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Social MCP: Multi-Agent Social Media Automation

@kitadmin01

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基本情報

カテゴリ

AI とエージェント

トランスポート

stdio

作者

kitadmin01

Social MCP: Multi-Agent Social Media Automation について

Socail MCP Server

Social MCP: Multi-Agent Social Media Automation の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

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

Social MCP: Multi-Agent Social Media Automation のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

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

よくある質問

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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