TikTok MCP Service

A Model Context Protocol service for TikTok video discovery and metadata extraction. This service provides a robust interface for searching TikTok videos by hashtags and retrieving trending content, with built-in anti-detection measures and error handling.

Features

Search videos by hashtags
Configurable video count per search (default: 30)
Anti-bot detection measures
Proxy support
Automatic API session management
Rate limiting and error handling
Health status monitoring

Configuration

The service uses environment variables for configuration. Create a .env file with:

ms_token=your_tiktok_ms_token  # Optional but recommended to avoid bot detection
TIKTOK_PROXY=your_proxy_url    # Optional proxy configuration

Installation and Setup

Installing via Smithery

To install TikTok Video Search for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @terrylinhaochen/tiktok_mcp --client claude

Installing Manually

# Install dependencies
poetry install

# Install browser automation dependencies
poetry run python -m playwright install

# Start the service
poetry run python -m tiktok_mcp_service.main

Claude Desktop Integration

Once your service is running, you can integrate it with Claude Desktop. Since we're using Poetry for dependency management, make sure to run the MCP CLI commands through Poetry:

# Navigate to the project directory
cd /path/to/tiktok-mcp-service

# Install the service in Claude Desktop with Poetry in editable mode
poetry run mcp install tiktok_mcp_service/main.py --with-editable . -f .env

# Optional: Install with a custom name
poetry run mcp install tiktok_mcp_service/main.py --name "TikTok Video Search" --with-editable . -f .env

After installation, the service will be available in Claude Desktop and will run using Poetry for proper dependency management.

API Endpoints

Health Check

GET /health - Check service health and API initialization status

{
  "status": "running",
  "api_initialized": true,
  "service": {
    "name": "TikTok MCP Service",
    "version": "0.1.0",
    "description": "A Model Context Protocol service for searching TikTok videos"
  }
}

Search Videos

POST /search - Search for videos with hashtags
```
{
  "search_terms": ["python", "coding"],
  "count": 30  // Optional, defaults to 30
}
```
Response includes video URLs, descriptions, and engagement statistics (views, likes, shares, comments).

Resource Management

POST /cleanup - Clean up resources and API sessions

Error Handling

The service includes comprehensive error handling for:

API initialization failures
Bot detection issues
Network errors
Rate limiting
Invalid search terms

Development

Built with:

TikTokApi
FastMCP
Poetry for dependency management
Playwright for browser automation

License

MIT# tiktok_mcp

TikTok API Limitations

Important Notice: TikTok has implemented strict anti-scraping measures that limit API access.As a result, this service provides the following functionality:

Mock Data Mode: When TikTok blocks API access (which is currently the case), the serviceprovides realistic-looking simulated results that are relevant to the search terms. This ensuresthat your Claude integration continues to function even when TikTok restricts access.
API Access Attempts: The service still attempts to use the TikTok API first, but will quicklyfall back to mock data if the API is unavailable or returns errors.
Transparency: When mock data is provided, this is clearly indicated in the response via thetransformations field, which includes a note explaining that simulated results are being shown.

This implementation ensures your service remains operational despite TikTok's anti-scraping measures.

TikTok MCP Service