Using AI Agents to Organize Your LinkedIn Network

8/11/2025

Beyond the Feed: Using AI Agents to Organize Your Professional Network on LinkedIn

Let's be honest, your LinkedIn network is probably a mess.

It’s not your fault. Over the years, you’ve connected with former colleagues, people you met at a conference that one time, interesting folks from your industry, recruiters, potential clients, & maybe even your cousin who just joined the platform. Now, it's a sprawling, disorganized digital rolodex of hundreds or even thousands of people.

When you actually need to find someone—a potential beta tester for your new product, a marketing expert in the SaaS space, or just that one person you spoke to about a partnership last year—it feels like searching for a needle in a haystack. You scroll endlessly, trying to remember names & faces, & your valuable network feels more like a burden than a resource.

But what if you could have a personal assistant, one that works 24/7, to automatically sort, categorize, & make sense of your entire professional network for you?

Turns out, you can. We’re not talking about hiring a virtual assistant. We're talking about building a custom AI agent to do it for you. & at the heart of this emerging technology is something called the Model Context Protocol, or MCP. This isn't some far-off futuristic concept; it's happening right now, & it's changing the way we interact with data & AI.

First Off, What's an "MCP Agent"?

When I first heard the term, I thought it had something to do with a Microsoft certification. Nope. In the world of AI, MCP stands for Model Context Protocol.

Think of it like a universal adapter or a USB-C port for artificial intelligence. It’s an open-source standard, championed by companies like Anthropic (the minds behind the AI model Claude), that creates a consistent way for AI agents to connect with all sorts of tools, data, & services.

Before MCP, getting an AI to perform a multi-step task—like, say, reading a document, summarizing it, & saving the summary to a specific file—required a bunch of clunky, custom-coded integrations. Each tool needed its own special handshake. MCP changes that by creating a standardized "language" that lets AI agents seamlessly plug into different applications & data sources. This makes it MUCH easier to build complex, automated workflows.

So, an "MCP Agent" is simply an AI agent built using this protocol. It’s an agent that can not only think but also do things by interacting with different systems. People are already building them for all kinds of stuff, like finding personalized job opportunities based on a LinkedIn profile or even generating outreach emails.

But we’re going to focus on a task that’s arguably more foundational: bringing order to the chaos of your professional network.

Why Bother Categorizing Your LinkedIn Network?

Is it really worth the effort to organize your connections? Absolutely. A well-organized network is a superpower. The benefits aren’t just about being tidy; they're about unlocking real, tangible opportunities.

Targeted Outreach & Communication: Instead of blasting a generic message to everyone, imagine being able to send a targeted message only to "Software Engineers in the FinTech industry" or "Founders I met at Web Summit 2024." The relevance & response rate of your outreach would skyrocket.
Identifying Hidden Opportunities: By categorizing your contacts, you can spot patterns & opportunities you'd otherwise miss. You might realize you have a strong network of potential clients in a specific niche or a group of experts you could tap for advice on a new venture.
Building Stronger Relationships: Networking isn't just about collecting contacts; it's about building relationships. When you can easily recall who someone is & what you talked about (e.g., "Category: Former Colleague, Notes: Discussed collaboration on Project X"), you can have much more meaningful follow-up conversations.
Enhanced Visibility & Reputation: Being a valuable contributor to your network builds your reputation. By organizing your contacts, you can more easily share relevant information, make helpful introductions, & position yourself as a knowledgeable & connected professional. It makes you the go-to person.
Career Advancement: A sorted network is a career safety net. Whether you're looking for a new job, seeking mentorship, or need expert advice, knowing exactly who to turn to in your network is a massive advantage. It helps you get access to job opportunities & career advice faster.

Honestly, an organized network transforms a passive list of names into an active, valuable asset for your career or business.

How It Works: The Anatomy of a LinkedIn Categorization Agent

Okay, so how does this actually work in practice? Building a custom AI agent to categorize your LinkedIn profiles sounds crazy technical, but the process is becoming more accessible every day, even for those without a coding background.

Here are the core components you’d need:

The Scraper (The Data Gatherer): The first step is to get the data. This is typically done using a scraping tool. Tools like Bright Data, Phantombuster, or others can be tasked with visiting the public profiles of your LinkedIn connections & extracting key information. This includes their job title, company, industry, skills, education, & summary.
The AI Model (The Brains): This is where the magic happens. The raw data scraped from the profiles is fed to a large language model (LLM) like OpenAI's GPT-4 or Anthropic's Claude. You'll give the AI a specific set of instructions—a "prompt"—on how to analyze this data.
The No-Code Platform (The Conductor): A platform like Make.com or Zapier acts as the central hub that orchestrates the entire workflow. You can create an automated "scenario" or "zap" that says: "When I add a new LinkedIn profile URL to a spreadsheet, trigger the scraper, then send the scraped data to the AI with my instructions, & finally, take the AI's output & put it back into my spreadsheet in the correct columns." These platforms offer visual, drag-and-drop interfaces to build these workflows without code.

