open-index/open-npm huggingface dataset:
npm package: @iflow-mcp/psycharch-minimax-mcp-tools
Description: Async MCP server with Minimax API integration for image generation and text-to-speech
Author: PsychArch
Latest version: 2.2.3

# Minimax MCP 工具

![Banner](assets/banner.png)

Minimax AI 集成的模型上下文协议(MCP)服务器，提供异步图像生成和文本转语音功能，具备高级速率限制和错误处理。

[English](README.md) | 简体中文

### MCP 配置
添加到你的 MCP 设置中：
```json
{
  "mcpServers": {
    "minimax-mcp-tools": {
      "command": "npx",
      "args": ["minimax-mcp-tools"],
      "env": {
        "MINIMAX_API_KEY": "your_api_key_here"
      }
    }
  }
}
```

## 异步设计 - 专为大规模内容制作而生

此MCP服务器采用**异步提交-屏障模式**，专为**批量内容创作**而设计：

🎬 **配音幻灯片制作** - 并行生成数十张幻灯片图像和对应的配音内容  
📚 **AI驱动的有声书制作** - 同时生成多个章节，支持不同音色的角色配音  
🖼️ **网站素材批量生成** - 为网页项目创建统一风格的视觉和音频元素  
🎯 **多媒体内容流水线** - 完美适配需要图文音并茂的LLM驱动内容工作流

### 架构优势：
1. **提交阶段**：工具立即返回任务ID，任务在后台执行
2. **智能限速**：自适应速率限制（图像10 RPM，语音20 RPM）支持突发容量
3. **屏障同步**：`task_barrier`等待所有任务并返回综合结果
4. **批量优化**：提交多个任务以饱和速率限制，然后一次屏障获得最大吞吐量

## 架构
```mermaid
sequenceDiagram
    participant User as 用户
    participant MCP as MCP服务器
    participant TM as 任务管理器
    participant API as Minimax API

    Note over User, API: 异步提交-屏障模式

    User->>MCP: submit_image_generation(prompt1)
    MCP->>TM: submitImageTask()
    TM-->>MCP: taskId: img-001
    MCP-->>User: "任务 img-001 已提交"
    
    par 后台执行（速率限制）
        TM->>API: POST /image/generate
        API-->>TM: 图像数据 + 保存文件
    end

    User->>MCP: submit_speech_generation(text1)
    MCP->>TM: submitTTSTask()
    TM-->>MCP: taskId: tts-002
    MCP-->>User: "任务 tts-002 已提交"
    
    par 后台执行（速率限制）
        TM->>API: POST /speech/generate
        API-->>TM: 音频数据 + 保存文件
    end

    User->>MCP: submit_image_generation(prompt2)
    MCP->>TM: submitImageTask()
    TM-->>MCP: taskId: img-003
    MCP-->>User: "任务 img-003 已提交"

    par 后台执行（速率限制）
        TM->>API: POST /image/generate (排队)
        API-->>TM: 图像数据 + 保存文件
    end

    User->>MCP: task_barrier()
    MCP->>TM: barrier()
    TM->>TM: 等待所有任务
    TM-->>MCP: 结果摘要
    MCP-->>User: ✅ 所有任务已完成<br/>文件可在指定路径获取

    Note over User, API: 立即任务提交 + 后台速率限制执行
```

## 工具

### `submit_image_generation`
**提交图像生成任务** - 异步生成图像。

**必需参数：** `prompt`, `outputFile`  
**可选参数：** `aspectRatio`, `customSize`, `seed`, `subjectReference`, `style`

### `submit_speech_generation`
**提交语音生成任务** - 异步文本转语音。

**必需参数：** `text`, `outputFile`  
**可选参数：** `highQuality`, `voiceId`, `speed`, `volume`, `pitch`, `emotion`, `format`, `sampleRate`, `bitrate`, `languageBoost`, `intensity`, `timbre`, `sound_effects`

### `task_barrier`
**等待任务完成** - 等待所有已提交的任务完成并检索结果。对于批处理至关重要。

## 许可证
MIT
npm package: @iflow-mcp/punkpeye-mcp-ping
Description: Pings a host and returns the result
Author: Frank Fiegel
Latest version: 1.0.0

# MCP Ping

Pings a host and returns the result.

> [!NOTE]
> This MCP server was made predominantly to [demonstrate](https://github.com/punkpeye/mcp-ping/blob/main/src/createServer.ts) how to use [FastMCP](https://github.com/punkpeye/fastmcp).

