search-webanalytics-data

Linkd

automcp-app

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

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Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

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 68 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.4 out of 5—verify behavior in your own environment before production use.

Use Cases

Web Research & Information Gathering

Fetch and extract information from websites automatically

Example

Research competitor pricing, scrape product reviews, monitor news mentions

Automate 5-10 hours/week of manual web research

Content Monitoring & Alerts

Track website changes, new content, price updates

Example

Monitor competitor blog for new posts, track stock availability, watch for pricing changes

Stay informed without manual checking, never miss important updates

Data Extraction & Aggregation

Extract structured data from multiple websites

Example

Compile product listings from 10 e-commerce sites, aggregate job postings, collect real estate data

Build datasets 100x faster than manual copying

API-less Integration

Interact with services that don't offer APIs

Example

Check form submissions, validate website functionality, test user flows

Automate interactions with any website, even without API

Implementation Guide

Prerequisites

  • Claude Desktop or Cursor with MCP support
  • Understanding of web scraping ethics and robots.txt
  • Rate limiting awareness to avoid overwhelming target sites
  • Knowledge of legal restrictions on data collection

Time Estimate

20-40 minutes including configuration and testing

Installation Steps

  1. 1.Install web automation MCP server via npm or pip
  2. 2.Configure allowed domains and rate limits in MCP config
  3. 3.Test with simple fetch: 'Get content from example.com'
  4. 4.Progress to extraction: 'Extract all product prices from this page'
  5. 5.Set up monitoring: 'Check this URL daily for changes'
  6. 6.Parse structured data: 'Create CSV from this table'
  7. 7.Respect robots.txt and rate limits always

Troubleshooting

  • 403 Forbidden: Website blocks bots—respect their wishes, use official API instead
  • Rate limit errors: Slow down requests, add delays between fetches
  • Stale data: Target site changed HTML structure—update selectors
  • Timeout errors: Site is slow or blocking—increase timeout, try different user agent
  • JavaScript-rendered content: Use headless browser MCP servers for dynamic sites

Best Practices

✓ Do

  • +Check robots.txt and respect crawl rules
  • +Rate limit requests: 1-2 requests/second maximum
  • +Use official APIs when available instead of scraping
  • +Identify your bot with descriptive user agent
  • +Cache results to minimize repeated requests
  • +Handle errors gracefully with retries and fallbacks
  • +Validate extracted data for accuracy

✗ Don't

  • Don't scrape sites that explicitly forbid it (robots.txt, ToS)
  • Don't overwhelm servers with rapid requests—use rate limiting
  • Don't scrape personal data without consent and legal basis
  • Don't ignore copyright on extracted content
  • Don't assume HTML structure is stable—handle changes
  • Don't use scraped data for commercial purposes without permission

💡 Pro Tips

  • Use CSS selectors or XPath for robust data extraction
  • Set up monitoring alerts for extraction failures (structure changed)
  • Implement exponential backoff for retries on failures
  • Store raw HTML for reprocessing if extraction logic changes
  • Combine with data analysis tools for insights from extracted data
  • Consider using official APIs or RSS feeds as more stable alternatives

Technical Details

Architecture

MCP server handles HTTP requests, HTML parsing, JavaScript rendering (if headless browser), and returns structured data to Claude.

Protocols

  • HTTP/HTTPS
  • WebSocket (for real-time sites)
  • Puppeteer/Playwright (for JavaScript sites)

Compatibility

  • Static HTML sites
  • JavaScript-rendered SPAs (with headless browser)
  • REST APIs
  • GraphQL endpoints

When to Use This

✓ Use When

Use for research automation, content monitoring, data aggregation from multiple sources, and when official APIs don't exist. Best for read-only information gathering.

✗ Avoid When

Avoid for sites with APIs (use API instead), sites that explicitly forbid scraping, when data is copyrighted, or for login-required content without proper authorization.

Integration

  • Scheduled monitoring with change detection
  • Multi-source data aggregation pipelines
  • Fallback to web scraping when API rate limits hit
  • Headless browser for JavaScript-heavy sites

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.468 reviews
  • Nikhil Robinson· Dec 28, 2024

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

  • Dhruvi Jain· Dec 24, 2024

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

  • James Bhatia· Dec 20, 2024

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

  • Hiroshi Chen· Dec 16, 2024

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

  • Harper Perez· Dec 16, 2024

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

  • Valentina Iyer· Dec 16, 2024

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

  • Aarav Johnson· Nov 19, 2024

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

  • Oshnikdeep· Nov 15, 2024

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

  • Nikhil Gonzalez· Nov 11, 2024

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

  • Harper Gonzalez· Nov 7, 2024

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

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