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Social MCP: Multi-Agent Social Media Automation

@kitadmin01

代码仓库

基本信息

分类

AI 与智能体

传输方式

stdio

作者

kitadmin01

关于 Social MCP: Multi-Agent Social Media Automation

Socail MCP Server

Social MCP: Multi-Agent Social Media Automation 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "social_mcp": {
      "command": "python3",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

Social MCP: Multi-Agent Social Media Automation 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Social MCP: Multi-Agent Social Media Automation?

Social MCP is a multi‑agent system that automates content extraction, tweet generation, posting, and engagement on platforms like Twitter and Bluesky. It uses LLMs for content generation, Playwright for browser automation, and platform APIs for integration.

How to use Social MCP: Multi-Agent Social Media Automation?

Clone the repository, create a Python virtual environment, install dependencies (including Playwright), and configure a .env file with Twitter credentials, Playwright session directory, and Google Sheets API / OAuth settings. Start the MCP server from /social_mcp with python mcp_server/server.py, then run the MCP client with python mcp_client/client.py.

Key features of Social MCP: Multi-Agent Social Media Automation

  • Persistent Twitter session management with automatic login detection
  • Tweet posting with retry logic and navigation recovery
  • LLM‑powered tweet generation and content scheduling
  • Hashtag‑based content discovery and engagement automation
  • Robust browser automation with page state verification
  • Google Sheets integration and shared retry / secrets utilities

Use cases of Social MCP: Multi-Agent Social Media Automation

  • Automate content extraction, LLM‑driven tweet generation, and multi‑platform posting
  • Schedule and publish content across Twitter and Bluesky
  • Perform hashtag‑based search, liking, and general social engagement
  • Orchestrate multi‑agent workflows that coordinate content creation and publishing

常见问题

1

What are the runtime dependencies?

Python 3, Playwright (installed via `playwright install`), and all packages in `requirements.txt`. A `.env` file with Twitter credentials and a Playwright session directory is required.

2

How do I configure authentication?

Store Twitter username/password, Playwright session directory, and any other secrets in the `.env` file. For Google Sheets and Bluesky, set up OAuth credentials separately.

3

Where is browser session data stored?

Persistent browser session data is stored in the directory specified by `PLAYWRIGHT_SESSION_DIR` in the `.env` file (default `./playwright_session`).

4

Can Social MCP run in headless mode?

Yes. Set `HEADLESS=true` in the `.env` file to enable headless browser operation.

5

Which social media platforms are supported?

Twitter (via Playwright browser automation) and Bluesky (via API integration).

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