Why We Shipped a Claude Plugin First

The Decision That Shaped Our Product Strategy

When we started building SearchFit, we faced a straightforward question: which AI platform should we target first with our answer engine optimization tooling? The obvious choice seemed to be ChatGPT. It dominates consumer AI usage. It has the largest installed base. Every SEO and growth team we talk to mentions ChatGPT first when discussing AI visibility concerns.

We built the ChatGPT GPT anyway, it works well. But we shipped the Claude plugin first. That choice wasn't random, and it wasn't contrarian for its own sake. It came from watching how the AI ecosystem is actually developing, understanding where answer engine optimization matters most right now, and recognizing that the Claude marketplace represents a fundamentally different opportunity for brands trying to rank in AI search.

This post explains that reasoning. If you're managing AI visibility for a brand, thinking about how to position your content for LLM visibility, or trying to understand where to focus your answer engine optimization efforts, understanding why we made this call will help you make better decisions about your own AI-first content strategy.

Understanding the Claude Marketplace Advantage

The Claude marketplace exists. That's the first fact that matters.

When Anthropic announced plugins for Claude, they didn't just release a technical capability, they created a discoverable, categorized, searchable marketplace where businesses can actually find and install purpose-built tools. Visit Build with Claude - Plugin Marketplace and you'll see exactly what we mean. Plugins are organized by category. They have install counts. They get reviewed and rated. Users actively browse and install them.

Compare that to ChatGPT's GPT store. The GPT store exists, but adoption has been slower. Many users don't know it exists. Discovery is harder. Installation friction is higher. Most importantly, there's no clear signal yet that GPTs are driving meaningful traffic or visibility for brands.

When we looked at the data, actual usage patterns, plugin installation metrics, user behavior, Claude's plugin ecosystem showed something we hadn't seen in ChatGPT's GPT space: real, measurable adoption by people looking for specific solutions to specific problems. That's the environment where answer engine optimization actually works. That's where brands can gain visibility through AI.

The Claude plugin marketplace is also younger, which means less saturation. When you ship a plugin to a mature marketplace, you're competing against thousands of existing solutions. When you ship to an emerging marketplace, you're helping define how that category develops. We chose the latter.

Why Plugin Architecture Beats GPT Architecture for AEO

There's a technical reason we prioritized the Claude plugin route, beyond just marketplace dynamics.

Plugins in Claude's ecosystem are built on a different architecture than ChatGPT GPTs. According to Introducing Plugins for Claude, Claude's plugin system is designed around function calling and real-time data retrieval. This means a Claude plugin can actually fetch current information, interact with APIs, and provide fresh data to Claude as it generates responses.

For answer engine optimization, this matters enormously. When someone searches in Claude or Perplexity and those engines need to cite sources, they're looking for plugins and integrations that can provide real-time, authoritative data. A plugin that can reliably fetch your brand's current information, product data, or content is fundamentally more useful to the AI engine than a static GPT.

This architectural difference means Claude plugins can participate in the citation chain more effectively. When Claude is generating an answer and needs to pull in external information, it has native mechanisms to call plugins and integrate their responses directly into the answer. That's where your brand gets cited. That's where answer engine optimization actually happens.

GPTs, by contrast, are more like isolated conversational experiences. You start a conversation with a GPT, and it operates in its own space. That's great for specific use cases, but it's not the same as being integrated into the core answer generation process across multiple AI engines.

The Citation Problem That Answer Engine Optimization Solves

Let's step back and talk about the actual problem we're solving.

When someone asks a question in ChatGPT, Perplexity, Gemini, or Claude, the AI engine generates an answer. That answer often includes citations. Sometimes those citations point to your brand's content. Sometimes they point to competitors. Sometimes they point to outdated information. Most of the time, brands have zero visibility into which answers cite them, how often that happens, or what they could do to increase those citations.

That's the problem answer engine optimization addresses. And it's a real, measurable problem. We've talked to dozens of B2B SaaS companies, e-commerce brands, and agencies managing multiple clients, and they're all reporting the same thing: their organic search traffic is flat or declining, and they suspect AI answer engines are cannibalizing that traffic. They're right.

The question then becomes: if traffic is moving to AI answers, how do you get cited in those answers? How do you gain visibility in Claude, ChatGPT, Perplexity, and Gemini?

