open-index/open-npm huggingface dataset:
npm package: @iflow-mcp/example-mcp-server
Description: A Model Context Protocol (MCP) server implementation in Node.js
Author: Danny Avila
Latest version: 1.0.0

# Simple Streamable HTTP MCP Server

A clean implementation of an MCP server using the Streamable HTTP transport, following the official MCP patterns.

## Features

- **Streamable HTTP Transport**: Supports both JSON responses and Server-Sent Events (SSE)
- **Session Management**: Proper session handling with unique session IDs
- **Progress Notifications**: Long-running tools send progress updates
- **Multiple Tools**:
  - `hello_world`: Simple greeting tool
  - `get_server_info`: Returns server information
  - `long_running_test`: Configurable duration test with progress (default: 30s)
  - `slow_test`: 10-minute test with progress updates

## Architecture

This server follows the MCP team's recommended patterns:

1. **Session-based Architecture**: Each client gets a unique session ID
2. **Transport Reuse**: Transports are stored and reused for subsequent requests
3. **Proper Initialization**: New sessions are created only on initialization requests
4. **Clean Shutdown**: All transports are properly closed on server shutdown

## Running the Server

```bash
# Install dependencies
npm ci

# Run the server (default port: 3001, DEBUG logging enabled by default)
npm run start

# Run without debug logging, or edit `.env` to set DEBUG=false
DEBUG=false npm run start

# Run in development mode (auto-reload)
npm run dev
```

## Testing

Use the provided test script to verify the server is working correctly:

```bash
npm run test:http
```

This will test:
- Session initialization
- Tool listing and calling
- Session ID management
- SSE streaming
- Session termination

## Progress Notifications

The `long_running_test` and `slow_test` tools demonstrate progress notifications:

```javascript
// Example tool call with progress
{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "name": "long_running_test",
    "arguments": {
      "duration": 60,
      "steps": 12,
      "message": "Testing progress notifications"
    },
    "_meta": {
      "progressToken": "unique-progress-token"
    }
  },
  "id": 1
}
```

The server will send progress notifications:
```javascript
{
  "method": "notifications/progress",
  "params": {
    "progress": 1,
    "total": 12,
    "progressToken": "unique-progress-token"
  }
}
```

## Key Differences from Basic Examples

1. **Proper Session Management**: Sessions are created per client, not per request
2. **Transport Lifecycle**: Transports persist across requests within a session
3. **Error Handling**: Comprehensive error handling for all edge cases
4. **Progress Support**: Long-running operations can report progress
5. **Clean Architecture**: Clear separation between server creation and request handling

## Environment Variables

- `PORT`: Server port (default: 3001)
- `DEBUG`: Enable debug logging (`true` by default)

## Endpoints

- `POST /mcp`: Handle JSON-RPC requests
- `GET /mcp`: Handle SSE streaming
- `DELETE /mcp`: Terminate sessions
- `GET /health`: Health check endpoint
npm package: @iflow-mcp/excalidraw-mcp
Description: MCP server for Excalidraw
Latest version: 0.1.1

# Excalidraw MCP Server

This is a Model Context Protocol (MCP) server for Excalidraw, providing API functionality for operating on Excalidraw drawings.

## Features

- Create, read, update, and delete Excalidraw drawings
- Export drawings to SVG, PNG, and JSON formats
- Simple file-based storage system

## Installation

```bash
# Clone the repository
git clone https://github.com/yourusername/excalidraw-mcp.git
cd excalidraw-mcp

# Install dependencies
npm install

# Build the project
npm run build
```

## Usage

### Starting the Server

```bash
npm start
```

### API Endpoints

The server provides the following tools:

#### Drawing Management

- `create_drawing`: Create a new Excalidraw drawing
- `get_drawing`: Get an Excalidraw drawing by ID
- `update_drawing`: Update an Excalidraw drawing by ID
- `delete_drawing`: Delete an Excalidraw drawing by ID
- `list_drawings`: List all Excalidraw drawings

#### Export Operations

- `export_to_svg`: Export an Excalidraw drawing to SVG
- `export_to_png`: Export an Excalidraw drawing to PNG
- `export_to_json`: Export an Excalidraw drawing to JSON

## Development

### Project Structure

```
excalidraw-mcp/
├── src/
│   ├── common/
│   │   └── errors.ts
│   └── operations/
│       ├── drawings.ts
│       └── export.ts
├── index.ts
├── package.json
├── tsconfig.json
└── README.md
```

### Building

```bash
npm run build
```

### Running in Development Mode

```bash
npm run dev
```

## License

MIT
npm package: @iflow-mcp/eyaltoledano-instagram-dm-mcp
Description: Instagram Direct Messages MCP server for Claude Desktop
Latest version: 1.3.6

# Instagram DM MCP Server

An MCP (Model-Consumer Protocol) server for Instagram direct messaging functionality, built with `fastmcp` and `instagrapi`. This server enables AI assistants to read and send Instagram direct messages.

