Deepgram MCP Server

A Model Context Protocol (MCP) server that provides access to Deepgram's speech recognition and text-to-speech capabilities.

Features

Audio Transcription: Convert audio to text with high accuracy
Text-to-Speech: Generate natural-sounding speech from text
Audio Analysis: Extract insights like sentiment, topics, intents, and entities
Speaker Diarization: Identify different speakers in audio
Language Detection: Automatically detect the language of audio
Multiple Models: Support for various Deepgram models optimized for different use cases

Installation

Clone this repository
Install dependencies:
npm install
Copy the environment file and add your Deepgram API key:
cp env.example .env # Edit .env and add your DEEPGRAM_API_KEY
Build the project:
npm run build

Usage

HTTP Transport (Recommended for Production)

npm start
# or
node dist/index.js

The server will start on port 8080 by default. You can specify a different port:

node dist/index.js --port 8081

STDIO Transport (For Development)

npm run start:stdio
# or
node dist/index.js --stdio --port 8081

Available Tools

1. transcribe_audio

Transcribe audio to text with various options for customization.

Parameters:

audioUrl or audioData: Audio source (URL or base64)
model: Deepgram model to use (default: "nova-2-general")
language: Language code (default: "en")
punctuate: Add punctuation (default: true)
diarize: Speaker identification (default: false)
sentiment: Sentiment analysis (default: false)
And many more options...

2. text_to_speech

Convert text to speech using Deepgram's TTS models.

Parameters:

text: Text to convert to speech (required)
model: TTS model to use (default: "aura-asteria-en")
voice: Voice selection
format: Output format (default: "mp3")
speed: Speech speed (default: 1.0)

3. analyze_audio

Perform advanced audio analysis including sentiment, topics, intents, and entities.

Parameters:

audioUrl or audioData: Audio source
features: Analysis features to enable
model: Model for analysis

4. get_models

Get information about available Deepgram models.

Parameters:

model_type: Filter by model type ("transcription", "tts", or "all")

Client Configuration

For MCP clients, use this configuration:

{
  "mcpServers": {
    "deepgram": {
      "url": "http://localhost:8080/mcp"
    }
  }
}

Development

# Watch mode for development
npm run watch

# Development with STDIO
npm run dev:stdio

# Development with HTTP
npm run dev

API Key

Get your Deepgram API key from Deepgram Console.

Agno Integration

This MCP server also includes integration with Agno, a high-performance runtime for multi-agent systems.

Agno Tests

# Text-to-Speech test (saves audio to generated_audio/)
npm run test:agno:tts

# Speech-to-Text test (transcribes sample audio)
npm run test:agno:stt

License

MIT

Deepgram MCP Server