This MCP server for LinkedIn, developed by Hritik Raj, enables AI agents to interact with LinkedIn's platform for job applications and feed searching. Built using Python and leveraging the unofficial LinkedIn API, it provides tools for profile retrieval, advanced job searching, feed post retrieval, and resume analysis. The implementation focuses on simplifying LinkedIn interactions, offering functionality to extract key profile information, perform customizable job searches, and parse resumes in PDF format. It's particularly useful for applications requiring automated LinkedIn engagement, enabling use cases such as job matching, content curation, and candidate screening without directly dealing with LinkedIn's API complexities.
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 2026-09-19.
Scan details: Circle-IR · 2026-09-19 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- social-media
- Source
- PulseMCP
- Repository
- github.com/hritik003/linkedin-mcp
- Author type
- human
- Last scanned
- 2026-09-19
- Updated
- 2026-09-19
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.