Linked-API/linkedapi-mcp

Use cases
- **Sales automation assistant**. Ask your AI to find leads, check their profiles, and draft personalized outreach. It can search for "software engineers at companies with 50-200 employees in San Francisco", analyze their backgrounds, and suggest connection messages that actually make sense.
- **Recruitment assistant**. Let your assistant search for candidates with specific skills, review their experience, and send initial outreach. It handles the time-consuming parts while you focus on actually talking to people.
- **Conversation assistant**. Your AI can read your existing LinkedIn conversations and help you respond naturally. It understands the context of your chats, suggests relevant replies, and can even send follow-up messages.
- **Market research assistant**. Need competitor analysis? Your assistant can gather data about companies, their employees, and recent activities. Get insights about industry trends without spending hours on LinkedIn.
Get started
To start using Linked API MCP, spend 2 minutes reading these essential guides:
1. Installation – set up MCP in Claude, Cursor, VS Code, or Windsurf.
2. Available tools – explore all the LinkedIn tools your assistant can call.
3. Usage examples – see real-world examples to get you started quickly.
Long-running actions
Linked API actions run through a cloud browser and are queued like normal automation. Many actions take several minutes, especially searches and profile fetches with optional data.
If a tool returns status, workflowId, operationName, and message, the action is still running. Do not retry the original tool because that can queue duplicate work. Call get_workflow_result with the exact workflowId and operationName until the final result is returned. By default get_workflow_result long-polls until the workflow completes or the current MCP client's request budget elapses; pass waitSeconds: 0 for an immediate single-shot snapshot.
License
This project is licensed under the MIT – see the LICENSE file for details.