open-index/open-npm huggingface dataset:
npm package: @mseep/mcp-testrail
Description: This Model Context Protocol (MCP) server provides tools for interacting with TestRail directly from Claude AI and other MCP-supported clients like Cursor. It allows you to manage test cases, projects, suites, runs, and more without leaving your conversati
Author: bun913
Latest version: 0.12.0

# TestRail MCP Server

This Model Context Protocol (MCP) server provides tools for interacting with TestRail directly from Claude AI and other MCP-supported clients like Cursor. It allows you to manage test cases, projects, suites, runs, and more without leaving your conversation with the AI.

## Available Tools

The TestRail MCP server provides the following tools:

| Category | Tools |
|----------|-------|
| **Projects** | `getProjects`, `getProject` |
| **Suites** | `getSuites`, `getSuite`, `addSuite`, `updateSuite` |
| **Cases** | `getCase`, `getCases`, `addCase`, `updateCase`, `deleteCase`, `getCaseTypes`, `getCaseFields`, `copyToSection`, `moveToSection`, `getCaseHistory`, `updateCases` |
| **Sections** | `getSection`, `getSections`, `addSection`, `moveSection`, `updateSection`, `deleteSection` |
| **Runs** | `getRuns`, `getRun`, `addRun`, `updateRun` |
| **Tests** | `getTests`, `getTest` |
| **Results** | `getResults`, `getResultsForCase`, `getResultsForRun`, `addResultForCase`, `addResultsForCases` |
| **Plans** | `getPlans` |
| **Milestones** | `getMilestones` |
| **Shared Steps** | `getSharedSteps` |

## Usage

You can connect this MCP server by setting like the below. This method uses `npx` to automatically download and run the latest version of the package, eliminating the need for local installation.

```json
// Example configuration using npx
{
  "mcpServers": {
    "testrail": {
      "command": "npx",
      "args": ["@bun913/mcp-testrail@latest"],
      "env": {
        "TESTRAIL_URL": "https://your-instance.testrail.io", // Replace with your TestRail URL
        "TESTRAIL_USERNAME": "your-email@example.com", // Replace with your TestRail username
        "TESTRAIL_API_KEY": "YOUR_API_KEY" // Replace with your TestRail API key
      }
    }
  }
}
```

## Troubleshooting

- **`spawn node ENOENT` errors**: Ensure that Node.js is properly installed and in your PATH.
- **Connection issues**: Verify that the server is running and the URL is correctly configured in your MCP client.
- **Authentication issues**: Check your TestRail API credentials in the `.env` file.
- **SSE connection errors**: If you see `SSE error: TypeError: fetch failed: connect ECONNREFUSED`, make sure the server is running on the specified port.
- **Your conversation is too long**: Pleae use `limit` and `offset` parameter for test cases

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

## Acknowledgements

- [TestRail API](https://docs.testrail.techmatrix.jp/testrail/docs/702/api/)
- [Model Context Protocol SDK](https://github.com/modelcontextprotocol/typescript-sdk)
npm package: @mseep/mcp-triple-whale
Description: An MCP server for accessing Triple Whale e-commerce analytics data through the Triple Whale API.
Latest version: 1.0.0

# Triple Whale MCP Server

    An MCP server for accessing Triple Whale e-commerce analytics data through the Triple Whale API.

    ## Features

    - Access to Blended Stats Table data
    - Shop information retrieval
    - Available metrics and dimensions discovery
    - MCP Inspector integration for testing

    ## Setup

    1. Clone this repository
    2. Install dependencies:
       ```
       npm install
       ```
    3. Create a `.env` file with your Triple Whale API credentials:
       ```
       TRIPLE_WHALE_API_KEY=your_api_key_here
       TRIPLE_WHALE_SHOP_ID=your_shop_id_here
       ```
    4. Run the server:
       ```
       npm run dev
       ```

    ## Testing with MCP Inspector

    To test the server with the MCP Inspector:

    ```
    npm run inspect
    ```

    This will open a web interface where you can:
    - Test all available tools with custom inputs
    - Browse available resources
    - View server logs and responses

