Lets your agent read LinkedIn profiles and create posts.
Available today. Use it from your connected AI after setup.
Needs your own linkedin account. You sign in to it and approve access when you connect.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use linkedin
About this server
LinkedIn API as MCP tools to retrieve profile data and publish content. Powered by HAPI MCP.
Install linkedin
The server’s own address, for the clients that take one directly. Or connect ahel onceand every client you use reads it from one address, with the account kept on ahel rather than in each client’s config.
Claude Code
claude mcp add --transport http --scope user linkedin 'https://linkedin.run.mcp.com.ai/mcp'Run it once in your project, then open /mcp to approve any sign-in the server asks for.
Claude Desktop
https://linkedin.run.mcp.com.ai/mcpAdd a custom connector in Settings, paste this address, and approve the sign-in.
Cursor
cursor://anysphere.cursor-deeplink/mcp/install?name=linkedin&config=eyJ1cmwiOiJodHRwczovL2xpbmtlZGluLnJ1bi5tY3AuY29tLmFpL21jcCJ9Open the link and Cursor adds the server at that address.
ChatGPT
https://linkedin.run.mcp.com.ai/mcpIn Settings, enable Developer mode, create an MCP app, and paste this address. Your plan and workspace must allow custom apps.
Codex
codex mcp add linkedin --url 'https://linkedin.run.mcp.com.ai/mcp'Run it once, then sign in with codex mcp login linkedin if the server asks for an account.
From the project's README
As published by la-rebelion/hapimcp in README.md. This repository publishes several servers, so only the opening is shown here.
Stop rewriting systems for AI. Instantly turn your APIs into MCP servers.
HAPI MCP lifts your OpenAPI catalog into MCP tools automatically, keeping design (OAS/Arazzo) and runtime (agents/LLMs) cleanly separated. Your existing APIs become AI-ready tools—no new business logic, no sidecar servers, no rework.
Key Features
- No rewrites: Reuse 100% of your API logic. OpenAPI in, MCP tools out. No parallel codebase or shadow services.
- Faster time-to-value: Turn specs into agent-ready tools in minutes. Update the spec, ship new tools instantly.
- Reduced risk: Permissions, auth, rate limits, auditability are inherited from your APIs—governance without bolt-ons.
- Scales with you: runMCP delivers serverless-like elasticity with long-running when needed. Cold-start fast, stay warm for throughput.
- Deterministic orchestration: OrcA plans and executes multi-tool tasks predictably—no brittle prompt chaining.
- Vendor-neutral: Works with any MCP client: ChatGPT, Claude, QBot, chatMCP. OAS + MCP + Arazzo stay portable.
How It Works
Shortened here. Read the whole README on GitHub.
Signals
- GitHub stars
- 10
- Forks
- 1
- Last commit
- Aug 2026
Advanced
- Delivery
- linkedin MCP server → your ahel connector (mcp.ahel.ai) → your AI.
- Item type
- mcp-server
- Key
ai-com-mcp-linkedin- Source
- github.com/la-rebelion/hapimcp
- Hosted endpoint
https://linkedin.run.mcp.com.ai/mcp