A Simple Workflow Could Look Like This:

Trigger: You add a LinkedIn profile URL to a Google Sheet.
Action 1 (Scrape): The no-code platform tells your scraping tool to go to that URL & pull the profile data.
Action 2 (Analyze): The scraped text is sent to an AI model with a prompt like:
- "You are an expert network organizer. Analyze the following LinkedIn profile data & categorize the person based on these rules. First, determine their primary industry (e.g., 'SaaS', 'FinTech', 'Healthcare', 'E-commerce'). Second, determine their role seniority (e.g., 'Founder/C-Level', 'VP/Director', 'Manager', 'Individual Contributor'). Third, identify their core function (e.g., 'Engineering', 'Marketing', 'Sales', 'Product'). Return the output in a simple format: Industry, Seniority, Function."
Action 3 (Record): The AI's clean, categorized output is then automatically added to the corresponding columns in your Google Sheet right next to the person's name & profile URL.

You can get as granular as you want with your categories. You could add tags for specific skills ("Python," "SEO," "UX Design"), relationships ("Former Colleague," "Met at Conference"), or potential interest ("Potential Client," "Beta Tester," "Investor Prospect").

The result? A dynamic, self-organizing database of your professional network that you can easily filter, sort, & search.

Putting It Into Practice: Real-World Categorization Examples

Once you have this system in place, the possibilities are pretty cool.

For the Sales Professional: You could create a list of all your connections categorized as "Marketing Managers" in the "E-commerce" industry to introduce them to your new marketing automation tool.
For the Founder: You could filter for "Founders" or "Investors" to get feedback on your pitch deck or search for "Software Engineers" with "React" skills for potential recruitment.
For the Job Seeker: You could identify "Recruiters" or "Hiring Managers" at your target companies & craft a personalized message based on their profile.
For the Community Builder: You could find everyone you "Met at SaaStr 2025" & send a follow-up message to strengthen the new connection.

It moves you from a one-size-fits-all approach to a highly personalized & strategic one.

The Broader Trend: AI is Your New Business Front Door

This idea of using AI to manage & categorize relationships isn't just for your personal LinkedIn network. It’s a powerful concept for businesses, too. Think about the "network" of potential customers who visit your website every day. They come with questions, needs, & different levels of interest. How do you manage & categorize them effectively?

This is where things get really interesting for business operations. Just as an MCP agent can bring order to your personal network, other AI tools can automate engagement with your business network. For instance, businesses are increasingly looking for ways to provide instant, personalized experiences to website visitors. Leaving them to fill out a "Contact Us" form & wait is like adding a great connection on LinkedIn & then never speaking to them again.

This is where a solution like Arsturn comes into play. It taps into the same core idea of using AI for intelligent engagement. Arsturn allows a business to build a no-code AI chatbot that's trained specifically on its own data—its website content, product documentation, help articles, you name it.

This chatbot becomes your 24/7 front door. It can:

Provide Instant Support: Answer customer questions immediately, day or night.
Categorize & Qualify Leads: Just like our LinkedIn agent categorizes contacts, the Arsturn chatbot can ask qualifying questions to understand a visitor's needs & categorize them as a "hot lead," a "customer needing support," or someone "just browsing."
Engage Visitors: Proactively interact with visitors, guiding them to the right information & boosting engagement.

For businesses, this is HUGE. It's about using conversational AI to build meaningful connections with your audience from the very first interaction. It automates that initial sorting & engagement process, ensuring every potential lead or customer is handled promptly & personally, which can seriously boost conversions.

A Quick Word on the Ethics of Scraping

Now, we have to address the elephant in the room: is scraping LinkedIn okay? It's a bit of a gray area. While recent court rulings have suggested that scraping publicly available data isn't illegal, it IS explicitly against LinkedIn's terms of service.

So, if you decide to explore this, you need to be smart & ethical about it.

Respect Privacy: Only use publicly available data & for the purpose you intended. Don't collect sensitive information.
Don't Be a Nuisance: Use tools that mimic human behavior & have delays between actions to avoid overwhelming LinkedIn's servers.
Be Transparent: If you're using this data for outreach, be genuine. The goal is to build real relationships, not to be a spam bot.
Know the Risks: There's always a chance LinkedIn could detect the activity & restrict your account. Proceed with caution & awareness.

The goal isn't to exploit the platform; it's to make your own network more useful for you.

Tying It All Together

Look, the way we manage our professional lives is changing. We have more connections & more data than ever before, but we’re often drowning in it. The rise of accessible AI tools & protocols like MCP gives us a way to fight back against the chaos.

Starting with something as practical as categorizing your LinkedIn network is a perfect first step. It transforms a messy, passive list into a strategic asset that can open doors to new collaborations, clients, & career opportunities. It’s about working smarter, not just harder, to leverage the relationships you’ve already built.

Whether you're organizing your personal network with a custom agent or engaging your business network with a tool like Arsturn, the principle is the same: use AI to build better, more meaningful connections at scale.

Hope this was helpful & gives you some ideas to chew on. Let me know what you think! Would you ever build an agent to organize your own network?