That's where the plugin architecture becomes critical. It's not enough to just have good content. You need to be integrated into the systems that AI engines use to generate answers. You need to be discoverable by the AI engines themselves, not just by human users. You need to be cited, not just found.

A Claude plugin that your brand controls, that can feed real-time data directly into Claude's answer generation process, is exactly that kind of integration point. It's a direct line from your brand's information to the AI engine's responses. That's answer engine optimization in practice.

How Plugin-First Strategy Informs Content Engineering

Shipping the Claude plugin first also forced us to think differently about content engineering.

When you're building a GPT, you're essentially creating a chatbot that lives inside ChatGPT. The user interacts with your GPT directly. That's a user experience problem.

When you're building a Claude plugin, you're creating a tool that Claude itself will call when it needs information. The user never directly interacts with your plugin, they interact with Claude, and Claude calls your plugin behind the scenes. That's a systems integration problem, and it's a much more interesting one for answer engine optimization.

This distinction forced us to think about: What information does Claude actually need when it's generating answers? How should that information be structured so Claude can parse it and integrate it into its responses? What format makes it easiest for Claude to cite your brand accurately?

Those are the right questions for answer engine optimization. They're not about building a better chatbot. They're about making your brand's information as useful as possible to AI engines when they're generating answers.

When you think about your content strategy this way, not as content for humans reading a website, but as data structures that AI engines can reliably parse and cite, you start making different decisions about how to organize, format, and present information. You start thinking about API schemas and structured data. You start thinking about real-time updates instead of static pages.

That's the shift we wanted to model for our customers. By shipping a Claude plugin first, we were saying: this is where answer engine optimization is heading. This is the architecture that matters. This is how you actually gain visibility in AI search.

Prerequisites: What You Need to Build an Answer Engine Optimization Strategy

Before we walk through how we approached the Claude plugin build, let's establish what you need in place to make answer engine optimization work at all.

Accurate, Structured Data About Your Brand

Your plugin can't cite information it doesn't have. Before you build any integration with Claude or any other AI engine, you need a clear, accurate, structured source of truth about your brand, products, services, or content. This could be a database, an API, or a well-organized knowledge base. The key is that it needs to be:

• Current (updated regularly, ideally in real-time)
• Comprehensive (covering the full range of information AI engines might need to cite)
• Structured (formatted so that APIs and AI systems can parse it reliably)
• Authoritative (the single source of truth for your brand's information)

Many brands we talk to don't have this. They have scattered information across multiple platforms, outdated content, and no single system that an AI engine could reliably query. That's a problem. You can't participate in answer engine optimization if you don't have your own information organized.

Monitoring Capability Across Multiple AI Engines

You also need visibility into where you're being cited. That's why SearchFit exists, to track your brand visibility across AI platforms like ChatGPT, Perplexity, Claude, and Gemini and monitor how AI recommends your business.

Without this visibility, you're flying blind. You won't know if your plugin is working. You won't know which AI engines are citing you, which ones aren't, and why. You won't be able to measure the impact of your answer engine optimization efforts.

Building a plugin without monitoring is like running an SEO campaign without analytics. You might be doing the work, but you have no idea if it's working.

Content That Answers Questions, Not Just Sells Products

AI engines cite sources when they're answering user questions. They don't cite product pages or marketing copy. They cite authoritative, informative content that actually helps answer the question the user asked.

If your content strategy is purely promotional, if every piece of content is designed to sell something, you're going to struggle with answer engine optimization. You need content that answers questions your potential customers are asking, even if those answers don't directly lead to a sale.

For a B2B SaaS company, that might mean blog posts about industry trends, technical guides, best practices, or problem-solving frameworks. For an e-commerce brand, it might mean buying guides, product comparisons, or how-to content. For an agency, it might mean case studies or methodology explainers.

The content doesn't need to be selfless, it can and should position your brand as the expert, but it needs to genuinely answer the question. That's what AI engines cite.

Step 1: Map Your Answer Engine Optimization Opportunity

Before you build anything, you need to understand where answer engine optimization actually matters for your business.

Start by identifying the questions your potential customers are asking in AI engines. These are different from the keywords people search for in Google. They're conversational, specific, and often comparative.

