This MCP server implementation provides a bridge to LinkedIn's platform, enabling AI assistants to perform various LinkedIn operations such as logging in, browsing feeds, searching profiles, viewing specific profiles, and interacting with posts. Developed by alinaqi, it uses Playwright for browser automation and implements secure session management with encrypted cookie storage. The server offers tools for both manual and automated LinkedIn interactions, making it particularly useful for AI applications requiring social media engagement, professional networking, or talent acquisition tasks. It focuses on rate limiting, error handling, and maintaining compliance with LinkedIn's terms of service, ensuring robust and responsible automation of LinkedIn activities.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-02.
Scan details: Circle-IR · 2026-09-02 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- browser-automation
- Source
- PulseMCP
- Repository
- github.com/alinaqi/mcp-linkedin-server
- Author type
- human
- Last scanned
- 2026-09-02
- Updated
- 2026-09-02
Use via MCP
Resolve LinkedIn from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.