What is the default behavior for publishing?
All publishing actions default to preview mode (`dry_run: true`). Nothing goes live without explicitly setting `dry_run: false` after reviewing the preview.
@timkulbaev
基本信息
MCP server for LinkedIn publishing from AI coding assistants. Dry run by default, SKILL.md for safe workflows, 28 unit tests. MIT licensed.
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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。
Mcp Linkedin is an MCP server that wraps the Unipile API to let AI assistants publish, comment, and react on LinkedIn. It is built for AI assistants like Claude Code and Claude Desktop, or any MCP-compatible client.
Install Node.js 18+, clone the repository, run npm install, then configure your MCP client (e.g., Claude Code or Claude Desktop) with the server command and environment variables UNIPILE_API_KEY and UNIPILE_DSN. The server exposes three tools: linkedin_publish, linkedin_comment, and linkedin_react. All publishing actions default to preview mode (dry_run: true) and require explicit confirmation to go live.
All publishing actions default to preview mode (`dry_run: true`). Nothing goes live without explicitly setting `dry_run: false` after reviewing the preview.
You need **Node.js 18+** and a **Unipile account**. Unipile handles LinkedIn OAuth – you do not need to manage LinkedIn tokens directly.
Set `UNIPILE_API_KEY` and `UNIPILE_DSN` in the MCP client configuration file (e.g., `~/.claude/mcp.json` for Claude Code). No `.env` file is used.
Yes. You can pass local file paths or URLs for `jpg`, `png`, `gif`, `webp`, and `mp4` files. Files are validated and temporarily downloaded.
Mcp Linkedin uses MCP stdio transport (JSON-RPC over standard input/output). No other transports (HTTP, WebSocket) are mentioned.

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