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Theta EdgeCloud On-Demand API MCP Server logo

Theta EdgeCloud On-Demand API MCP Server

thetatoken/on-demand-api-mcp
1 starsUpdated 2026-01-04Community

Works with

Claude CodeClaude DesktopCursorVS CodeClineCodex CLIOpenClaw+ any MCP client

Install to Claude Code

This server doesn't publish a one-line install command. Follow the setup in the source repository.

Summary

Official MCP server for Theta EdgeCloud's On-Demand Model APIs, providing access to 20+ AI models including image generation, audio transcription, and LLMs, directly from MCP-compatible clients.

README.md

Theta EdgeCloud On-Demand API MCP Server

Official Model Context Protocol (MCP) server for Theta EdgeCloud's On-Demand Model APIs. Access 20+ AI models directly from Claude Desktop, Claude Code, Cursor, and other MCP-compatible clients.

Features

  • 20+ AI Models - Image generation, audio transcription, LLMs, and more
  • Simple Integration - Works with any MCP-compatible client
  • Sync & Async - Get results immediately or poll for long-running tasks
  • File Uploads - Upload local files for processing

Installation

For Claude Desktop

Add to your claude_desktop_config.json:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "theta-edgecloud": {
      "command": "npx",
      "args": ["@thetalabs/on-demand-api-mcp"],
      "env": {
        "THETA_API_KEY": "your-api-key-here"
      }
    }
  }
}

For Claude Code

claude mcp add theta-edgecloud -e THETA_API_KEY=your-api-key-here -- npx @thetalabs/on-demand-api-mcp

Replace your-api-key-here with your actual API key.

Verify it's working: ``bash claude mcp list ``

You should see theta-edgecloud with status ✓ Connected.

Getting Your API Key

  1. Visit https://www.thetaedgecloud.com/dashboard/api-keys
  2. Create a new API key
  3. Add it to your MCP configuration

Available Tools

list_services

Discover available AI models and their capabilities.

list_services()
list_services(category="image")

infer

Run AI inference on any model.

# Transcribe audio
infer(service="whisper", input={"audio_filename": "https://example.com/audio.wav"})

# Generate an image
infer(service="flux-1-schnell", input={"prompt": "A sunset over mountains"})

# Chat with an LLM
infer(service="llama-3-1-8b", input={"messages": [{"role": "user", "content": "Hello!"}]})

Parameters:

  • service (required) - Service alias (e.g., "whisper", "flux-1-schnell")
  • input (required) - Input parameters (varies by service)
  • wait (optional) - Seconds to wait for result (0-60, default 30)
  • variant (optional) - Model variant if available (e.g., "turbo")

get_request_status

Check the status of an async inference request.

get_request_status(request_id="infer_abc123")

get_upload_url

Get a presigned URL to upload a local file.

get_upload_url(service="whisper", input_field="audio_filename")

Example Conversations

User: "What AI models are available on Theta EdgeCloud?"

Claude: calls list_services() "Here are the available models..."

---

User: "Transcribe this audio file: https://example.com/meeting.wav"

Claude: calls infer(service="whisper", input={"audio_filename": "..."}) "Here's the transcription..."

---

User: "Generate an image of a cyberpunk cityscape"

Claude: calls infer(service="flux-1-schnell", input={"prompt": "cyberpunk cityscape at night, neon lights"}) "Here's your image: [URL]"

Configuration

Environment Variables

| Variable | Description | Required | |----------|-------------|----------| | THETA_API_KEY | Your Theta EdgeCloud API key | Yes | | THETA_API_BASE_URL | API base URL (default: https://api.thetaedgecloud.com) | No |

Development

# Clone the repo
git clone https://github.com/thetalabs/on-demand-api-mcp
cd on-demand-api-mcp

# Install dependencies
npm install

# Build
npm run build

# Run locally
THETA_API_KEY=your-key npm start

Publishing

1. Publish to npm

# Login to npm (if not already)
npm login

# Publish the package
npm publish --access public

The package will be available as @thetalabs/on-demand-api-mcp on npm.

2. Register with MCP Registry

The MCP Registry is the official directory for MCP servers. Registering makes the server discoverable by MCP-compatible clients.

# Clone the registry repo
git clone https://github.com/modelcontextprotocol/registry
cd registry

# Build the publisher tool
make publisher

# Publish your server (requires authentication)
./bin/mcp-publisher --help

Namespace options:

| Namespace Type | Example | Verification | |----------------|---------|--------------| | GitHub-based | io.github.thetalabs/on-demand-api-mcp | GitHub OAuth | | Domain-based | thetaedgecloud.com/on-demand-api-mcp | DNS or HTTP challenge |

3. Automated Publishing (CI/CD)

For GitHub Actions, use GitHub OIDC authentication:

# .github/workflows/publish.yml
name: Publish to MCP Registry
on:
  release:
    types: [published]

jobs:
  publish:
    runs-on: ubuntu-latest
    permissions:
      id-token: write
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-node@v4
        with:
          node-version: '20'
      - run: npm ci && npm run build
      - run: npm publish --access public
      # Add MCP registry publishing step here

License

MIT

Links

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