linkedin-mcp

MCP server for editing your own LinkedIn profile from Claude Code — with a hard propose-then-approve split: the model can draft a change and show you the diff, but only one tool can ever write, and it acts only on a proposal you have seen.

Read this before you install

1. You bring your own LinkedIn app. There is no shared or hosted service here. You create your own app at linkedin.com/developers/apps, and your own client ID and secret go in a file on your own machine (~/.config/linkedin-mcp/.env, permissions 600). The server itself makes no outbound call to anything but LinkedIn's own API — there is no telemetry and no third party. Note that it is still an MCP server: profile data and diffs it returns go to whichever agent you connect, so if that agent is cloud-backed, your profile content reaches that provider like any other chat content. See PRIVACY.md.

2. Writing to your profile needs LinkedIn partner approval — which you must apply for yourself. LinkedIn's Profile Edit API is restricted to LinkedIn-approved partner developers (w_compliance is "a private permission and access is granted to select developers" — see docs/api-notes.md). Approval is granted per developer app, so your app needs your approval; nobody else's carries over. Until it lands, apply_proposal returns an invalid-scope error. That is expected, not a defect — and it may never land, since the permission goes to "select developers".

Everything else works today without partner approval: OAuth sign-in, reading your profile, drafting edits, and reviewing diffs. Only the final write is gated.

Related MCP server: kaushik-linkedin-mcp

How it works

Proposals persist under ~/.config/linkedin-mcp/proposals/ so an approval can happen in a later session. Tokens and client credentials live in ~/.config/linkedin-mcp/.env with permissions 600 — entered by you, never by an agent, never committed (see .env.example).

Install

Requires Python ≥ 3.11. Clone the repo, then register it as an MCP server in your agent — add this to your client's MCP config (for Claude Code that is ~/.claude.json, or run claude mcp add linkedin -- bash /path/to/linkedin-mcp/run.sh):

{
  "mcpServers": {
    "linkedin": {
      "command": "bash",
      "args": ["/path/to/linkedin-mcp/run.sh"]
    }
  }
}

Replace /path/to/linkedin-mcp with the absolute path to your clone. run.sh creates .venv/ and installs pinned dependencies on first launch (stamp-gated; all bootstrap output goes to stderr, keeping the MCP stdio channel clean).

Then follow docs/SETUP.md to create your LinkedIn app and sign in — the server has no credentials until you do.

Setup

Follow docs/SETUP.md — it walks through creating your own LinkedIn Developer app, registering the redirect URL, filling ~/.config/linkedin-mcp/.env with your own client ID and secret, running auth_start, and applying for the partner program.

Development

bash run.sh --help                                # bootstraps the venv (runtime deps only)
.venv/bin/pip install -r requirements-dev.txt     # adds pytest + coverage tooling
.venv/bin/python -m pytest                        # offline — every test runs against a mock transport

The test suite includes a granted-write fixture: a mock LinkedIn where every documented write endpoint happily returns 200. Tests assert that propose_edit leaves zero non-GET requests in the recorded log even when writes would succeed, and (positive control) that apply_proposal does record the documented write call in the same fixture. --live-probe is a diagnostic flag (single real request, discriminates "endpoint right but scope not granted" from "endpoint wrong"); it never runs in tests or CI and requires LINKEDIN_MCP_LIVE_PROBE=1.

The API surface is pinned to dated verbatim excerpts from the official docs in docs/api-notes.md.

License

MIT — see LICENSE.