About Linked API
Linked API is an MCP server that connects LinkedIn accounts to AI assistants for managing messages, connections, posts, and profile data. It runs actions through a cloud browser and supports polling long-running workflows for their results.
Key features
- 01Search leads and candidates
- 02Review profile and company data
- 03Read and send messages
- 04Manage connections and posts
- 05Track long-running workflows
Use cases
- 01Find prospects and prepare outreach
- 02Search candidates and contact them
- 03Review LinkedIn conversations and draft replies
- 04Gather company and industry activity
MCP support
Exposes LinkedIn search, profile, messaging, connection, post, and related account operations as tools for MCP clients. Long-running actions can be followed with `get_workflow_result` using the returned workflow identifiers.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://mcp.linkedapi.io/mcpclaude mcp add --transport http linked-api-linkedapi https://mcp.linkedapi.io/mcp{"mcpServers":{"linked-api-linkedapi":{"type":"http","url":"https://mcp.linkedapi.io/mcp"}}}Open in Cursor{"servers":{"linked-api-linkedapi":{"type":"http","url":"https://mcp.linkedapi.io/mcp"}}}Open in VS Code{"mcpServers":{"linked-api-linkedapi":{"type":"http","url":"https://mcp.linkedapi.io/mcp"}}}{"mcpServers":{"linked-api-linkedapi":{"serverUrl":"https://mcp.linkedapi.io/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
https://mcp.linkedapi.io/mcpAuth requiredTools
Details
From the project READMELinked 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:
- Installation – set up MCP in Claude, Cursor, VS Code, or Windsurf.
- Available tools – explore all the LinkedIn tools your assistant can call.
- 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.
Comments
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An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.