open-index/open-npm huggingface dataset:
npm package: @iflow-mcp/mcp-server-taskwarrior
Description: MCP server for taskwarrior
Author: Brock Wilcox
Latest version: 1.0.1

# TaskWarrior MCP Server

Node.js server implementing Model Context Protocol (MCP) for [TaskWarrior](https://taskwarrior.org/) operations.

<a href="https://glama.ai/mcp/servers/e8w3e1su1x">
  <img width="380" height="200" src="https://glama.ai/mcp/servers/e8w3e1su1x/badge" alt="TaskWarrior Server MCP server" />
</a>

## Features

- View pending tasks
- Filter tasks by project and tags
- Add new tasks with descriptions, due dates, priorities, projects and tags
- Mark tasks as complete

**Note**: This runs your local `task` binary, so TaskWarrior needs to be installed and configured!

> [!WARNING]
> This currently uses task `id` which is an unstable identifier; taskwarrior
> sometimes renumbers tasks when new ones are added or removed. In the future
> this should be more careful, using task UUID instead.

## API

### Tools

- **get_next_tasks**
  - Get a list of all pending tasks
  - Optional filters:
    - `project`: Filter by project name
    - `tags`: Filter by one or more tags

- **add_task**
  - Add a new task to TaskWarrior
  - Required:
    - `description`: Task description text
  - Optional:
    - `due`: Due date (ISO timestamp)
    - `priority`: Priority level ("H", "M", or "L")
    - `project`: Project name (lowercase with dots)
    - `tags`: Array of tags (lowercase)

- **mark_task_done**
  - Mark a task as completed
  - Required:
    - `identifier`: Task ID or UUID

## Usage with Claude Desktop

Add this to your `claude_desktop_config.json`:

```json
{
  "mcpServers": {
    "taskwarrior": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-server-taskwarrior"
      ]
    }
  }
}
```

## Installation

```bash
npm install -g mcp-server-taskwarrior
```

Make sure you have TaskWarrior (`task`) installed and configured on your system.

## Example usage ideas:

* What are my current work tasks?
  * Executes: `task project:work next`
* TODO: Call my sister (high priority)
  * Executes: `task add priority:H Call my sister`
* OK, I've called my sister
  * Executes: `task done 1`

## License

This MCP server is licensed under the MIT License. See the LICENSE file for details.
npm package: @iflow-mcp/mcp-server-tembo
Description: A MCP server or the Tembo Cloud platform API
Author: Darren Baldwin
Latest version: 0.0.0

<h1 align="center">Tembo MCP Server</h1>

<p align="center">An MCP server for the <a href="https://cloud.tembo.io">Tembo Cloud</a> platform API</p>

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

## Installation

### Installing via Smithery

To install Tembo Cloud API for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@tembo-io/mcp-server-tembo):

```bash
npx -y @smithery/cli install @tembo-io/mcp-server-tembo --client claude
```

### Locally

1. Clone this repo

```
git clone https://github.com/tembo-io/mcp-server-tembo.git
```

2. Download [Claude Desktop](https://www.anthropic.com/products/claude-3-opus-desktop)

3. Load the below tembo mcp server json config into Claude Desktop (open claude desktop > click settings > developer)

> [!NOTE]
> You will need to [generate a API key for Tembo Cloud](https://tembo.io/docs/development/api)

```json
{
	"mcpServers": {
		"mcp-server-tembo": {
			"command": "node",
			"env": {
				"TEMBO_API_KEY": "your_tembo_api_key"
			},
			"args": ["/absolute/path/to/cloned/repo/mcp-server-tembo/dist/index.js"]
		}
	}
}
```

### Hosted version

Coming soon.

