Super Singularity MCP Server

A Model Context Protocol (MCP) server for integrating Claude Desktop with Super Singularity's course creation API, ElevenLabs text-to-speech, and Azure Blob Storage.

Features

• Complete Course Management: Create, update, and manage courses
• All Card Types: Support for content, quiz, poll, form, video, audio, and link cards
• Text-to-Speech: Generate audio from text using ElevenLabs TTS
• Cloud Storage: Upload and host audio files on Azure Blob Storage
• Script Preservation: Store original script text in audio card contents
• Production Ready: Environment configuration, error handling, and timeout management

Quick Start

1. Clone and Install:

   git clone <repository-url>
   cd mcp-servers
   uv sync
   

2. Configure Environment:

   cp .env.example .env
   # Edit .env with your API keys and configuration
   

3. Add to Claude Desktop: Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

   {
     "mcpServers": {
       "super-singularity": {
         "command": "uv",
         "args": ["run", "python", "/path/to/mcp-servers/server.py"]
       }
     }
   }
   

4. Restart Claude Desktop and start creating courses!

Environment Configuration

Required environment variables in .env:

# Super Singularity API
API_BASE_URL=https://your-api-domain.com
API_TOKEN=your-bearer-token-here  
COMPANY_ID=your-company-id-here

# ElevenLabs TTS
ELEVENLABS_API_KEY=your-elevenlabs-api-key-here
ELEVENLABS_VOICE_ID=21m00Tcm4TlvDq8ikWAM

# Azure Blob Storage  
AZURE_STORAGE_CONNECTION_STRING=DefaultEndpointsProtocol=https;AccountName=...
AZURE_CONTAINER_NAME=audio-files

Available Tools

Course Management

• get_course(course_id) - Get course details
• create_course(title, ...) - Create new course
• get_course_cards(course_id) - Get all cards in course

Card Creation

• create_content_card() - Text content with optional image
• create_quiz_card() - Multiple choice questions
• create_poll_card() - Opinion polls for collecting learner feedback
• create_form_card() - Form inputs for collecting learner responses
• create_video_card() - Video content
• create_audio_card() - Audio content with optional script preservation
• create_link_card() - External resource links

Audio Generation

• generate_audio_from_text(text, title) - Generate audio using ElevenLabs TTS
• Creates audio files and uploads to Azure Storage
• Returns URL and script preservation instructions

Audio Card Workflow

Due to MCP limitations, audio card creation from script requires two steps:

1. Generate Audio:

   generate_audio_from_text("Your script text here", "Audio Title")
   

2. Create Card with Script Preservation:

   create_audio_card(course_id, audio_url, title, script="Your script text here")
   

The script parameter preserves the original text in the card contents for future reference.

MCP Limitations Discovered

The Problem

MCP tools that combine multiple async operations (ElevenLabs + Azure + API requests) cause "Internal Server Error" in Claude Desktop, regardless of function names or implementation approach.

Failed Attempts

All of these caused Internal Server Errors:

• create_audio_card_from_script()
• generate_audio_url_from_script()
• create_audio_card_using_script()
• test_helper_function_plus_api()

Working Solution

Separate tools for each operation:

• generate_audio_from_text() - Only handles ElevenLabs + Azure
• create_audio_card() - Only handles API requests
• Two-step workflow with clear instructions for script preservation

Root Cause Analysis

The limitation appears to be related to:

• Complex async operation chains in single MCP tools
• Timeout thresholds for multi-step operations
• Memory/resource constraints in Claude Desktop MCP client
• Event loop handling of combined external service calls

Community Validation

Our findings align with known MCP issues documented in the community:

• GitHub Issue #424: "MCP Timeout needs to be configurable"
• GitHub Issue #417: "MCP Server Internal Server Error Report"
• Multiple forum discussions about timeout errors and Internal Server Errors

Best Practices Learned

1. Keep MCP tools simple and atomic - Single responsibility per tool
2. Avoid combining multiple external service calls in one tool
3. Use helper functions for complex operations, but call them from separate tools
4. Provide clear instructions in tool responses to guide multi-step workflows
5. Test incrementally when adding new integrations

API Documentation

Complete API documentation available in: documentation/external-api-documentation.md

Dependencies

• mcp - Model Context Protocol Python SDK
• httpx - Async HTTP client for API requests
• elevenlabs - ElevenLabs TTS integration
• azure-storage-blob - Azure Blob Storage client
• python-dotenv - Environment variable management

License

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Contributing

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