audio-transcriber 0.6.8

Transcribe your .wav .mp4 .mp3 .flac files to text or record your own audio!

Audio-Transcriber - A2A | AG-UI | MCP

Version: 0.6.8

Overview

Transcribe your .wav .mp4 .mp3 .flac files to text or record your own audio!

This repository is actively maintained - Contributions are welcome!

Contribution Opportunities:

• Support new models

Wrapped around OpenAI Whisper

MCP

MCP Tools

Function Name	Description	Tag(s)
transcribe_audio	Transcribes audio from a provided file or by recording from the microphone.	audio_processing

A2A Agent

Architecture Summary

---
config:
  layout: dagre
---
flowchart TB
 subgraph subGraph0["Agent Capabilities"]
        C["Agent"]
        B["A2A Server - Uvicorn/FastAPI"]
        D["MCP Tools"]
        F["Agent Skills"]
  end
    C --> D & F
    A["User Query"] --> B
    B --> C
    D --> E["Platform API"]

     C:::agent
     B:::server
     A:::server
    classDef server fill:#f9f,stroke:#333
    classDef agent fill:#bbf,stroke:#333,stroke-width:2px
    style B stroke:#000000,fill:#FFD600
    style D stroke:#000000,fill:#BBDEFB
    style F fill:#BBDEFB
    style A fill:#C8E6C9
    style subGraph0 fill:#FFF9C4

Component Interaction Diagram

sequenceDiagram
    participant User
    participant Server as A2A Server
    participant Agent as Agent
    participant Skill as Agent Skills
    participant MCP as MCP Tools

    User->>Server: Send Query
    Server->>Agent: Invoke Agent
    Agent->>Skill: Analyze Skills Available
    Skill->>Agent: Provide Guidance on Next Steps
    Agent->>MCP: Invoke Tool
    MCP-->>Agent: Tool Response Returned
    Agent-->>Agent: Return Results Summarized
    Agent-->>Server: Final Response
    Server-->>User: Output

Usage

CLI

Short Flag	Long Flag	Description
-h	--help	See Usage
-b	--bitrate	Bitrate to use during recording
-c	--channels	Number of channels to use during recording
-d	--directory	Directory to save recording
-e	--export	Export txt, srt, and vtt files
-f	--file	File to transcribe
-l	--language	Language to transcribe
-m	--model	Model to use: <tiny, base, small, medium, large>
-n	--name	Name of recording
-r	--record	Specify number of seconds to record to record from microphone

audio-transcriber --file '~/Downloads/Federal_Reserve.mp4' --model 'large'

audio-transcriber --record 60 --directory '~/Downloads/' --name 'my_recording.wav' --model 'tiny'

MCP CLI

Short Flag	Long Flag	Description
-h	--help	Display help information
-t	--transport	Transport method: 'stdio', 'http', or 'sse' [legacy] (default: stdio)
-s	--host	Host address for HTTP transport (default: 0.0.0.0)
-p	--port	Port number for HTTP transport (default: 8000)
	--auth-type	Authentication type: 'none', 'static', 'jwt', 'oauth-proxy', 'oidc-proxy', 'remote-oauth' (default: none)
	--token-jwks-uri	JWKS URI for JWT verification
	--token-issuer	Issuer for JWT verification
	--token-audience	Audience for JWT verification
	--oauth-upstream-auth-endpoint	Upstream authorization endpoint for OAuth Proxy
	--oauth-upstream-token-endpoint	Upstream token endpoint for OAuth Proxy
	--oauth-upstream-client-id	Upstream client ID for OAuth Proxy
	--oauth-upstream-client-secret	Upstream client secret for OAuth Proxy
	--oauth-base-url	Base URL for OAuth Proxy
	--oidc-config-url	OIDC configuration URL
	--oidc-client-id	OIDC client ID
	--oidc-client-secret	OIDC client secret
	--oidc-base-url	Base URL for OIDC Proxy
	--remote-auth-servers	Comma-separated list of authorization servers for Remote OAuth
	--remote-base-url	Base URL for Remote OAuth
	--allowed-client-redirect-uris	Comma-separated list of allowed client redirect URIs
	--eunomia-type	Eunomia authorization type: 'none', 'embedded', 'remote' (default: none)
	--eunomia-policy-file	Policy file for embedded Eunomia (default: mcp_policies.json)
	--eunomia-remote-url	URL for remote Eunomia server

Using as an MCP Server

The MCP Server can be run in two modes: stdio (for local testing) or http (for networked access). To start the server, use the following commands:

Run in stdio mode (default):

audio-transcriber-mcp

Run in HTTP mode:

audio-transcriber-mcp --transport "http"  --host "0.0.0.0"  --port "8000"

Model Information

Courtesy of and Credits to OpenAI: Whisper.ai

Size	Parameters	English-only model	Multilingual model	Required VRAM	Relative speed
tiny	39 M	tiny.en	tiny	~1 GB	~32x
base	74 M	base.en	base	~1 GB	~16x
small	244 M	small.en	small	~2 GB	~6x
medium	769 M	medium.en	medium	~5 GB	~2x
large	1550 M	N/A	large	~10 GB	1x

Deploy MCP Server as a Service

The ServiceNow MCP server can be deployed using Docker, with configurable authentication, middleware, and Eunomia authorization.