## Development

```
pnpm run build
```

```
node index.js
```
npm package: @iflow-mcp/mcp-server-to-markdown
Description: MCP server to generate markdown descriptions for files using Cloudflare
Author: Frad LEE
Latest version: 0.1.2

# MCP Server To Markdown ![](https://img.shields.io/badge/A%20FRAD%20PRODUCT-WIP-yellow)

[![Twitter Follow](https://img.shields.io/twitter/follow/FradSer?style=social)](https://twitter.com/FradSer)

[English](README.md) | 简体中文

一个使用 Cloudflare AI 服务将各种文件格式转换为 Markdown 描述的 Model Context Protocol (MCP) 服务器。该服务器提供了标准化的文件转换和描述生成接口。

## 功能特点

- 与 Cloudflare AI 服务无缝集成
- 高效的 Markdown 描述生成
- 全面的文件格式支持
- 与 Cloudflare tomarkdown API 原生集成
- 易用的 MCP 接口
- 跨平台兼容性

## 支持的文件格式

| 类别 | 文件扩展名 |
|----------|----------------|
| 文档 | .pdf |
| 图片 | .jpeg, .jpg, .png, .webp, .svg |
| 网页内容 | .html |
| 数据 | .xml, .csv |
| 电子表格 | .xlsx, .xlsm, .xlsb, .xls, .et, .ods, .numbers |

## 系统要求

- Node.js 18 或更高版本
- 有效的 Cloudflare API Token
- 激活的 Cloudflare Account ID

## 安装

通过 npm 全局安装：

```bash
npm install -g mcp-server-to-markdown
```

## MCP 客户端配置

### Cursor 集成

1. 导航至 Cursor 设置
2. 从侧边栏选择 "MCP"
3. 选择 "Add new global MCP server"
4. 应用以下配置：
    ```json
    {
      "mcpServers": {
        "to-markdown": {
          "command": "mcp-server-to-markdown",
          "args": [
            "CLOUDFLARE_API_TOKEN": "your_api_token"
            "CLOUDFLARE_ACCOUNT_ID": "your_account_id"
          ]
        }
      }
    }
    ```

### Claude Desktop 设置

在 `claude_desktop_config.json` 中添加以下内容：

```json
{
  "mcpServers": {
    "to-markdown": {
      "command": "mcp-server-to-markdown",
      "args": [
            "CLOUDFLARE_API_TOKEN": "your_api_token"
            "CLOUDFLARE_ACCOUNT_ID": "your_account_id"
          ]
    }
  }
}
```

### ChatWise 配置

1. 启动 ChatWise
2. 访问设置
3. 选择工具部分
4. 点击 "+" 添加新工具
5. 使用以下参数配置：
   - Type: `stdio`
   - ID: `to-markdown`
   - Command: `mcp-server-to-markdown`
   - Args:
      ```
      CLOUDFLARE_API_TOKEN=your_api_token
      CLOUDFLARE_ACCOUNT_ID=your_account_id
      ```

## API 参考

### to-markdown 工具

将各种文件格式转换为 Markdown 描述。

**输入参数：**
- `filePaths`: Array<string> (必需) - 要处理的文件路径列表

**响应结构：**
```json
[
  {
    "filename": "example.pdf",
    "mimeType": "application/pdf",
    "description": "Generated Markdown description",
    "tokens": 123
  }
]
```

## 开发指南

### 入门

1. 克隆并设置环境：
```bash
git clone <repository-url>
cd mcp-server-to-markdown
cp .env.example .env
```

2. 配置 Cloudflare 凭证：
```plaintext
CLOUDFLARE_API_TOKEN=your_api_token
CLOUDFLARE_ACCOUNT_ID=your_account_id
```

3. 安装依赖并构建：
```bash
npm install
npm run build
```

### 项目结构

```
.
├── src/             # 源代码
├── dist/            # 编译输出
├── types.ts         # 类型定义
└── .env             # 环境配置
```

### 可用脚本

- `npm run build` - 构建 TypeScript 代码
- `npm run inspect` - 使用 MCP 检查器运行

## 使用示例

```typescript
const result = await toMarkdown({
  filePaths: [
    "/path/to/document.pdf",
    "/path/to/image.jpg"
  ]
});
```

