mcp-linkedin

This MCP server provides programmatic access to LinkedIn data through an unofficial LinkedIn API. It exposes tools to fetch feed posts and search for jobs via the LinkedIn Feeds and Job APIs, enabling LLM-driven workflows to extract insights, summarize activity, and identify opportunities from LinkedIn content. The recommended starting tools are get_feed_posts to retrieve recent feed entries and search_jobs to locate relevant job postings. Use these tools in your prompt-based interactions to pull structured results that can be fed into downstream reasoning or planning steps. The server relies on the LinkedIn API wrapper used by the project and may be subject to API rate limits or occasional changes in API behavior; handle responses accordingly and respect LinkedIn’s terms of service.

Prerequisites:

• Python 3.8+ and access to uv/uvx runtime as described by the project
• Internet access to install dependencies from GitHub
• Optional: a LinkedIn account for authenticating via the unofficial API

Installation steps:

1. Install the MCP LinkedIn server via Smithery (recommended): npx -y @smithery/cli install mcp-linkedin --client claude

2. Manual installation (uvx-based runtime):

   • Ensure you have uvx installed and available in your PATH.
   • Start from the Git source: npm run ??? # (If applicable in your environment) or use: uvx --from git+https://github.com/adhikasp/mcp-linkedin mcp-linkedin
   • Set required environment variables (see config): export LINKEDIN_EMAIL="your_linkedin_email" export LINKEDIN_PASSWORD="your_linkedin_password"

3. Verify installation by starting the MCP server as configured (see mcp_config).

4. Consult the repository README for any additional runtime notes or updates.

Notes and tips:

• This server uses an unofficial LinkedIn API wrapper; use at your own risk and comply with LinkedIn's terms of service.
• Environment variables LINKEDIN_EMAIL and LINKEDIN_PASSWORD are required for authenticated access.
• If you encounter authentication or API changes, check the upstream wrapper repository and adjust environment or args accordingly.
• The configuration exports the mcp-linkedin module under the 'linkedin' server name; you can scale or duplicate entries if you manage multiple LinkedIn profiles or contexts.