Using Docker Run

docker pull knucklessg1/audio-transcriber:latest

docker run -d \
  --name audio-transcriber-mcp \
  -p 8004:8004 \
  -e HOST=0.0.0.0 \
  -e PORT=8004 \
  -e TRANSPORT=http \
  -e AUTH_TYPE=none \
  -e EUNOMIA_TYPE=none \
  knucklessg1/audio-transcriber:latest

For advanced authentication (e.g., JWT, OAuth Proxy, OIDC Proxy, Remote OAuth) or Eunomia, add the relevant environment variables:

docker run -d \
  --name audio-transcriber-mcp \
  -p 8004:8004 \
  -e HOST=0.0.0.0 \
  -e PORT=8004 \
  -e TRANSPORT=http \
  -e AUTH_TYPE=oidc-proxy \
  -e OIDC_CONFIG_URL=https://provider.com/.well-known/openid-configuration \
  -e OIDC_CLIENT_ID=your-client-id \
  -e OIDC_CLIENT_SECRET=your-client-secret \
  -e OIDC_BASE_URL=https://your-server.com \
  -e ALLOWED_CLIENT_REDIRECT_URIS=http://localhost:*,https://*.example.com/* \
  -e EUNOMIA_TYPE=embedded \
  -e EUNOMIA_POLICY_FILE=/app/mcp_policies.json \
  knucklessg1/audio-transcriber:latest

Using Docker Compose

Create a docker-compose.yml file:

services:
  audio-transcriber-mcp:
    image: knucklessg1/audio-transcriber:latest
    environment:
      - HOST=0.0.0.0
      - PORT=8004
      - TRANSPORT=http
      - AUTH_TYPE=none
      - EUNOMIA_TYPE=none
    ports:
      - 8004:8004

For advanced setups with authentication and Eunomia:

services:
  audio-transcriber-mcp:
    image: knucklessg1/audio-transcriber:latest
    environment:
      - HOST=0.0.0.0
      - PORT=8004
      - TRANSPORT=http
      - AUTH_TYPE=oidc-proxy
      - OIDC_CONFIG_URL=https://provider.com/.well-known/openid-configuration
      - OIDC_CLIENT_ID=your-client-id
      - OIDC_CLIENT_SECRET=your-client-secret
      - OIDC_BASE_URL=https://your-server.com
      - ALLOWED_CLIENT_REDIRECT_URIS=http://localhost:*,https://*.example.com/*
      - EUNOMIA_TYPE=embedded
      - EUNOMIA_POLICY_FILE=/app/mcp_policies.json
    ports:
      - 8004:8004
    volumes:
      - ./mcp_policies.json:/app/mcp_policies.json

Run the service:

docker-compose up -d

Configure mcp.json for AI Integration

Configure mcp.json

{
  "mcpServers": {
    "audio_transcriber": {
      "command": "uv",
      "args": [
        "run",
        "--with",
        "audio-transcriber",
        "audio-transcriber-mcp"
      ],
      "env": {
        "WHISPER_MODEL": "medium",            // Optional
        "TRANSCRIBE_DIRECTORY": "~/Downloads" // Optional
      },
      "timeout": 200000
    }
  }
}

A2A CLI

Endpoints

• Web UI: http://localhost:8000/ (if enabled)
• A2A: http://localhost:8000/a2a (Discovery: /a2a/.well-known/agent.json)
• AG-UI: http://localhost:8000/ag-ui (POST)

Short Flag	Long Flag	Description
-h	--help	Display help information
	--host	Host to bind the server to (default: 0.0.0.0)
	--port	Port to bind the server to (default: 9000)
	--reload	Enable auto-reload
	--provider	LLM Provider: 'openai', 'anthropic', 'google', 'huggingface'
	--model-id	LLM Model ID (default: qwen3:4b)
	--base-url	LLM Base URL (for OpenAI compatible providers)
	--api-key	LLM API Key

| | --mcp-url | MCP Server URL (default: http://localhost:8000/mcp) | | | --web | Enable Pydantic AI Web UI | False (Env: ENABLE_WEB_UI) |

Install Python Package

python -m pip install audio-transcriber

or

uv pip install --upgrade audio-transcriber

Ubuntu Dependencies

sudo apt-get update
sudo apt-get install libasound-dev portaudio19-dev libportaudio2 libportaudiocpp0 ffmpeg gcc -y

Repository Owners