Kapoq MCP Explained

We launched our MCP in March at the Prosper Show — and we’re excited about all of the ways our clients and partners are utilizing it and customizing it to better understand their Amazon and Walmart business.

Model Context Protocol (MCP) servers allow your favorite AI assistant to integrate with data sources. The Kapoq MCP, built on Kapoq DataLink, inherits all the same context about your business that’s already in Kapoq — so your AI assistant can give you better answers with lower effort. It creates a direct connection between your Kapoq data and your preferred AI tool, letting you query your advertising, sales, inventory, and traffic data through plain-English conversation, with no manual data uploads required.

Here’s how your brand can utilize the Kapoq MCP, whether you’re new to AI tools, or are an expert user already.

Get Started with The Basics

If this is your first time interacting with an MCP, you’re in good company! The good news is that getting started integrating your favorite AI assistant into Kapoq is incredibly easy.

Kapoq’s data model adds context and intelligence before your AI assistant ever sees it, which results in pre-aggregated, structured data that produces more accurate, trustworthy insights when paired with AI analysis.

How to Get Started

1. Connect your favorite AI assistant to your Kapoq account. We have detailed walkthroughs for some of the most popular LLMs:
   1. ChatGPT Setup Guide
   2. Claude Setup Guide
   3. Notion Setup Guide
2. Ask a plain-English question about your Kapoq data. Here are some examples our clients love:
   1. What were our top performing products last month?
   2. Show me daily total sales for the last 4 weeks — I want to spot any promotional spikes or drop-offs.
   3. Run a full advertising health check: blended ROAS, ACoS, CPC, CTR, and conversion rate for the available window.
   4. Which ASINs are at risk of stocking out in the next 30 days? Include current stock, daily sales velocity, days of cover, and inbound shipments.

Level Up with Sophisticated Reports and Dashboards

Because the MCP server allows you to integrate your Kapoq data with incredibly powerful AI tools like Claude or ChatGPT, the possibilities for what you can do with your data are endless. 

Many of our clients are using Claude to build live interactive reports in HTML, all with simple natural language prompts and the Kapoq MCP. These reports can be hosted live on an agency’s website so clients can login and view refreshing reports.

You can also build PowerPoint presentations to audit client accounts. When you build your entire audit into a Skill for Claude to run, it uses the Kapoq MCP to pull the data, then builds your presentation for you in minutes.

Additionally, you can build executive summaries and weekly client business reviews. These types of use cases can save your team hours of work, giving them time to do the work that AI can’t do. The list goes on and on — the possibilities are truly endless.

Next Steps

1. Identify where your team is spending too much time on creating reports, decks, or dashboards.
2. Prompt your AI assistant to create these assets.

Develop Advanced Usage in Github

For users who are ready to take the leap into more advanced usage of Kapoq’s MCP, we created the K-Stack on Github — a place for DataLink users to share wins and learnings. We’ll also publish community Skills anyone can drop into their AI assistant!

Every Skill is published under the AGPL 3.0 license which means it is open-source and free to use. Fork them, customize them for your needs, or contribute your own back to the community.

Next Steps

• Go to K-Stack on Github.

1. Open the kstack repository and download the skill you want to try.
2. Add your chosen Skill to your preferred AI assistant and customize it if necessary.

Amazon Ads MCP vs Kapoq MCP

Amazon Ad’s MCP is great, but it doesn’t include all the context about your business and cross-marketplace data that Kapoq’s does. Additionally, Amazon’s native data is inconsistent and hard to trust; it’s often fragmented across reports and APIs and uses inconsistent metric definitions. Many sellers and agencies find that it requires constant clarification and rework, making it easy for AI to misinterpret.

Kapoq MCP, on the other hand, includes all the in-between context and data to allow Amazon MCP to access the data a seller wants or needs to know. Our data is pre-aggregated, contextualized, and AI-ready thanks to our six interconnected modules. Our data uses consistent metrics across advertising, inventory, and sales, with business context embedded before your query even runs. You get trustworthy insights every time.

Many users are already reinventing what’s possible with Kapoq’s MCP. Sign up for a free demo to see how you can get the most out of your data.