## 许可证

MIT License

本项目由 [Frad LEE](https://twitter.com/FradSer) 维护
npm package: @iflow-mcp/mcp-server-ts
Description: 一个同时支持stdio,streamableHttp和sse的mcp框架
Author: caixintong
Latest version: 1.0.0

# 一个同时支持stdio，streamableHttpless和sse三种协议的MCP服务框架

## 项目说明
目前MCP服务在AI方向的业务使用频率很高，但随着业务的加深，发现存在以下痛点：
  1.不同平台对MCP服务协议要求不同，有支持streamableHttp，有仅支持sse的。相同功能重复开发，浪费时间成本
  2.有些研发人员并不了解MCP，现学现开发会让研发周期加长，时间成本耗费过多
为了解决不同平台不同要求，降低研发人员开发成本，本人提出一个框架，同时支持stdio，streamableHttpless和sse三种模式，实现一次开发实现三种模式

## 目录结构
- build: 编译之后的文件
- src
 -- router: 配置streamableHttp和sse协议的路由
   -- index.ts: 注册streamableHttp路由入口
   -- mcp.ts: streamableHttp的配置路径，具体为`process.env.MCP_BASE_PATH`的路径请求,如果没有配置，默认/mcp
   -- sse.ts: sse的配置路径，具体为`process.env.MCP_BASE_PATH`的路径请求,如果没有配置，默认/mcp
 -- tools: mcp的工具 
   -- index.ts: 注册工具
   -- mockFunc.ts: 模拟一个工具写法 - 这部分需要根据业务开发
 -- cli.ts: 命令行解析工具
 -- index.ts: 总入口
 -- server.ts: 创建Mcp服务
 -- sse.ts: 运行sse模式
 -- stdio.ts: 运行stdio模式
 -- streamableHttp.ts: 运行streamableHttp模式
- xingyun/bin : 是根据我们业务使用的部署工具开发的部署脚本 - 这部分需要根据实际部署平台更改
- build_xingyun.sh: 是根据我们业务使用的部署工具开发的部署脚本 - 这部分需要根据实际部署平台更改

## 启动服务

1.启动stdio: npm run start 是默认启动stdio

1.启动StreamableHttp: npm run start:http 是默认启动端口3001

2.更改端口启动StreamableHttp: npm run dev:http 或者 npm run start -- -t http -p 3001 
-t httt: 代表启动StreamableHttp
-p 3001: 代表启动端口3001

## 测试StreamableHttp方式
### 第一种方式 curl命令
1.cd demo && npm run dev:http // 这个会启动 http://localhost:3001/mcp 这个地址
2.终端curl命令
``` ts
curl -X POST http://localhost:3001/mcp \
-H "Content-Type: application/json" \
-H "Accept: application/json, text/event-stream" \
-d '{
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"name": "mockfunc",
"arguments": {"desc": "测试参数","desc1": "测试参数"
}
},
"id": 1
}'
```
### 第二种方式 使用inspector工具
1.cd demo && npm run dev:http // 先启动自己服务
2.npm run inspector // 启动inspector工具
3.在URL地址配上自己服务地址

## 测试SSE方式 
方式和测试StreamableHttp方式 相同，只不过启动是用 npm run start:sse

## 环境变量说明
## 内网使用配置

### 环境变量配置
```bash
# 监听特定内网IP（例如：192.168.1.100）
export MCP_HOST=192.168.1.100
export MCP_PORT=3001

# 使用内网域名（可选）
export MCP_DOMAIN=mcp-server.internal.com

# 修改基础路径（可选，默认是 /mcp）
export MCP_BASE_PATH=/api/mcp

