open-index/open-npm huggingface dataset:
npm package: @iflow-mcp/sentry-issues-mcp
Description: a mcp server to get sentry issue by id or url for LLM
Author: lee62
Latest version: 1.0.5

# sentry-issue-mcp

[![中文文档](https://img.shields.io/badge/中文文档-查看-red)](README_cn.md)
[![English](https://img.shields.io/badge/English-Read-blue)](README.md)
[![smithery badge](https://smithery.ai/badge/@Leee62/sentry-issues-mcp)](https://smithery.ai/server/@Leee62/sentry-issues-mcp)

## Description

> ⚠️ Getting issues is deprecated as of version 1.0.5. The response structure is so similar to the event API that it's considered redundant.

This is a mcp for sentry issue.\
It supports 2 tools to get a issue or list of issues.\
U can let LLM analysis the Res, or u want to do.

## Feature

- EZ size
- EZ understand
- EZ tiny

## Tools

- get_single_event
  - get a event detail infos, tiny mode return stack info, huge mode return all info
  - inputs:
    - url_or_id: sentry event url or sentry event id
    - organization_id_or_slug: sentry organization id or slug, it can be undefined
    - project_id_or_slug: sentry project id or slug, it can be undefined
    - mode: tiny or huge, it can be undefined
- get_project_events
  - get list of events, tiny mode return id and title, huge mode return all info
  - inputs:
    - project_id_or_slug: sentry project id or slug
    - organization_id_or_slug: sentry organization id or slug, it can be undefined
    - mode: tiny or huge, it can be undefined

## QuickStart

this is MCP Server Config

```json
  "mcpServers": {
    "sentry-issue-mcp": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "sentry-issues-mcp@latest"
      ],
      "env": {
        "SENTRY_HOST": "<your_sentry_host>",
        "SENTRY_ORG": "<your_sentry_org>",
        "SENTRY_PROJ": "<your_sentry_proj>",
        "SENTRY_USER_TOKEN": "<your_sentry_user_token>"
      }
    }
  }
```

## Case

- Ask LLM to analysis one issue by url or id
  1. input "analysis the issue, and give me the reason of it, and tell me how to fix it, {sentry_issue_url}"
  2. if ur LLM is SMART🧠, it will call tools
  3. u will get result
- Ask LLM to find Today most dangerous issue (PS: default val of sentry time period is "24h")
  1. input "find today most dangerous issue, and give me the reason of it, and tell me how to fix it"
  2. if ur LLM is SMART🧠, it will call tools
  3. u will get result

## License

MIT
npm package: @iflow-mcp/server-cmd
Description: MCP server for executing CMD and SSH commands
Author: Phiality
Latest version: 1.0.0

# CMD MCP Server

[![smithery badge](https://smithery.ai/badge/server-cmd)](https://smithery.ai/server/server-cmd)
![npm downloads](https://img.shields.io/npm/dt/server-cmd)
A Model Context Protocol (MCP) server implementation for executing CMD commands on both Windows and Linux, as well as allowing SSH connections. This server allows you to integrate command-line operations with MCP-compatible applications.

<a href="https://glama.ai/mcp/servers/s83mqs6123"><img width="380" height="200" src="https://glama.ai/mcp/servers/s83mqs6123/badge" alt="cmd-mcp-server MCP server" /></a>

## Features

- Execute CMD commands through MCP
- TypeScript implementation
- Built on the official MCP SDK
- Cross-platform compatibility

## Installation

### Installing via Smithery

To install CMD Server for Claude Desktop automatically via [Smithery](https://smithery.ai/server/server-cmd):

```bash
npx -y @smithery/cli install server-cmd --client claude
```

### Manual Installation
```bash
npm install server-cmd
```

## Prerequisites

- Node.js (v16 or higher recommended)
- npm or yarn package manager

## Usage

```typescript
import { MCPCmdServer } from 'server-cmd';

// Initialize the server
const server = new MCPCmdServer();

// Start the server
server.start();
```

## Configuration

The server can be configured through environment variables or a configuration object:

```typescript
const config = {
  // Add your configuration options here
};

const server = new MCPCmdServer(config);
```

## Development

To set up the development environment:

1. Clone the repository:
```bash
git clone https://github.com/PhialsBasement/CMD-MCP-Server.git
cd CMD-MCP-Server
```

2. Install dependencies:
```bash
npm install
```

3. Build the project:
```bash
npm run build
```

## Scripts

- `npm run build` - Compile TypeScript to JavaScript
- `npm run prepare` - Prepare the package for publishing

## Dependencies

- `@modelcontextprotocol/sdk`: ^1.0.1
- `glob`: ^10.3.10
- `zod-to-json-schema`: ^3.23.5

## Contributing

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

## License

This project is licensed under the MIT License - see the LICENSE file for details.