For a SaaS company selling project management software, people might search Google for "project management software." But in Claude or ChatGPT, they might ask: "What's the best project management tool for remote teams?" or "How do I choose between Monday.com and Asana?" or "What features should I look for in project management software?"

Those questions are answer engine optimization opportunities. When Claude generates an answer to any of those questions, it's likely to cite sources. If your brand is cited, you gain visibility and credibility with someone actively considering a purchase.

Start mapping these questions:

1. List the top 20-30 questions your customers ask during their buying journey. Think about the questions that come up in sales calls, support tickets, and product demos.

2. Search for those questions in Claude, ChatGPT, Perplexity, and Gemini. See which AI engines answer them. See which sources get cited. See if your brand is mentioned.

3. Identify the gaps. Where are questions being answered without citing your brand? Where are competitors being cited instead? Where is information missing or outdated?

4. Prioritize. Focus on questions where:

• Your brand has unique, authoritative information - The question is actively being asked in AI engines - Your competitors aren't already dominating the citations - The question aligns with your business goals

This mapping exercise is critical. It tells you exactly where to focus your answer engine optimization efforts. It's the difference between building a plugin that might be useful and building a plugin that directly addresses the visibility gaps in your AI search presence.

Step 2: Structure Your Data for AI Engine Integration

Once you've identified your answer engine optimization opportunities, you need to structure your data so that AI engines can reliably access and cite it.

This is where the technical architecture becomes important. When you're building a Claude plugin, you're essentially building an API that Claude can call. That API needs to return structured data that Claude can parse, understand, and cite accurately.

According to the Plugins reference - Claude Code Docs, Claude's plugin system uses standard API schemas and function calling. This means your plugin needs to expose clear, well-documented functions that Claude can call to retrieve specific information.

For a SaaS company, this might look like:

• A function that returns your current pricing and features
• A function that returns case studies and customer success stories
• A function that returns technical documentation or API information
• A function that returns company information, team details, or company history

Each function should:

• Have a clear, descriptive name (e.g., get_pricing_information instead of fetch_data)
• Accept specific parameters that allow Claude to request exactly what it needs
• Return structured data in a consistent format (JSON is standard)
• Include metadata that helps Claude understand what the data represents and how to cite it

The key principle: make it easy for Claude to get exactly the information it needs, in the format it needs, so it can confidently cite your brand.

Many plugins fail at this step. They return too much data, making it hard for Claude to find what it needs. They return unstructured data that Claude has to parse. They return information without clear metadata about what it represents. All of these problems reduce the likelihood that Claude will cite your brand accurately or at all.

Invest time in getting this right. Your data structure is the foundation of your answer engine optimization strategy.

Step 3: Build and Deploy Your Claude Plugin

Now you're ready to build. The good news: Claude's plugin system is well-documented and relatively straightforward to implement.

The Build with Claude - Plugin Marketplace provides the official marketplace and documentation. Start by reviewing the Build with Claude Plugins - Anthropic Developer Docs to understand the full development process.

Here's the high-level process:

1. Define Your Plugin's Purpose and Capabilities

Write a clear description of what your plugin does. This description will appear in the Claude marketplace, so it needs to be clear to both Claude and to human users who might discover your plugin.

For SearchFit, our Claude plugin's purpose is straightforward: it provides real-time data about a brand's visibility across AI search engines. When Claude is answering a question about AI search visibility or answer engine optimization, it can call our plugin to get current, accurate data.

2. Design Your API Schema

Define the functions your plugin will expose. For each function:

• Write a clear description of what it does
• Define the parameters it accepts
• Specify the format of the data it returns
• Include examples

This schema is what Claude uses to understand when and how to call your plugin.

3. Implement Your Backend

Build the actual API that your plugin will call. This is where your structured data comes in. Your API needs to reliably retrieve the information your plugin promises to return.

Make sure your API:

• Handles errors gracefully
• Returns data in the exact format your schema specifies
• Includes proper authentication if needed
• Performs well (Claude will timeout if your API is too slow)

4. Test with Claude

Before you submit to the marketplace, test your plugin directly with Claude. Use Claude Code: allow web fetch on all domains to understand how Claude handles external API calls and web fetching.

Try asking Claude questions that your plugin is designed to answer. See if Claude calls your plugin. See if it uses the data correctly. See if it cites your brand.

