at runtime.

Component License Role
CrispASR MIT ASR engine, server, language detection
ffmpeg LGPL 2.1+ / GPL 2+ Media decoding and audio extraction
Cohere Transcribe 03-2026 Apache 2.0 English ASR model (loaded by CrispASR)
Qwen3-ASR 1.7B Apache 2.0 Chinese ASR model (loaded by CrispASR)
FireRed LID Apache 2.0 Language detection model (loaded by CrispASR)
httpx BSD HTTP client for CrispASR API
MCP Python SDK MIT MCP server framework
Node.js MIT npm installer runtime
adm-zip MIT Verified plugin ZIP extraction

Model files must be downloaded separately by the user from their respective HuggingFace repositories. See Required models above.

Related projects

  • CrispASR -- the ASR engine this tool wraps
  • CrisperWeaver -- CrispASR's desktop GUI (not used by this tool)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

crispasr_agent_transcriber-0.4.0.tar.gz (111.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

crispasr_agent_transcriber-0.4.0-py3-none-any.whl (35.7 kB view details)

Uploaded Python 3

File details

Details for the file crispasr_agent_transcriber-0.4.0.tar.gz.

File metadata

  • Download URL: crispasr_agent_transcriber-0.4.0.tar.gz
  • Upload date:
  • Size: 111.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.11.24 {"installer":{"name":"uv","version":"0.11.24","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for crispasr_agent_transcriber-0.4.0.tar.gz
Algorithm Hash digest
SHA256 71b8c4a817cac842f4010dddd4d5c479c0938eca636a67815fb773b815848c61
MD5 deb6599222b9e7b96f03605b93e035ae
BLAKE2b-256 34e9f727a97dd3e871abee516d8e71590966869baa881a3f316b94763c90d746

See more details on using hashes here.

File details

Details for the file crispasr_agent_transcriber-0.4.0-py3-none-any.whl.

File metadata

  • Download URL: crispasr_agent_transcriber-0.4.0-py3-none-any.whl
  • Upload date:
  • Size: 35.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.11.24 {"installer":{"name":"uv","version":"0.11.24","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for crispasr_agent_transcriber-0.4.0-py3-none-any.whl
Algorithm Hash digest
SHA256 ed8fc8d9d2ab1a6aa8de9e2fbbcba733a1e1580032a8f29e3b3b6df073a3d3e4
MD5 130246ffbd69e9f6c95af89a34daa63f
BLAKE2b-256 3dcfb94b36047b19474753884440da19794d7129726e08f053fdaba61db323d4

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page