https://github.com/knuckles-team/audio-transcriber
Transcribe audio into text. Agentic AI supported through MCP Server.
https://github.com/knuckles-team/audio-transcriber
a2a a2a-server ag-ui mcp-server openai transcription transformers whisper
Last synced: about 1 month ago
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Transcribe audio into text. Agentic AI supported through MCP Server.
- Host: GitHub
- URL: https://github.com/knuckles-team/audio-transcriber
- Owner: Knuckles-Team
- License: mit
- Created: 2022-12-27T18:57:18.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2026-04-20T07:43:10.000Z (about 2 months ago)
- Last Synced: 2026-04-20T09:35:21.891Z (about 2 months ago)
- Topics: a2a, a2a-server, ag-ui, mcp-server, openai, transcription, transformers, whisper
- Language: Python
- Homepage:
- Size: 648 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Agents: AGENTS.md
Awesome Lists containing this project
README
# Audio-Transcriber - A2A | AG-UI | MCP
*Version: 0.11.2*
## 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](https://pypi.org/project/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
```mermaid
---
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
```mermaid
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: |
| -n | --name | Name of recording |
| -r | --record | Specify number of seconds to record to record from microphone |
```bash
audio-transcriber --file '~/Downloads/Federal_Reserve.mp4' --model 'large'
```
```bash
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):
```bash
audio-transcriber-mcp
```
#### Run in HTTP mode:
```bash
audio-transcriber-mcp --transport "http" --host "0.0.0.0" --port "8000"
```
#### Model Information
[Courtesy of and Credits to OpenAI: Whisper.ai](https://github.com/openai/whisper/blob/main/README.md)
| 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
```bash
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:
```bash
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:
```yaml
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:
```yaml
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:
```bash
docker-compose up -d
```
#### Configure `mcp.json` for AI Integration
Configure `mcp.json`
```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) |
## Install Python Package
```bash
python -m pip install audio-transcriber
```
or
```bash
uv pip install --upgrade audio-transcriber
```
##### Ubuntu Dependencies
```bash
sudo apt-get update
sudo apt-get install libasound-dev portaudio19-dev libportaudio2 libportaudiocpp0 ffmpeg gcc -y
```
## Repository Owners
## MCP Configuration Examples
### 1. Standard IO (stdio) Deployment
```json
{
"mcpServers": {
"audio-transcriber": {
"command": "uv",
"args": [
"run",
"audio-transcriber-mcp"
],
"env": {
"AGENT_DESCRIPTION": "",
"AGENT_SYSTEM_PROMPT": "",
"AUDIO_PROCESSINGTOOL": "True",
"DEFAULT_AGENT_NAME": "",
"TRANSCRIBE_DIRECTORY": "",
"WHISPER_MODEL": ""
}
}
}
}
```
### 2. Streamable HTTP (SSE) Deployment
```json
{
"mcpServers": {
"audio-transcriber": {
"command": "uv",
"args": [
"run",
"audio-transcriber-mcp",
"--transport",
"http",
"--host",
"0.0.0.0",
"--port",
"8000"
],
"env": {
"AGENT_DESCRIPTION": "",
"AGENT_SYSTEM_PROMPT": "",
"AUDIO_PROCESSINGTOOL": "True",
"DEFAULT_AGENT_NAME": "",
"TRANSCRIBE_DIRECTORY": "",
"WHISPER_MODEL": ""
}
}
}
}
```