This testing phase is crucial. It's where you'll discover if your data structure works in practice, if your API is reliable, and if Claude actually uses your plugin the way you intended.

5. Submit to the Claude Marketplace

Once you're confident your plugin works, submit it to the Build with Claude - Plugin Marketplace. The marketplace has a submission process and review criteria. Follow those carefully.

Your plugin listing should include:

• A clear, compelling description
• Screenshots or examples of how the plugin works
• Instructions for installation and use
• Information about your brand and why your plugin is authoritative

Remember: your plugin listing is part of your answer engine optimization strategy. Users discovering your plugin in the marketplace is one way you gain visibility. But more importantly, Claude calling your plugin and citing your brand in answers is the real win.

Step 4: Monitor Your Answer Engine Optimization Performance

Shipping your Claude plugin isn't the end, it's the beginning. Now you need to measure whether it's actually improving your AI search visibility.

This is where AI Tracking | SearchFIT becomes essential. You need to track:

• Citation frequency: How often is your brand being cited in Claude answers?
• Citation context: What questions are triggering your brand's citation?
• Citation quality: Are you being cited as a primary source or a secondary mention?
• Citation trends: Is your citation frequency increasing over time?
• Competitive positioning: How do your citations compare to competitors?

Without this data, you won't know if your plugin is working. You might have built something technically sound that nobody uses. Or you might have built something that works great but isn't being called by Claude because Claude doesn't encounter questions where it would be useful.

The Analytics | SearchFIT dashboard should show you AI-powered analytics and insights for your SEO performance, tracking rankings, traffic, and visibility across all platforms.

Set up regular monitoring, weekly or monthly reviews of your citation data. Look for:

• Spikes in citations (indicating your plugin is being used)
• Patterns in which questions trigger your citations
• Opportunities to expand your plugin's capabilities based on questions Claude is asking but your plugin isn't answering

Use this data to iterate. If certain types of questions aren't triggering your citations, update your plugin to handle those questions better. If certain data points are being cited frequently, double down on those areas.

Step 5: Iterate Based on Real-World Usage

Your Claude plugin won't be perfect on day one. Real-world usage will reveal gaps, opportunities, and improvements.

Common iterations we've made:

Expanding Your Data Coverage

You might discover that Claude is asking your plugin for information you didn't think to include. For example, we initially focused our SearchFit plugin on current visibility data, but we found Claude was also asking about how to improve AI search visibility. So we expanded the plugin to include recommendations and best practices.

Improving Response Speed

If your plugin is slow, Claude might timeout or deprioritize calling it. Monitor your API performance and optimize. Sometimes this means caching more data, sometimes it means restructuring your queries, sometimes it means upgrading your infrastructure.

Clarifying Your Data

If Claude is citing your brand but misinterpreting the data, your data structure might need clarification. Add better descriptions, include examples, or restructure the data to be more explicit about what it represents.

Adding New Functions

As you see which questions Claude is asking, you might realize you need to expose new functions. If Claude keeps asking about your pricing but your plugin only returns product information, add a pricing function.

The beauty of the plugin approach is that iteration is fast. You don't need to wait for a marketplace review or a new deployment cycle. You can update your backend API and Claude will immediately start calling the new version.

Pro Tips for Claude Plugin Answer Engine Optimization

Tip 1: Make Your Plugin Discoverable

Your plugin won't be useful if Claude doesn't know about it. Make sure your plugin description clearly explains what information it provides and in what contexts Claude should use it.

Avoid vague descriptions like "Get information about our company." Instead, be specific: "Get current pricing, features, and customer success metrics for SearchFit's AI visibility platform."

The more specific your description, the more likely Claude is to call your plugin when it's relevant.

Tip 2: Optimize for Citation Accuracy

Remember: the goal isn't just to have Claude call your plugin. The goal is to have Claude cite your brand in its answer.

Include clear metadata with your data that makes it easy for Claude to cite you correctly. Include your brand name, your website URL, and any relevant context about why this information is authoritative.

If your plugin returns a case study, include the client name, the results achieved, and the date. If it returns pricing information, include when that pricing was last updated. This context helps Claude cite you accurately and confidently.