```

### 端口配置优先级
1. 环境变量 `MCP_PORT`（最高优先级）
2. 命令行参数 `--port` 
3. 默认值：3001端口

### 访问地址优先级
1. 环境变量 `MCP_DOMAIN`（最高优先级）
2. 环境变量 `MCP_HOST`
3. 默认: localhost

### 内网访问方式
假设你的内网服务器IP是 `192.168.1.100`，端口是 `3001`：

**基础访问：**
```
http://192.168.1.100:3001/sales
```

**带域名的访问：**
```
http://mcp-server.internal.com/sales
```

**自定义路径：**
```
http://192.168.1.100:3001/api/mcp
```
### 额外说明
1.在 xingyun/bin/control.sh中，这段代码是启动streamableHttpless的，如果需要启动sse，需要改为 `npm run start:sse`
```
start(){
    npm run start:http
    sleep 3
    status
}
```

2.在package.json中 stop的语句是 `"stop": "pkill -f \"demo\" || true",`这个demo是要根据你自己启动服务的名字相同
npm package: @iflow-mcp/mcp-server-weibo
Description: Model Context Protocol服务器，用于抓取微博用户信息、动态和搜索等功能
Latest version: 1.0.3

# Weibo MCP Server (TypeScript Version)

This is a server based on the [Model Context Protocol](https://modelcontextprotocol.io) for scraping Weibo user information, feeds, and search functionality. This server can help retrieve detailed information about Weibo users, feed content, and perform user searches.

<a href="https://glama.ai/mcp/servers/@Selenium39/mcp-server-weibo">
  <img width="380" height="200" src="https://glama.ai/mcp/servers/@Selenium39/mcp-server-weibo/badge" alt="Weibo Server MCP server" />
</a>

## Installation

Install from source code:

```json
{
    "mcpServers": {
        "weibo": {
            "command": "npx",
            "args": [
                "--from",
                "git+https://github.com/Selenium39/mcp-server-weibo.git",
                "mcp-server-weibo"
            ]
        }
    }
}
```

Install from package manager:

```json
{
    "mcpServers": {
        "weibo": {
            "command": "npx",
            "args": ["mcp-server-weibo"],
        }
    }
}
```

## Components

### Tools

- `search_users(keyword, limit)`: 根据关键词搜索微博用户
- `get_profile(uid)`: 获取用户详细资料信息
- `get_feeds(uid, limit)`: 获取用户微博动态
- `get_hot_search(limit)`: 获取微博热搜榜
- `search_content(keyword, limit, page?)`: 根据关键词搜索微博内容

### Resources

None

### Prompts

None

## Requirements

- Node.js >= 18.0.0

## License

MIT License

## Disclaimer

This project is not affiliated with Weibo and is for learning and research purposes only.

## Other
mcp-server-weibo is indexed and certified by [MCP Review](https://mcpreview.com/mcp-servers/selenium39/mcp-server-weibo)
npm package: @iflow-mcp/mcp-shell
Description: Secure shell server for the Model Context Protocol. Integrates with Claude Desktop.
Author: High Dimensional Research
Latest version: 0.1.3

# Shell MCP Server

A Node.js implementation of the Model Context Protocol (MCP) that provides secure shell command execution capabilities. This server allows AI models to execute shell commands in a controlled environment with built-in security measures. Easily integrates with [Claude Desktop](https://claude.ai/download) for connecting Claude with your shell.

## Features

- MCP-compliant server implementation
- Secure command execution with blacklist protection
- Command existence validation
- Standard I/O based transport
- Error handling and graceful shutdown

## Installation

Run `npx mcp-shell`.

To add it to Claude Desktop, run `npx mcp-shell config`. Or add `npx -y mcp-shell` to your config manually.

Start (or restart) [Claude Desktop](https://claude.ai/download) and you should see the MCP tool listed on the landing page.

## Security Features

The server implements several security measures:

1. Command Blacklisting

   - Prevents execution of dangerous system commands
   - Blocks access to critical system modifications
   - Protects against file system destruction
   - Prevents privilege escalation

2. Command Validation
   - Verifies command existence before execution
   - Validates against the blacklist
   - Returns clear error messages for invalid commands

## Available Tools

The server provides one tool:

### run_command

Executes a shell command and returns its output.

