Linkedapi MCP

Communauté Marketing et ventes

Control LinkedIn accounts and retrieve real-time LinkedIn data.

Que pouvez-vous faire avec Linkedapi MCP ?

  • 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 m...
  • 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.

Installation

Les étapes d'installation sont dans la documentation ci-dessous. Documentation

Documentation

Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.

Sommaire
  1. Use cases
  2. Get started
  3. Long-running actions
  4. License

Linked API MCP server connects your LinkedIn account to AI assistants like Claude, Cursor, and VS Code. Ask them to search for leads, send messages, analyze profiles, and much more – they'll handle it through our cloud browser, safely and automatically.

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.

Questions fréquentes

Qu'est-ce que Linkedapi MCP ?

Control LinkedIn accounts and retrieve real-time LinkedIn data.

Comment installer Linkedapi MCP ?

Suivez les étapes d'installation de sa documentation, affichée sur cette page et dans son dépôt.

Linkedapi MCP est-il open source ?

Oui. Son code est sur GitHub sous licence MIT.

Qui maintient Linkedapi MCP ?

Il est publié par Linked-API. AI.tn le référence sans le maintenir ni le recommander.

Issu des listes communautaires awesome-mcp-servers et du dépôt GitHub du projet. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.