    ## Available Tools

    - `get_blended_stats`: Get blended statistics from Triple Whale
    - `get_shop_info`: Get information about the configured shop
    - `get_available_metrics`: Get list of available metrics for the shop
    - `get_available_dimensions`: Get list of available dimensions for the shop

    ## Available Resources

    - `triplewhale://shop`: Information about the configured shop
    - `triplewhale://metrics`: List of available metrics
    - `triplewhale://dimensions`: List of available dimensions

    ## Example Usage

    ### Getting Blended Stats

    ```json
    {
      "dateRange": {
        "start": "2023-01-01",
        "end": "2023-01-31"
      },
      "metrics": [
        {
          "id": "revenue"
        },
        {
          "id": "orders"
        }
      ],
      "dimensions": [
        {
          "id": "utm_source"
        }
      ],
      "limit": 10
    }
    ```

    ## API Documentation

    For more information about the Triple Whale API, see:
    - [Blended Stats Table Documentation](https://triplewhale.readme.io/docs/blended-stats-table)
    - [Triple Whale API Reference](https://triplewhale.readme.io/reference/introduction-to-the-triple-whale-api)
npm package: @mseep/mcp-tts
Description: [![smithery badge](https://smithery.ai/badge/@PhialsBasement/zonos-tts-mcp)](https://smithery.ai/server/@PhialsBasement/zonos-tts-mcp)
Latest version: 1.0.0

# Zonos MCP Integration
[![smithery badge](https://smithery.ai/badge/@PhialsBasement/zonos-tts-mcp)](https://smithery.ai/server/@PhialsBasement/zonos-tts-mcp)

A Model Context Protocol integration for Zonos TTS, allowing Claude to generate speech directly.

## Setup

### Installing via Smithery

To install Zonos TTS Integration for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@PhialsBasement/zonos-tts-mcp):

```bash
npx -y @smithery/cli install @PhialsBasement/zonos-tts-mcp --client claude
```

### Manual installation

1. Make sure you have Zonos running with our API implementation ([PhialsBasement/zonos-api](https://github.com/PhialsBasement/Zonos-API))

2. Install dependencies:
```bash
npm install @modelcontextprotocol/sdk axios
```

3. Configure PulseAudio access:
```bash
# Your pulse audio should be properly configured for audio playback
# The MCP server will automatically try to connect to your pulse server
```

4. Build the MCP server:
```bash
npm run build
# This will create the dist folder with the compiled server
```

5. Add to Claude's config file:
Edit your Claude config file (usually in `~/.config/claude/config.json`) and add this to the `mcpServers` section:

```json
"zonos-tts": {
  "command": "node",
  "args": [
    "/path/to/your/zonos-mcp/dist/server.js"
  ]
}
```

Replace `/path/to/your/zonos-mcp` with the actual path where you installed the MCP server.

## Using with Claude

Once configured, Claude automatically knows how to use the `speak_response` tool:

```python
speak_response(
    text="Your text here",
    language="en-us",  # optional, defaults to en-us
    emotion="happy"    # optional: "neutral", "happy", "sad", "angry"
)
```

## Features

- Text-to-speech through Claude
- Multiple emotions support
- Multi-language support
- Proper audio playback through PulseAudio

## Requirements

- Node.js
- PulseAudio setup
- Running instance of Zonos API (PhialsBasement/zonos-api)
- Working audio output device

## Notes

- Make sure both the Zonos API server and this MCP server are running
- Audio playback requires proper PulseAudio configuration
npm package: @mseep/mcp-typescript-server-starter
Description: ModelContextProtocol typescript server starter
Latest version: 0.1.0

# DomainGenius MCP Server

The DomainGenius MCP server powers the domain search functionality of [DomainGenius](https://domaingenius.ch/), providing real-time domain availability checks and pricing information.

## Features

- Real-time domain availability checking
- Domain pricing information retrieval
- Automatic TLD handling (defaults to .com if not specified)
- Error handling and detailed response format
- Seamless integration with AI-powered domain search tools

## Quick Start

1. Install dependencies:
```bash
pnpm install
```

2. Set up your environment:
```bash
cp .env.example .env
```
Then add your Vercel API token to the `.env` file.

3. Build and run:
```bash
pnpm run build
pnpm start
```

## Development

For development with hot-reloading:
```bash
pnpm run dev
```

## License

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