open-index/open-npm huggingface dataset:
npm package: @iflow-mcp/linkedin-mcp-server
Description: MCP server for interacting with Linkedin Marketing API
Latest version: 0.1.2

# Linkedin MCP Server

MCP server for interacting with [Linkedin Community Management API](https://learn.microsoft.com/en-us/linkedin/marketing/community-management/community-management-overview?view=li-lms-2025-03).

This MCP server:

- Can be hosted locally or remotely : uses [HTTP+SSE transport](https://spec.modelcontextprotocol.io/specification/2024-11-05/basic/transports/#http-with-sse) defined in MCP
- Implements the [Draft Third-Party Authorization Flow from MCP specs](https://spec.modelcontextprotocol.io/specification/draft/basic/authorization/#29-third-party-authorization-flow) to delegate authorization to LinkedIn's OAuth authorization server

> ⚠️ Disclaimer: The Third-Party Authorization Flow proposal status is currently in draft. The only MCP client, to my knowledge, that currently implements this specification of the protocol is the [MCP Inspector](https://github.com/modelcontextprotocol/inspector)

## Features

### Tools

- `user-info` - Get current logged in user infos (name, headline and profile picture)
- `create-post` - Create a new post on LinkedIn

## Installation

Follow those instructions to run Linkedin MCP server on your host. You'll need to provide your own Linkedin client.

### Requirements

- Node 22 (`lts/jod`)
- pnpm 10
- a Linkedin client with `Community Management API` product installed and `http://localhost:3001/callback` added to the authorized redirect URLs

### Instructions

- Install dependencies:

```bash
pnpm install
```

- Create env file and populate with your Linkedin client credentials and a random string secret value for `JWT_SECRET`:

```bash
cp .env.template .env && vi .env
```

- Run the server:

```bash
pnpm run dev
```

- Configure your favorite MCP client to use this new server:

```json
{
  "mcpServers": {
    "linkedin": {
      "url": "http://localhost:3001/sse"
    }
  }
}
```

### Debugging

Start the [MCP Inspector](https://github.com/modelcontextprotocol/inspector) to debug this server, which is available as a package script:

```bash
pnpm run inspector
```

Access the inspector in your browser at `http://localhost:5173`

## Acknowledgment

- [Den Delimarsky](https://www.linkedin.com/in/dendeli/) that bravely gave a first shot at this new authorization flow with Microsoft Entra ID and detailed his results in his blog post: https://den.dev/blog/auth-modelcontextprotocol-entra-id/
- [Matt Pocock](https://www.linkedin.com/in/mapocock/) and his always welcome neat TS tricks specifically in the context of writting your own MCP server on AI Hero: https://www.aihero.dev/publish-your-mcp-server-to-npm
npm package: @iflow-mcp/lioensky-siliconflow-flux-mcp-server
Description: A Model Context Protocol server with OhMyGPT Flux that generates images.
Author: Exa Labs
Latest version: 0.1.0

# SiliconFlow Flux MCP 服务器

这是一个基于Model Context Protocol (MCP)的服务器，允许AI通过MCP协议使用SiliconFlow的Flux模型进行图像生成。

## 功能特点

- 允许AI助手通过MCP协议调用SiliconFlow的Flux模型生成高质量图像
- 支持多种图像分辨率：1024x1024, 960x1280, 768x1024, 720x1440, 720x1280
- 可自定义生成参数，如随机种子等
- 缓存最近的图像生成结果

## 系统要求

- Node.js v18.0.0 或更高版本

您可以通过以下命令验证Node.js安装：

```bash
node --version  # 应显示v18.0.0或更高版本
```

## 安装步骤

1. 克隆仓库：

```bash
git clone https://github.com/lioensky/siliconflow-flux-mcp-server.git
```

2. 安装依赖：

```bash
npm install
```

3. 构建项目：

```bash
npm run build
```

## 配置说明

### API密钥配置

在使用前，您需要：

1. 在项目根目录创建或编辑`.env`文件
2. 通过https://cloud.siliconflow.cn/i/HxM1olJu 来获取14元额度密钥
3. 添加您的SiliconFlow API密钥：

```
SILICONFLOW_API_KEY=您的API密钥
```

> **注意**：您需要自备SiliconFlow的API密钥才能使用此服务。

### MCP服务器配置

在您的MCP配置文件中添加以下内容：

```json
{
  "mcpServers": {
    "siliconflow-flux-mcp": {
      "command": "node",
      "args": ["路径/到/siliconflow-flux-mcp-server/build/index.js"],
      "env": {
        "SILICONFLOW_API_KEY": "您的API密钥"
      }
    }
  }
}
```

## 使用方法

配置完成后，AI助手可以通过MCP协议调用此服务生成图像。服务提供了`generate_image`工具，接受以下参数：

- `prompt`：图像生成提示词（建议使用英文以获得最佳效果）
- `resolution`：图像分辨率，支持多种标准尺寸
- `seed`（可选）：随机种子，用于生成可重复的结果

## 开发者工具

您可以使用MCP Inspector工具来测试服务器：

```bash
npm run inspector
```

## 许可证

请参阅项目仓库中的许可证文件。