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Automate LinkedIn Lead Generation & Outreach

MCP server connecting LinkedIn to AI assistants via a cloud browser - search leads, analyze profiles, and send messages safely.

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Linked API
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84
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Updated last month
Version 1.0.0
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claudeuniversal
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Why it matters

Leverage AI to automate LinkedIn lead generation, profile analysis, and personalized outreach. This asset connects AI assistants to LinkedIn via a cloud browser for efficient sales and recruitment.

Outcomes

What it gets done

01

Discover and analyze potential leads on LinkedIn.

02

Draft personalized outreach messages for sales and recruitment.

03

Gather competitor and market data through LinkedIn.

04

Automate LinkedIn profile searches and data retrieval.

Install

Add it to your toolbox

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/vb-linked-api-mcp | bash

Capabilities

Tools your agent gets

search_profiles

Search LinkedIn profiles by criteria like job title, company, location, and skills.

analyze_profile

Analyze LinkedIn profile information including experience, skills, and qualifications.

send_message

Send automated personalized messages to LinkedIn connections and prospects.

read_conversations

Read and retrieve existing LinkedIn conversations and message history.

suggest_responses

Generate suggested responses for LinkedIn conversations and messages.

generate_leads

Discover and generate qualified leads based on specified search criteria.

qualify_leads

Evaluate and qualify leads based on profile data and engagement metrics.

draft_outreach

Create personalized outreach messages for sales and recruitment campaigns.

Overview

Linked API MCP Server

Linked API MCP Server connects LinkedIn to an AI assistant via a queued cloud browser, enabling lead search, profile analysis, and messaging. Use it for AI-driven LinkedIn research and outreach; long-running actions must be polled via get_workflow_result rather than retried.

What it does

Linked API MCP Server connects a LinkedIn account to AI assistants like Claude, Cursor, and VS Code, letting them search for leads, analyze profiles, read and respond to conversations, and gather company/market data - all executed through a cloud browser rather than direct API scraping, intended to run safely and automatically. It supports use cases like sales lead generation and outreach drafting, recruitment candidate search and initial contact, reading and replying to existing LinkedIn conversations with context, and competitor/market research on companies and their employees.

Because actions run through a queued cloud browser, many operations - especially searches and profile fetches with optional data - take several minutes to complete rather than returning instantly.

When to use - and when NOT to

Use this connector when you want an assistant to automate LinkedIn research and outreach - finding leads or candidates matching specific criteria, analyzing a profile's background, or drafting/sending contextual messages - without you manually browsing LinkedIn.

Do not retry a tool call that returns status, workflowId, operationName, and message fields - that means the action is still running asynchronously in the cloud browser queue. Retrying would queue duplicate work; instead poll get_workflow_result with the exact workflowId/operationName until the final result comes back.

Inputs and outputs

Search and analysis tools take LinkedIn search criteria (role, company size, location) or profile/company identifiers. Messaging tools take a target profile and message content. Long-running actions return an intermediate status/workflowId/operationName/message response; get_workflow_result takes that workflowId and operationName (plus optional waitSeconds) and returns the final result, long-polling by default until completion or the client's request budget elapses.

Capabilities

  • Search LinkedIn for leads or candidates by criteria (role, company size, location, skills)
  • Analyze LinkedIn profiles and company/employee data
  • Read and respond to existing LinkedIn conversations with context-aware suggestions
  • Send connection requests and messages
  • get_workflow_result: poll for the final result of a long-running queued action by workflowId/operationName

How to install

Follow the official installation guide at linkedapi.io/mcp/installation for Claude, Cursor, VS Code, or Windsurf. See the available-tools and usage-examples docs for the full tool list and sample prompts.

Who it's for

Sales, recruiting, and market research teams who want an AI assistant to search, analyze, and message LinkedIn contacts without manual browsing.

Source README

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.

FAQ

Common questions

Discussion

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