LinkedIn MCP Server

A ToS-compliant Model Context Protocol server for LinkedIn, using only the official LinkedIn API.

Unlike other LinkedIn MCP servers that rely on scraping (which violates LinkedIn's User Agreement and risks account bans), this server uses LinkedIn's official Consumer API with proper OAuth 2.0 authentication.

Quick start

Fastest way to get started: Copy the setup prompt from SETUP_PROMPT.md and paste it into Claude Code. Claude will clone the repo, install it, configure your credentials, and log you in — you just click "allow" on each step.

Need to do it manually instead? Follow the step-by-step Setup Guide or continue reading below.

Related MCP server: Linkd MCP Server

Posting pipeline

A built-in web dashboard for managing your LinkedIn content from draft to publish. Write posts as markdown files, move them through a kanban board, schedule them for specific dates and times, and let Claude post them automatically when they're due.

Draft  →  Approved  →  Scheduled  →  Completed

Quick setup: Copy the prompt from PIPELINE_SETUP_PROMPT.md into Claude Code — it handles the install, auto-start, and scheduled posting for you.

See pipeline/README.md for full manual setup, configuration, and schedule options.

MCP tools

All write operations require explicit user approval before executing, keeping the integration compliant with LinkedIn's API Terms of Use (no automated posting).

Security and compliance

• Human-in-the-loop — Every write tool uses a two-step confirm pattern: preview first (default), then publish only after explicit approval

• Approval stamp — Published posts include a configurable stamp showing the content was human-approved

• Audit logging — Every preview, publish, and delete is recorded in a local NDJSON audit log

• Token encryption — Access tokens are encrypted at rest using Fernet with a machine-derived key

• Token refresh — Silently refreshes expired tokens when a refresh token is available, avoiding unnecessary re-authentication

• Health check — Diagnose issues with a single tool call: checks token validity, API connectivity, credential configuration, and audit log status

• Character count — Post previews show character count against LinkedIn's 3,000-character limit, preventing over-length submissions

• Undo/recall — Quick-delete the most recently published post with a single tool call, without needing to look up the URN

• MCP Inspector compatible — All tool schemas include additionalProperties: false and the server declares its version for strict MCP spec compliance

• Scope verification — Checks that the stored token has all required scopes before attempting API actions, failing fast with a clear message

• Configurable encryption key — Optionally provide your own encryption key via environment variable for token portability between machines

• Configurable callback port — Change the OAuth callback port from the default 8585 via environment variable

• Type checked — Full mypy strict mode with no errors across all modules

• CI pipeline — GitHub Actions runs tests and type checking on Python 3.10, 3.11, and 3.12 for every push and PR

• Post history — Local record of all published posts with URNs, timestamps, content, and type filtering

• Link preview — Fetch Open Graph metadata from URLs before sharing to check the link card

• First-run setup — Interactive setup assistant that checks configuration and walks through missing steps

• Poll creation — Create LinkedIn polls with 2-4 options and configurable duration (1, 3, 7, or 14 days)

• Document posts — Upload and share PDFs, slide decks, and other documents as native LinkedIn document posts

• Video posts — Upload and publish video content (MP4, MOV, AVI, MKV, WEBM) up to 200 MB via LinkedIn's video upload API

• Minimal scope — Only requests the API scopes needed (openid, profile, email, w_member_social)

Testing

The project includes a comprehensive test suite with 229 unit tests (96% coverage) covering all modules:

pip install -e ".[dev]"
pytest tests/ -v

Setup

• Setup Prompt — paste into Claude Code and let it do everything for you

• Manual Setup Guide — step-by-step if you prefer to do it yourself

Requirements

• Claude Code — this is an MCP server designed for use with Claude Code (requires an Anthropic subscription: Pro, Max, Team, or Enterprise). It also works with Claude Desktop for Cowork integration. See the deployment notes below for other surfaces.

• Python 3.10+

• A LinkedIn Developer App with "Sign in with LinkedIn" and "Share on LinkedIn" enabled

Install

git clone https://github.com/anubisalpha/linkedin-mcp.git
cd linkedin-mcp
pip install -e .

This installs the linkedin-mcp CLI command. You can also run the server as a module:

linkedin-mcp          # CLI entry point
python -m linkedin_mcp  # module entry point (equivalent)

Environment variables

How it works

1. Authentication — Standard OAuth 2.0 Authorization Code Flow via your browser. Credentials never pass through the MCP server.

2. Token storage — Encrypted at rest using Fernet. Tokens expire after 60 days; refresh tokens are used automatically when available.

3. Human-in-the-loop — Every write action requires explicit user approval before the API call is made.

4. Minimal scope — Only openid, profile, email, and w_member_social.

ToS compliance

• Uses only the official LinkedIn API — no scraping, crawling, or browser automation

• No automated posting — every publish requires human approval

• No data storage beyond tokens — profile data is fetched on demand, not cached

Rate limits

• 150 posts per day per member

• 100,000 API calls per day per application

Deployment

This server uses stdio transport, which means it runs locally alongside your MCP client.

.mcp.json example

{
  "mcpServers": {
    "linkedin": {
      "command": "linkedin-mcp",
      "env": {
        "LINKEDIN_CLIENT_ID": "your_client_id",
        "LINKEDIN_CLIENT_SECRET": "your_client_secret"
      }
    }
  }
}

Use linkedin-mcp (the CLI entry point) or python -m linkedin_mcp as the command. Use literal credential values, not ${VAR} references.

Architecture

See docs/architecture.md for implementation details and design decisions.

Support

If you find this useful, consider buying me a coffee. No pressure at all — but if you'd like to support the project, it's genuinely appreciated.

License

MIT