**Input Schema:**

```json
{
  "type": "object",
  "properties": {
    "command": { "type": "string" }
  }
}
```

**Response:**

- Success: Command output as plain text
- Error: Error message as plain text

## Blacklisted Commands

The following command categories are blocked for security:

- File System Destruction Commands (rm, rmdir, del)
- Disk/Filesystem Commands (format, mkfs, dd)
- Permission/Ownership Commands (chmod, chown)
- Privilege Escalation Commands (sudo, su)
- Code Execution Commands (exec, eval)
- System Communication Commands (write, wall)
- System Control Commands (shutdown, reboot, init)

## Error Handling

The server includes comprehensive error handling:

- Command not found errors
- Blacklisted command errors
- Execution errors
- MCP protocol errors
- Graceful shutdown on SIGINT

## Implementation Details

The server is built using:

- Model Context Protocol SDK
- StdioServerTransport for communication
- execa for command execution
- command-exists for command validation

## Development

To modify the security settings, you can:

1. Edit the `BLACKLISTED_COMMANDS` set to adjust blocked commands
2. Modify the `validateCommand` function to add additional validation rules
3. Enhance the command parsing logic in the `CallToolRequestSchema` handler
npm package: @iflow-mcp/mcp-slop-adapter
Description: MCP to SLOP adapter
Author: Franci Penov
Latest version: 0.3.0

# MCP to SLOP Adapter

A lightweight adapter that connects [MCP](https://modelcontextprotocol.io/) (Model Context Protocol) clients like Claude Desktop with any [SLOP](https://github.com/agnt-gg/slop) (Simple Language Open Protocol) compatible server.

## What is MCP and SLOP?

- **MCP (Model Context Protocol)**: A proprietary protocol developed by Anthropic that enables AI models to access tools and resources. [Learn more about MCP](https://modelcontextprotocol.io/).
- **SLOP (Simple Language Open Protocol)**: A simple open-source REST-based pattern for AI APIs with 5 basic endpoints. [Learn more about SLOP](https://github.com/agnt-gg/slop) or join the [SLOP Discord community](https://discord.com/invite/nwXJMnHmXP).

## Features

This adapter bridges MCP and SLOP by:

- Converting MCP tool requests to SLOP API calls
- Exposing SLOP resources as MCP resources
- Providing MCP tools for SLOP-specific endpoints (chat, memory, pay)
- Handling error conversion between protocols

## Installation & Usage

### Using npx

You can run the adapter directly using npx:

```bash
npx @kortexa-ai/mcp-slop-adapter http://your-slop-server-url
```

### Global Installation

```bash
npm install -g @kortexa-ai/mcp-slop-adapter
mcp-slop-adapter http://your-slop-server-url
```

## Configuring Claude Desktop

To connect Claude Desktop with a SLOP server:

1. Make sure your SLOP server is running
2. Edit Claude Desktop's configuration file:
   - Windows: `%APPDATA%\Claude\claude_desktop_config.json`
   - macOS: `~/Library/Application Support/Claude/claude_desktop_config.json`
3. Add the following configuration:

```json
{
    "mcpServers": {
        "mcp-slop-adapter": {
            "command": "npx",
            "args": [
                "@kortexa-ai/mcp-slop-adapter",
                "http://your-slop-server-url"
            ]
        }
    }
}
```

Replace `http://your-slop-server-url` with the URL of your SLOP server.

## Debugging

You can use the [MCP Inspector](https://github.com/modelcontextprotocol/inspector) to connect to the adapter and inspect your SLOP server.

## Exposed MCP Capabilities

This adapter exposes:

- **Tools**: Native SLOP tools from `/tools` endpoint, plus `chat`, `memory-store`, `memory-get`, and `pay`
- **Resources**: All resources from the SLOP `/resources` endpoint

## License

MIT