search-webanalytics-data

Linkd

by automcp-app

Linkd uses the LinkedIn API for easy recruitment—search contacts, extract profiles, and boost sales prospecting with dee

Integrates with Linkd API to extract LinkedIn user and company profiles, search contacts, retrieve email addresses, and perform deep research workflows for sales prospecting and recruitment.

github stars

3

Requires Linkd API keyCredit-based usage model

best for

  • / Sales professionals building prospect lists
  • / Recruiters sourcing candidates
  • / Business development teams researching leads
  • / Marketing teams building contact databases

capabilities

  • / Search LinkedIn users with filters
  • / Search companies on LinkedIn
  • / Extract detailed LinkedIn profile data
  • / Retrieve email addresses and phone numbers
  • / Scrape LinkedIn posts and comments

what it does

Integrates with Linkd API to extract LinkedIn profiles, search for users and companies, and retrieve contact information for sales prospecting and recruitment workflows.

about

Linkd is a community-built MCP server published by automcp-app that provides AI assistants with tools and capabilities via the Model Context Protocol. Linkd uses the LinkedIn API for easy recruitment—search contacts, extract profiles, and boost sales prospecting with dee It is categorized under search web, analytics data.

how to install

You can install Linkd in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

Linkd is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

Linkd MCP Server

This is an unofficial Model Context Protocol (MCP) Server for Linkd..

More information about automcp can be found at automcp.app.

For detailed API documentation and usage examples, visit the official Linkd documentation.

More information about the Model Context Protocol can be found here.

Table of Contents

Installation

Manual Installation

To install the server, run:

npx linkd-mcp <YOUR-LINKD-API-KEY>

Running on Cursor

Add to ~/.cursor/mcp.json like this:

{
  "mcpServers": {
    "linkd": {
      "command": "npx",
      "args": ["-y", "linkd-mcp"],
      "env": {
        "LINKD_API_KEY": "YOUR-API-KEY"
      }
    }
  }
}

Running on Windsurf

Add to your ./codeium/windsurf/model_config.json like this:

{
  "mcpServers": {
    "linkd": {
      "command": "npx",
      "args": ["-y", "linkd-mcp"],
      "env": {
        "LINKD_API_KEY": "YOUR-API-KEY"
      }
    }
  }
}

Claude Desktop app

This is an example config for the Linkd MCP server for the Claude Desktop client.

{
  "mcpServers": {
    "linkd": {
      "command": "npx",
      "args": ["--yes", "linkd-mcp"],
      "env": {
        "LINKD_API_KEY": "your-api-key"
      }
    }
  }
}

Tools

  • search_for_users - Search for LinkedIn users with filters like query, school, and match threshold
  • search_for_companies - Search for companies on Linkd using filters like query and match threshold
  • enrich_linkedin - Retrieves detailed profile information for a specific LinkedIn URL (1 credit per lookup)
  • retrieve_contacts - Retrieves email addresses and phone numbers for a LinkedIn profile (1 credit per lookup)
  • scrape_linkedin - Retrieves detailed profile data and posts with comments from a LinkedIn profile URL (2 credits per request)
  • research_profile - Research a profile using email or phone number
  • initiate_deep_research - Start a deep research job for comprehensive LinkedIn data gathering
  • check_deep_research_status - Check the status of an ongoing deep research job

License

This project is licensed under the MIT License.

FAQ

What is the Linkd MCP server?
Linkd is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Linkd?
This profile displays 10 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
MCP server reviews

Ratings

4.510 reviews
  • Shikha Mishra· Oct 10, 2024

    Linkd is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Piyush G· Sep 9, 2024

    We evaluated Linkd against two servers with overlapping tools; this profile had the clearer scope statement.

  • Chaitanya Patil· Aug 8, 2024

    Useful MCP listing: Linkd is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Sakshi Patil· Jul 7, 2024

    Linkd reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Ganesh Mohane· Jun 6, 2024

    I recommend Linkd for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Oshnikdeep· May 5, 2024

    Strong directory entry: Linkd surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Dhruvi Jain· Apr 4, 2024

    Linkd has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Rahul Santra· Mar 3, 2024

    According to our notes, Linkd benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Pratham Ware· Feb 2, 2024

    We wired Linkd into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Yash Thakker· Jan 1, 2024

    Linkd is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.