**Current Version: 1.3.5**

## Features

- Read recent direct messages from your Instagram inbox with comprehensive thread information
- Send direct messages to Instagram users
- Simple greeting resource (example functionality)
- Health check endpoint with status information
- Proper logging to stderr to avoid JSON parsing issues
- Support for various authentication methods, including environment variables

## Installation

### As an npm package (recommended)

1. Install the package globally:

```bash
npm install -g instagram-dm-mcp
```

2. Run the setup script to install Python dependencies:

```bash
instagram-dm-mcp-setup
```

3. Register the server with Claude Desktop and configure credentials:

```bash
instagram-dm-mcp install
```

You will be prompted to paste in your Instagram cookies information. If you arne't sure how to get this, log into Instagram on Chrome, right-click on the page, and select "Inspect". Go to the "Application" tab, then click on "Cookies" in the left sidebar. You should see a list of cookies. Copy the values for `sessionid`, `csrftoken`, and `ds_user_id`.

The `install` command will automatically register the Instagram DM MCP server with Claude Desktop and add it to your Claude Desktop configuration file. The command will configure the server to use the `npx` approach, which makes it easier to maintain. You can also copy-paste the same setup to Claude or any other MCP client.

You can provide Instagram credentials in several ways:

- Using command-line arguments:
  ```bash
  instagram-dm-mcp install --session-id YOUR_SESSION_ID --csrf-token YOUR_CSRF_TOKEN --ds-user-id YOUR_DS_USER_ID
  ```

- Using a credentials file:
  ```bash
  instagram-dm-mcp install --from-file /path/to/instagram_cookies.json
  ```

- Using environment variables (INSTAGRAM_SESSION_ID, INSTAGRAM_CSRF_TOKEN, and INSTAGRAM_DS_USER_ID)

The installer will add these credentials as environment variables in the Claude Desktop configuration file, creating a configuration like this:

```json
"mcpServers": {
  // other servers...
  "InstagramDM": {
    "command": "npx",
    "args": [
      "-y",
      "instagram-dm-mcp",
      "start"
    ],
    "env": {
      "INSTAGRAM_SESSION_ID": "your-session-id",
      "INSTAGRAM_CSRF_TOKEN": "your-csrf-token",
      "INSTAGRAM_DS_USER_ID": "your-ds-user-id"
    }
  }
}
```
npm package: @iflow-mcp/eyevinnosc_mcp-server
Description: MCP server for using the Eyevinn Open Source Cloud API
Author: Eyevinn Technology AB
Latest version: 1.2.0

# Eyevinn Open Source Cloud MCP Server

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

This MCP server provides MCP tools for [Eyevinn Open Source Cloud](www.osaas.io) that requires local computer access, for example to upload a file to a storage bucket in OSC. MCP tools for architecting and building solutions with OSC is provided by the remote MCP endpoint that can be accessed using the [OSC remote MCP client](https://www.npmjs.com/package/@osaas/client-mcp).

<a href="https://glama.ai/mcp/servers/ku9s6ow21e"><img width="380" height="200" src="https://glama.ai/mcp/servers/ku9s6ow21e/badge" alt="Eyevinn Open Source Cloud Server MCP server" /></a>

### Features provided by the local MCP server

- Create a MinIO storage bucket in OSC.
- Upload a file to a MinIO storage bucket in OSC.
- List files on a MinIo storage bucket in OSC.

