audio-transcriber 0.15.1

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

Audio-Transcriber - A2A | AG-UI | MCP

Version: 0.15.1

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: nvidia/nemotron-3-super)
	--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) |

Security & Governance

This project is built on agent-utilities, inheriting enterprise-grade security and governance features.

Authentication & Authorization

Feature	Description
OIDC Token Delegation	RFC 8693 token exchange for user-context propagation from A2A → MCP
Eunomia Policies	Fine-grained, policy-driven tool authorization (none, embedded, remote)
Scoped Credentials	Tools execute with the caller's scoped identity where possible
3LO / OAuth / API Token	Multiple auth strategies with graceful fallback

Eunomia Policy Enforcement

Eunomia provides a policy enforcement point for all tool calls:

• Embedded mode: Load local mcp_policies.json for role-based access, sensitivity gating, and audit logging
• Remote mode: Forward authorization decisions to a central Eunomia policy server for multi-agent governance
• Enable via CLI: --eunomia-type embedded --eunomia-policy-file mcp_policies.json

Runtime Protections

Protection	Description
Tool Guard	Sensitivity detection with human-in-the-loop approval gating
Prompt Injection Defense	Input scanning and repetition/loop guards
Content Filtering	Output schema enforcement and cost budget controls
Stuck Loop Detection	Automatic detection and recovery from agent loops
Context Limit Warnings	Proactive alerts before context window exhaustion

Graph Agent Architecture

The A2A agent uses pydantic-graph orchestration with:

• RouterNode: Lightweight classifier that routes queries to specialized domains
• DomainNode: Focused executor with only relevant tools loaded, preventing tool hallucination
• Approval Gates: Policy-driven approval workflows before sensitive operations
• Usage Guards: Budget and rate limiting enforcement

Production Recommendation: Enable --eunomia-type embedded (or remote) + OIDC delegation + containerized deployment. See agent-utilities documentation for full policy configuration.

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

MCP Configuration Examples

stdio (recommended for local development)

{
  "mcpServers": {
    "audio-transcriber": {
      "command": ".venv/bin/audio-transcriber-mcp",
      "args": [],
      "env": {
        "WHISPER_MODEL": "base"
}
    }
  }
}

Streamable HTTP (recommended for production)

{
  "mcpServers": {
    "audio-transcriber": {
      "url": "http://localhost:8080/audio-transcriber-mcp/mcp"
    }
  }
}