## Security

Please note that executing command-line operations can be potentially dangerous. Make sure to implement proper security measures and input validation when using this server in production environments.

## Support

For issues and feature requests, please use the [GitHub issue tracker](https://github.com/PhialsBasement/CMD-MCP-Server/issues).
npm package: @iflow-mcp/server-hyperliquid
Description: MCP server for Hyperliquid
Author: mektigboy
Latest version: 0.0.1

# Hyperliquid MCP Server

An MCP server implementation that integrates the Hyperliquid SDK.

## Tools

- **get_all_mids**

  - Retrieve mid prices for all coins on Hyperliquid
  - No required inputs

- **get_candle_snapshot**

  - Get historical candlestick data for any token
  - Inputs:
    - `coin` (string): Token symbol
    - `interval` (string): Time interval (e.g., '15m', '1h')
    - `startTime` (number): Start time in milliseconds since epoch
    - `endTime` (number, optional): End time in milliseconds since epoch

- **get_l2_book**
  - Access the L2 order book for any token
  - Inputs:
    - `symbol` (string): Token symbol

### Usage with Claude Desktop

Add this to your `claude_desktop_config.json`:

### NPX

```json
{
  "mcpServers": {
    "brave-search": {
      "command": "npx",
      "args": ["-y", "@mektigboy/server-hyperliquid"]
    }
  }
}
```

## License

This MCP server is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.
npm package: @iflow-mcp/server-koboldai
Description: MCP server for KoboldAI API integration
Author: Phiality
Latest version: 1.0.0

[![MseeP.ai Security Assessment Badge](https://mseep.net/pr/phialsbasement-koboldcpp-mcp-server-badge.png)](https://mseep.ai/app/phialsbasement-koboldcpp-mcp-server)

# Kobold MCP Server

A Model Context Protocol (MCP) server implementation for interfacing with KoboldAI. This server enables integration between KoboldAI's text generation capabilities and MCP-compatible applications.

## Features

- Text generation with KoboldAI
- Chat completion with persistent memory
- OpenAI-compatible API endpoints
- Stable Diffusion integration
- Built on the official MCP SDK
- TypeScript implementation

<a href="https://glama.ai/mcp/servers/a2xd4hoij7"><img width="380" height="200" src="https://glama.ai/mcp/servers/a2xd4hoij7/badge" alt="Kobold Server MCP server" /></a>

## Installation

```bash
npm install kobold-mcp-server
```

## Prerequisites

- Node.js (v16 or higher)
- npm or yarn package manager
- Running KoboldAI instance

## Usage

```typescript
import { KoboldMCPServer } from 'kobold-mcp-server';

// Initialize the server
const server = new KoboldMCPServer();

// Start the server
server.start();
```

## Configuration

The server can be configured through environment variables or a configuration object:

```typescript
const config = {
  apiUrl: 'http://localhost:5001' // KoboldAI API endpoint
};
const server = new KoboldMCPServer(config);
```

## Supported APIs

- Core KoboldAI API (text generation, model info)
- Chat completion with conversation memory
- Text completion (OpenAI-compatible)
- Stable Diffusion integration (txt2img, img2img)
- Audio transcription and text-to-speech
- Web search capabilities

## Development

1. Clone the repository:
```bash
git clone https://github.com/yourusername/kobold-mcp-server.git
cd kobold-mcp-server
```

2. Install dependencies:
```bash
npm install
```

3. Build the project:
```bash
npm run build
```

## Dependencies

- `@modelcontextprotocol/sdk`: ^1.0.1
- `node-fetch`: ^2.6.1
- `zod`: ^3.20.0
- `zod-to-json-schema`: ^3.23.5

## Contributing

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

## License

MIT License - see LICENSE file for details.