## Setup

### Installing via Smithery

To install Eyevinn Open Source Cloud MCP Server for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@osaas/mcp-server):

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

### Personal Access Token

- If you have not already done so, sign up for an [Eyevinn OSC account](https://app.osaas.io).
- In the Eyevinn OSC web console go to [API settings](https://app.osaas.io/dashboard/settings/api) (in Settings > API settings)
- Copy the Personal Access Token

### Usage with Claude Desktop

To use this with Claude Desktop, add the following to your `claude_desktop_config.json`:

```json
{
  "mcpServers": {
    "local-mcp-osc": {
      "command": "npx",
      "args": ["-y", "@osaas/mcp-server"],
      "env": {
        "OSC_ACCESS_TOKEN": "<YOUR_TOKEN>"
      }
    },
    "remote-mcp-osc": {
      "command": "npx",
      "args": ["-y", "@osaas/client-mcp"],
      "env": {
        "OSC_ACCESS_TOKEN": "<YOUR_TOKEN>"
      }
    }
  }
}
```

## Development

```
npx @modelcontextprotocol/inspector \
  -e OSC_ACCESS_TOKEN=<osc-access-token> \
  npx tsx src/index.ts
```

## 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/f-inc-containerinc-mcp
Description: MCP Server for Container Inc.
Author: Harry Bairstow
Latest version: 1.1.0

# @container-inc/mcp

MCP Server for deploying to [Container Inc.](https://container.inc)

> [!TIP]
> For now deployments are ephemneral and free. The platform is update coming soon to support more.

## Usage

```jsonc
// .cursor/mcp.json
{
  "mcpServers": {
    "@container-inc/mcp": {
      "command": "npx",
      "args": ["@container-inc/mcp"]
    }
  }
}
```

1. Place the above in a `.cursor/mcp.json` (or your editor's equivalent) file in your home directory.
2. Check the editor's settings to ensure it is enabled.
3. Just ask to deploy to Container Inc.

## Notes
* You'll be asked to login with GitHub this is so that:
  1. We can create a repository if needed
  2. Publish the docker image to ghcr.io
  3. Pull the code in the builder
* Ensure your project has a `Dockerfile` so it can be built
npm package: @iflow-mcp/factruesolin-api-test-mcp
Description: - 接口测试工具 - 生成接口测试计划，批量执行测试，评估测试结果，导出接口测试结果。
Author: Actrue
Latest version: 1.0.0

# api-test-mcp

- 接口测试工具
- 生成接口测试计划，批量执行测试，评估测试结果，导出接口测试结果。

### api-test-mcp核心功能

1. 创建测试计划
2. 批量执行测试任务
3. 自动评估接口测试结果
4. 可导出数据

## 更新信息

### 25 7月28日

去掉sqlite数据库，使用本地json存储数据，轻量化项目

### 25 6月 10日

ORM从Prisma迁移至drizzle，降低项目资源占用，提升项目性能。

接口从sse切换至streamableHttp

## 快速开始

1. 本地部署部署

```bash
git clone https://github.com/Actrue/api-test-mcp.git  ##复制源码
cd api-test-mcp
docker build -t api-test-mcp .   
docker run -p 3000:3000 -v $(pwd)/data:/usr/src/app/data api-test-mcp  
```

接入使用（cherry studio 为例）

添加服务器->类型选择streamableHttp->url填写 http://localhost:3000/mcp ->点击保存

## 源码构建

### 环境要求

node>=20

pnpm

### 构建过程

```bash
git clone https://github.com/Actrue/api-test-mcp.git  ##复制源码
cd api-test-mcp
pnpm run go  ##启动命令 此命令将在端口3000启动sse服务器
```

## 使用须知

推荐配合以下提示词使用

```txt
你是一个接口测试员，你将会得到接口的api文档，然后根据接口文档制作接口测试计划表以及计划任务，
你不仅需要检验api接口功能是否正常，也需要测试接口在接受错误数据时是否能正确处理，
若用户忘记提供测试url，请提醒用户
回复格式
[规划测试计划]
调用工具，制作接口测试计划
[调用插件按照计划进行测试]
格式：测试编号，测试目标，测试结果。
[根据结果生成总结和建议]
调用工具，把总结和建议写入数据表汇总
[测试结果，并导出为excel]
调用工具，获取测试结果
[测试结果总结]
总结整个测试情况
要求：
url必须是完整链接
```

## 支持平台

- Mac
- Windows
- Linux

## 技术栈

- [fastmcp-ts](https://github.com/punkpeye/fastmcp)
- [drizzle ORM](https://orm.drizzle.team/)
- [xlsx](https://www.npmjs.com/package/xlsx)