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

## Usage

```bash
mcp-ping
```

## Configuration

Server supports the following environment variables:

| Name       | Description                         |
| ---------- | ----------------------------------- |
| HTTP_PROXY | URL of HTTP proxy to use (optional) |

## MCP Server Profile

```json
{
  "prompts": [],
  "resources": [],
  "tools": [
    {
      "annotations": {
        "openWorldHint": false,
        "readOnlyHint": true,
        "title": "Ping"
      },
      "description": "Pings a host and returns the result",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "host": {
            "description": "The hostname or URL to ping (e.g., 'google.com' or 'https://google.com')",
            "type": "string"
          }
        },
        "required": ["host"],
        "type": "object"
      },
      "name": "ping"
    }
  ]
}
```

## Tools

### `ping` tool example response

```bash
Ping results for glama.ai:

PING glama.ai (37.16.29.120): 56 data bytes
64 bytes from 37.16.29.120: icmp_seq=0 ttl=55 time=11.273 ms
64 bytes from 37.16.29.120: icmp_seq=1 ttl=55 time=11.353 ms
64 bytes from 37.16.29.120: icmp_seq=2 ttl=55 time=11.455 ms
64 bytes from 37.16.29.120: icmp_seq=3 ttl=55 time=12.634 ms

--- glama.ai ping statistics ---
4 packets transmitted, 4 packets received, 0.0% packet loss
round-trip min/avg/max/stddev = 11.273/11.679/12.634/0.555 ms
```

## Testing

```bash
npm run test
```
npm package: @iflow-mcp/puremd-mcp
Description: Model Context Protocol (MCP) server for pure.md, the markdown delivery network for LLMs
Author: pure.md
Latest version: 1.0.3

# pure.md MCP server

[![smithery badge](https://smithery.ai/badge/@puremd/puremd-mcp)](https://smithery.ai/server/@puremd/puremd-mcp)

Welcome to the Model Context Protocol (MCP) server for [pure.md](https://pure.md).

![pure.md - Markdown delivery network for LLMs](https://pure.md/assets/og.png)

[pure.md](https://pure.md) lets your scripts, APIs, apps, agents, etc reliably access web content in markdown format -- simply prefix any URL with `pure.md/`.
It avoids bot detection and renders JavaScript for SPAs, and can convert HTML, PDFs, images, and more into pure markdown. Like a CDN for markdown content, it globally caches responses for future requests to the same resource, relieving stress on origin web servers.

**Without puremd-mcp, local agents may fail to fetch web content.** puremd-mcp teaches MCP clients like Cursor, Windsurf, and Claude Desktop how to adopt the functionality of pure.md, giving them web unblocking and searching capabilities.

puremd-mcp comes with two tools:

- `unblock-url` - Extract markdown from web pages without getting blocked
- `search-web` - Search the web for a query and concatenate results into markdown

The [Model Context Protocol](https://modelcontextprotocol.io/introduction), developed by Anthropic, is an open standard that enables AI systems to seamlessly interact with an ecosystem of tooling. With it, MCP clients like Cursor, Windsurf, and Claude Desktop can learn how to use a variety of APIs and other functionality.

## Authentication

Generating an API key is an optional step that unlocks higher rate limits. If you'd like to use the pure.md MCP server anonymously, simply set your `PUREMD_API_KEY` value to empty string (`""`).

1. Sign up for a new account at [pure.md](https://pure.md) &mdash; it's free to sign up!
2. In the dashboard, generate a new API token
3. Copy the token, and use it for the `PUREMD_API_KEY` value in your MCP client's configuration file (see below)

## Client configuration

### Cursor

Add the following to your `~/.cursor/mcp.json` file:

```json
{
  "mcpServers": {
    "pure.md": {
      "command": "npx",
      "args": ["-y", "puremd-mcp"],
      "env": {
        "PUREMD_API_KEY": "<TOKEN>"
      }
    }
  }
}
```

### Windsurf

Add the following to your `./codeium/windsurf/model_config.json` file:

```json
{
  "mcpServers": {
    "pure.md": {
      "command": "npx",
      "args": ["-y", "puremd-mcp"],
      "env": {
        "PUREMD_API_KEY": "<TOKEN>"
      }
    }
  }
}
```

### Claude Desktop

Add the following to your `~/Library/Application\ Support/Claude/claude_desktop_config.json` file:

```json
{
  "mcpServers": {
    "pure.md": {
      "command": "npx",
      "args": ["-y", "puremd-mcp"],
      "env": {
        "PUREMD_API_KEY": "<TOKEN>"
      }
    }
  }
}
```

### Installing via Smithery

To install puremd-mcp for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@puremd/puremd-mcp):

```bash
npx -y @smithery/cli install @puremd/puremd-mcp --client claude
```