ElevenLabs Text-to-Speech MCP

local-only server

The server can only run on the client’s local machine because it depends on local resources.

Integrations

  • Integrates ElevenLabs Text-to-Speech capabilities, allowing text to be converted to speech via the ElevenLabs API with voice selection and management features

Project Jessica (ElevenLabs TTS MCP)

This project integrates ElevenLabs Text-to-Speech capabilities with Cursor through the Model Context Protocol (MCP). It consists of a FastAPI backend service and a React frontend application.

Features

  • Text-to-Speech conversion using ElevenLabs API
  • Voice selection and management
  • MCP integration for Cursor
  • Modern React frontend interface
  • WebSocket real-time communication
  • Pre-commit hooks for code quality
  • Automatic code formatting and linting

Project Structure

jessica/ ├── src/ │ ├── backend/ # FastAPI backend service │ └── frontend/ # React frontend application ├── terraform/ # Infrastructure as Code ├── tests/ # Test suites └── docs/ # Documentation

Requirements

  • Python 3.11+
  • Poetry (for backend dependency management)
  • Node.js 18+ (for frontend)
  • Cursor (for MCP integration)

Local Development Setup

Backend Setup

# Clone the repository git clone https://github.com/georgi-io/jessica.git cd jessica # Create Python virtual environment python -m venv .venv source .venv/bin/activate # On Windows: .venv\Scripts\activate # Install backend dependencies poetry install # Configure environment cp .env.example .env # Edit .env with your ElevenLabs API key # Install pre-commit hooks poetry run pre-commit install

Frontend Setup

# Navigate to frontend directory cd src/frontend # Install dependencies npm install

Development Servers

Starting the Backend

# Activate virtual environment if not active source .venv/bin/activate # On Windows: .venv\Scripts\activate # Start the backend python -m src.backend

The backend provides:

Starting the Frontend

# In src/frontend directory npm run dev

Frontend development server:

Environment Configuration

Backend (.env)

# ElevenLabs API ELEVENLABS_API_KEY=your-api-key # Server Configuration HOST=127.0.0.1 PORT=9020 # Development Settings DEBUG=false RELOAD=true

Frontend (.env)

VITE_API_URL=http://localhost:9020 VITE_WS_URL=ws://localhost:9020/ws

Code Quality Tools

Backend

# Run all pre-commit hooks poetry run pre-commit run --all-files # Run specific tools poetry run ruff check . poetry run ruff format . poetry run pytest

Frontend

# Lint npm run lint # Type check npm run type-check # Test npm run test

Production Deployment

AWS ECR and GitHub Actions Setup

To enable automatic building and pushing of Docker images to Amazon ECR:

  1. Apply the Terraform configuration to create the required AWS resources:
    cd terraform terraform init terraform apply
  2. The GitHub Actions workflow will automatically:
    • Read the necessary configuration from the Terraform state in S3
    • Build the Docker image on pushes to main or develop branches
    • Push the image to ECR with tags for latest and the specific commit SHA
  3. No additional repository variables needed! The workflow fetches all required configuration from the Terraform state.

How it Works

The GitHub Actions workflow is configured to:

  1. Initially assume a predefined IAM role with S3 read permissions
  2. Fetch and extract configuration values from the Terraform state file in S3
  3. Re-authenticate using the actual deployment role from the state file
  4. Build and push the Docker image to the ECR repository defined in the state

This approach eliminates the need to manually configure GitHub repository variables and ensures that the CI/CD process always uses the current infrastructure configuration.

Quick Overview

  • Frontend: Served from S3 via CloudFront at jessica.georgi.io
  • Backend API: Available at api.georgi.io/jessica
  • WebSocket: Connects to api.georgi.io/jessica/ws
  • Docker Image: Stored in AWS ECR and can be deployed to ECS/EKS
  • Infrastructure: Managed via Terraform in this repository

MCP Integration with Cursor

  1. Start the backend server
  2. In Cursor settings, add new MCP server:

Troubleshooting

Common Issues

  1. API Key Issues
    • Error: "Invalid API key"
    • Solution: Check .env file
  2. Connection Problems
    • Error: "Cannot connect to MCP server"
    • Solution: Verify backend is running and ports are correct
  3. Port Conflicts
    • Error: "Address already in use"
    • Solution: Change ports in .env
  4. WebSocket Connection Failed
    • Error: "WebSocket connection failed"
    • Solution: Ensure backend is running and WebSocket URL is correct

For additional help, please open an issue on GitHub.

License

MIT

-
security - not tested
F
license - not found
-
quality - not tested

Integrates ElevenLabs Text-to-Speech capabilities with Cursor through the Model Context Protocol, allowing users to convert text to speech with selectable voices within the Cursor editor.

  1. Features
    1. Project Structure
      1. Requirements
        1. Local Development Setup
          1. Backend Setup
          2. Frontend Setup
        2. Development Servers
          1. Starting the Backend
          2. Starting the Frontend
        3. Environment Configuration
          1. Backend (.env)
          2. Frontend (.env)
        4. Code Quality Tools
          1. Backend
          2. Frontend
        5. Production Deployment
          1. AWS ECR and GitHub Actions Setup
          2. How it Works
          3. Quick Overview
        6. MCP Integration with Cursor
          1. Troubleshooting
            1. Common Issues
          2. License