LinkedIn MCP Server (AI version)
A powerful Model Context Protocol server that exposes verified LinkedIn capabilities as MCP tools, plus an account-research prompt — runnable over stdio (local) and Streamable HTTP (remote).
Built as the reference implementation for the course in
../Documentation/. Scope: LinkedIn-only (Tier A verified core + Tier D extended). SeePLAN.md.
Tools
| Tool | What it does | |---|---| | linkedin_get_company_profile | Company name, industry, size, HQ, specialities | | linkedin_get_company_posts | Recent company posts with engagement | | linkedin_get_company_insights | Headcount growth, hiring signals, people highlights | | linkedin_search_company_leaders | Leadership-level people at a company | | linkedin_get_person_profile | A person's profile | | linkedin_get_person_posts | A person's recent posts | | _Tier D (extended)_ | company/people/job search, contact info — added in Phase 4 |
Prompt: account_intel — scripts the tools into a full company brief.
Setup
uv sync --extra dev
cp .env.example .env # then fill in LI_AT + LI_JSESSIONIDRun
# stdio (default) — for local hosts / the Inspector
uv run linkedin-mcp
# Streamable HTTP — secured (Origin allowlist + bearer token), localhost-bound
uv run linkedin-mcp --transport httpVerify in the MCP Inspector
npx @modelcontextprotocol/inspector uv run linkedin-mcpList tools, then call linkedin_get_company_profile with {"linkedin_url_or_slug": "microsoft"}.
Plug into Claude Desktop (stdio)
{
"mcpServers": {
"linkedin": {
"command": "uv",
"args": ["run", "--directory", "C:/Users/WELCOME/Desktop/Linked-MCP/ai-version", "linkedin-mcp"]
}
}
}Notes & safety
- Unofficial
linkedin-api: cookie auth (LI_AT+LI_JSESSIONID) is the
supported path; password login often hits a challenge. Cookies expire → tools return a clear auth error.
- Rate limits are real; post counts are clamped. Heavy use can flag the account.
- stdio writes JSON-RPC on stdout — all logs go to stderr only.
- HTTP proxies your LinkedIn identity: set
MCP_AUTH_TOKENand keep the bind on
localhost before sharing.