Tip 3: Keep Your Plugin Focused

Don't try to make your plugin do everything. A focused plugin that does one thing well is more useful than a sprawling plugin that tries to answer every possible question.

SearchFit's plugin focuses specifically on AI search visibility data. We don't try to answer general questions about SEO or marketing strategy. We answer questions about AI visibility specifically. That focus makes our plugin more useful to Claude and more likely to be cited.

Tip 4: Monitor Competitor Plugins

You're not the only brand building Claude plugins. Check the Best Claude Code Plugins (2026): 10 Tested, 4 Worth Keeping to see what's working in the marketplace and what isn't.

Understand what your competitors' plugins do. Understand how they're being used. Use that intelligence to build a better plugin.

Tip 5: Integrate with Your Broader Answer Engine Optimization Strategy

Your Claude plugin is one piece of your answer engine optimization strategy. You also need to:

• Optimize your content for Perplexity citations (which has different citation mechanisms)
• Build relationships with ChatGPT's knowledge retrieval system
• Ensure your brand is cited in Google's AI Overviews
• Monitor your visibility across all AI engines

The plugin is important, but it's not the whole strategy. Use SearchFit's AI tracking capabilities to understand your visibility across all engines, not just Claude.

Why This Approach Scales for Your Brand

We chose to ship the Claude plugin first for specific, measurable reasons. But those reasons apply to your brand too.

If you're managing AI visibility for a B2B SaaS company, an e-commerce brand, or an agency managing multiple clients, the same logic applies: focus on the AI platforms where your visibility gaps are biggest and where integration is most straightforward.

For many brands, that's Claude right now. The marketplace is less saturated. The plugin architecture is cleaner. The citation mechanisms are more predictable. The opportunity to establish authority is greater.

But the broader principle matters more than the specific platform: answer engine optimization is about integration, not just content. It's about making your information as useful as possible to AI engines when they're generating answers. It's about being cited, not just found.

Plugins are the most direct way to achieve that integration. They're the closest thing to a direct line from your brand's information to the AI engine's responses. That's why we prioritized them.

The Bigger Picture: Why Answer Engine Optimization Matters Now

Let's zoom out for a moment. Why are we talking about Claude plugins at all? Why does answer engine optimization matter?

Because traffic is moving. Users are asking questions in Claude, ChatGPT, Perplexity, and Gemini instead of searching Google. When they do, they see AI-generated answers that cite sources. Those citations determine which brands gain visibility and which don't.

For the first time in search history, you can't just optimize for keyword rankings. You need to optimize for citations in AI-generated answers. You need to be integrated into the systems that AI engines use to generate those answers.

That's answer engine optimization. And plugins are the most direct path to making it work.

If you're losing organic traffic to AI answers, or if you're concerned that you might be in the near future, now is the time to act. The marketplace is still emerging. Competition is still manageable. Your opportunity to establish authority in AI search is real.

Start with the mapping exercise. Understand where your answer engine optimization opportunities are. Then build the integrations, whether that's a Claude plugin, a Perplexity integration, or both, that make your information as useful as possible to AI engines.

That's how you maintain visibility as search evolves. That's how you stay relevant when your customers are asking questions in AI engines instead of Google.

Key Takeaways: Why We Shipped a Claude Plugin First

1. The Claude Marketplace Represents Real Opportunity

Unlike ChatGPT's GPT store, Claude's plugin marketplace is actively used, discoverable, and still emerging. That's where answer engine optimization works best right now.

2. Plugin Architecture Enables Real Integration

Plugins aren't just chatbots, they're function calls that Claude uses when generating answers. That's where citations happen. That's where answer engine optimization matters.

3. Answer Engine Optimization Requires Structured Data

You can't participate in AI citations without having your information organized, current, and structured so that AI engines can reliably parse and cite it.

4. Visibility Requires Monitoring

You need to track where you're being cited across AI engines. That's the only way to know if your answer engine optimization efforts are working and where to focus next.

5. Integration Beats Content Alone

Great content is necessary but not sufficient. You need to be integrated into the systems that AI engines use to generate answers. That's where plugins come in.

If you're managing AI visibility for your brand, start with these steps: map your answer engine optimization opportunities, structure your data, and build the integrations that make your information as useful as possible to AI engines.

The future of search is happening in AI engines. Your visibility there determines your success. Plugins are how you make that happen.