npm package: @langgpt/mcp-deepseek-update-server
Description: MCP server for monitoring DeepSeek updates across multiple platforms
Author: LangGPT
Latest version: 1.0.0

# MCP DeepSeek Update Server

A Model Context Protocol (MCP) server that monitors DeepSeek updates across multiple platforms including official news, GitHub repositories, HuggingFace models, and Twitter/X announcements.

## Features

🔍 **Multi-Platform Monitoring**
- Official DeepSeek news and announcements
- GitHub repository updates and releases
- HuggingFace model releases
- Twitter/X official account updates (@deepseek_ai)

📊 **Rich Data Integration**
- Real-time RSS feeds for Twitter updates
- GitHub API integration for repository monitoring
- HuggingFace API for model releases
- Smart caching to prevent API rate limits

⚡ **MCP Protocol Compliance**
- Standard MCP tools for querying updates
- Resource endpoints for accessing cached data
- Configurable time ranges and filtering options
- Error handling and fallback mechanisms

## Installation

### Option 1: NPX (Recommended - No Installation Required)

```bash
# Run directly with npx
npx langgpt

# Initialize configuration
npx langgpt --init

# Test all data sources
npx langgpt --test

# Get Claude Desktop configuration
npx langgpt --config-claude
```

### Option 2: Global Installation

```bash
npm install -g langgpt
langgpt --help
```

### Option 3: Build from Source

```bash
git clone <repository-url>
cd mcp-deepseek-update-server
npm install
npm run build
```

## Usage

### As MCP Server (stdio)

Add to your MCP client configuration:

```json
{
  "mcpServers": {
    "deepseek-updates": {
      "command": "npx",
      "args": ["langgpt"]
    }
  }
}
```

**For Claude Desktop specifically:**

```bash
# Get the exact configuration
npx langgpt --config-claude
```

### As HTTP Server

```bash
# HTTP server not yet implemented
# Use stdio mode for now
npx langgpt
```

## Available Tools

### `check_deepseek_updates`
Get recent DeepSeek updates from all or specific sources.

**Parameters:**
- `days` (number, default: 7): Number of days to look back
- `source` (string, default: "all"): Source to check ("all", "news", "github", "huggingface", "twitter")  
- `includeMetrics` (boolean, default: true): Include engagement metrics

**Example:**
```json
{
  "name": "check_deepseek_updates",
  "arguments": {
    "days": 14,
    "source": "twitter",
    "includeMetrics": true
  }
}
```

### `get_latest_models`
Get the latest DeepSeek models from HuggingFace.

**Parameters:**
- `limit` (number, default: 10): Number of models to return
- `includeStats` (boolean, default: true): Include download/like statistics

### `check_deepseek_news`
Check for official DeepSeek news on a specific date.

**Parameters:**
- `date` (string): Date in YYMMDD format (e.g., "250601" for 2025-06-01)

### `get_twitter_updates`
Get recent tweets from DeepSeek's official Twitter account.

**Parameters:**
- `count` (number, default: 10, max: 50): Number of tweets to fetch
- `includeReplies` (boolean, default: false): Include reply tweets

## Resources

### `deepseek://updates/{source}`
Access cached update data for specific sources.

### `deepseek://models/latest`
Access latest model information from HuggingFace.

### `deepseek://news/{date}`
Access news data for specific dates.

## Configuration

Environment variables:

```bash
# Optional GitHub token for higher API limits
GITHUB_TOKEN=your_github_personal_access_token

# Cache duration in minutes (default: 15)
CACHE_DURATION=15

# Primary RSS URL for Twitter (default: rsshub.app)
TWITTER_RSS_PRIMARY=https://rsshub.app/twitter/user/deepseek_ai

# Backup RSS URLs (comma-separated)
TWITTER_RSS_BACKUP=https://rsshub.rssforever.com/twitter/user/deepseek_ai

# HTTP server port (default: 3000)
PORT=3000
```

## Data Sources

1. **Official News**: `https://api-docs.deepseek.com/zh-cn/news/`
2. **GitHub**: `https://github.com/deepseek-ai` organization
3. **HuggingFace**: `https://huggingface.co/deepseek-ai` organization  
4. **Twitter/X**: `@deepseek_ai` via RSShub RSS feeds

## Error Handling

The server implements robust error handling:
- Automatic fallback between multiple RSS sources for Twitter
- Rate limit awareness for GitHub API
- Graceful degradation when services are unavailable
- Comprehensive logging for debugging

## Contributing

1. Fork the repository
2. Create your feature branch (`git checkout -b feature/amazing-feature`)
3. Commit your changes (`git commit -m 'Add some amazing feature'`)
4. Push to the branch (`git push origin feature/amazing-feature`)
5. Open a Pull Request

## License

MIT License - see [LICENSE](LICENSE) file for details.

## Support

- Report issues on GitHub
- Check the [MCP documentation](https://modelcontextprotocol.io) for integration help
- Join the community discussions