## Support

For issues and feature requests, please use the GitHub issue tracker.
npm package: @iflow-mcp/server-macos
Description: MCP server for macOS system operations
Author: Michael Latman
Latest version: 0.1.0

# @mcp-get-community/server-macos

A Model Context Protocol server that provides macOS-specific system information and operations.

## Features

- System information retrieval (CPU, Memory, Disk, Network)
- Native macOS notifications

## Installation

```bash
npx @michaellatman/mcp-get@latest install @mcp-get-community/server-macos
```

## Configuration

Add this to your configuration:

```json
{
  "mcpServers": {
    "@mcp-get-community/server-macos": {
      "runtime": "node",
      "command": "npx",
      "args": [
        "-y",
        "@mcp-get-community/server-macos"
      ]
    }
  }
}
```

## Tools

### systemInfo

Retrieves system information from macOS.

Parameters:
- `category` (required): One of 'cpu', 'memory', 'disk', 'network', or 'all'

Example:
```json
{
  "name": "systemInfo",
  "arguments": {
    "category": "cpu"
  }
}
```

### sendNotification

Sends a native macOS notification.

Parameters:
- `title` (required): Title of the notification
- `message` (required): Content of the notification
- `sound` (optional): Whether to play a sound (default: true)

Example:
```json
{
  "name": "sendNotification",
  "arguments": {
    "title": "Hello",
    "message": "This is a test notification",
    "sound": true
  }
}
```

## Development

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

2. Build the project:
```bash
npm run build
```

3. Run in development mode:
```bash
npm run dev
```

## License

MIT
npm package: @iflow-mcp/server-moz-readability
Description: Fetch just the main content and convert it to markdown. Strips away all the junk, which is cleaner for LLMs and reduces your overall context window.
Author: Max Zimmer
Latest version: 1.0.3

# Mozilla Readability Parser MCP Server

An [model context protocol (MCP)](https://github.com/modelcontextprotocol) server that extracts and transforms webpage content into clean, LLM-optimized Markdown. Returns article title, main content, excerpt, byline and site name. Uses [Mozilla's Readability algorithm](https://github.com/mozilla/readability) to remove ads, navigation, footers and non-essential elements while preserving the core content structure. [More about MCP](https://modelcontextprotocol.io/introduction).

<a href="https://glama.ai/mcp/servers/jdcx8fmajm"><img width="380" height="200" src="https://glama.ai/mcp/servers/jdcx8fmajm/badge" alt="Mozilla Readability Parser Server MCP server" /></a>

## Features
- Removes ads, navigation, footers and other non-essential content
- Converts clean HTML into well-formatted Markdown (also uses Turndown)
- Returns article metadata (title, excerpt, byline, site name)
- Handles errors gracefully

## Why Not Just Fetch?
Unlike simple fetch requests, this server:
- Extracts only relevant content using Mozilla's Readability algorithm
- Eliminates noise like ads, popups, and navigation menus
- Reduces token usage by removing unnecessary HTML/CSS
- Provides consistent Markdown formatting for better LLM processing
- Includes useful metadata about the content

## Installation

### Installing via Smithery

To install Mozilla Readability Parser for Claude Desktop automatically via [Smithery](https://smithery.ai/server/server-moz-readability):

```bash
npx -y @smithery/cli install server-moz-readability --client claude
```

### Manual Installation
```bash
npm install server-moz-readability
```

## Tool Reference

### `parse`
Fetches and transforms webpage content into clean Markdown.

**Arguments:**
```json
{
  "url": {
    "type": "string",
    "description": "The website URL to parse",
    "required": true
  }
}
```

**Returns:**
```json
{
  "title": "Article title",
  "content": "Markdown content...",
  "metadata": {
    "excerpt": "Brief summary",
    "byline": "Author information",
    "siteName": "Source website name"
  }
}
```

## Usage with Claude Desktop
Add to your `claude_desktop_config.json`:
```json
{
  "mcpServers": {
    "readability": {
      "command": "npx",
      "args": ["-y", "server-moz-readability"]
    }
  }
}
```

## Dependencies
- @mozilla/readability - Content extraction
- turndown - HTML to Markdown conversion
- jsdom - DOM parsing
- axios - HTTP requests

## License
MIT