Introducing Jungle Scout MCP — a direct line between the AI your team already uses and Cobalt’s Amazon marketplace intelligence.
Most teams already know what they want to ask. “Who’s gaining in my category?” “Which price tiers are growing?” “Why did our share slip last quarter?” The hard part has never been the question. It’s the detour between asking it and getting a trustworthy answer — the dashboard export, the SQL query, the ticket to the analytics team, the wait.
Jungle Scout MCP removes the detour. It connects the AI assistant your team already works in — Claude, ChatGPT, Gemini, Microsoft Copilot — directly to Jungle Scout’s Amazon data. You ask in plain English, and the answer comes back grounded in real marketplace intelligence. No export. No SQL. No IT ticket.
Get a demoSo what is an MCP, exactly?
MCP stands for Model Context Protocol — but the simplest way to think about it is “an API for AI.” It gives an AI assistant a direct, secure line to a specific source of data. In this case, that source is Jungle Scout’s Cobalt: the same Amazon intelligence enterprise teams already rely on for category, competitor, pricing, keyword, and share analysis.
The difference is where the work happens. Instead of pulling data out of Cobalt and into a deck or spreadsheet, you bring Cobalt’s data into the conversation — inside the tools where decisions actually get made.
Why general-purpose AI isn’t enough on its own
General-purpose AI can help draft, summarize, and organize information. But it can’t independently answer why a competitor is gaining share, which price tiers are growing, who owns the keywords driving your category, or where new products are entering the market. Jungle Scout can—because it’s built for ecommerce intelligence, with the data and speed to surface those answers fast.
Ask a standalone model why a competitor is gaining share and it will give you a confident, plausible, and entirely ungrounded answer — because it has no live view of the marketplace. It doesn’t know which price tiers are growing, who owns the keywords driving demand, or where new products are entering. That’s the context Jungle Scout MCP supplies.
“The MCP is a total game changer for the power of Jungle Scout data.”
— Customer & Fortune 500 CPG brand
From question to answer, in seconds
Here’s what that looks like in practice. Say you want to know who’s winning Ground Coffee on Amazon.
You ask in plain English. Within seconds, you have a grounded answer: Amazon-as-seller owns roughly 60% of the category (about $242M), Black Rifle sits at #2 with $8.7M and +87% year over year, and the challenger PurityCoffee is up 150%. From there you keep going — “Why is Black Rifle gaining?” — and follow the thread into top keywords, top ASINs, and price-band moves. Half a minute in, you’re not staring at a CSV. You’re making a call on pricing, assortment, or ad spend, backed by the numbers you just saw.
The pattern is consistent no matter the question:
- Ask in plain English. Start with the business question, not a query.
- Get a data-grounded answer. The AI pulls the relevant Jungle Scout intelligence — share, growth, competitors, pricing, keywords, products, and brands.
- Investigate the drivers. Follow up on competitive moves, price-band performance, assortment gaps, search visibility, or new launches.
- Put the answer to work. Turn the finding into a briefing, QBR summary, scorecard, alert, or product recommendation.
Depth, not just speed
Fast answers are only useful if they hold up. Because Jungle Scout MCP draws on the breadth of Jungle Scout’s Amazon intelligence, it can support the kind of diagnosis that usually takes an analyst days.
Take a real example from the toy category. One of the hottest toy brands was celebrating 74% year-over-year Amazon revenue growth — a strong result on paper. But the broader category had grown 323% over the same period. That gap was the real story but they were lacking visibility into it.
Digging in revealed why the gap existed: the brand’s new products accounted for just 0.6% of revenue and had zero accumulated reviews. Competitor launches, by contrast, made up 36% of revenue and had already gathered nearly 1,400 reviews, giving them a stronger path to organic rank.
The conclusion wasn’t “lower your price.” It was a launch-execution problem. That is a diagnosis a team can actually act on, and Jungle Scout MCP surfaced it in a single conversation.
Built on a decade of Amazon data
None of this works without trustworthy data underneath it. Jungle Scout has spent more than ten years building one of the most comprehensive and accurate sources of Amazon marketplace intelligence, and Cobalt puts that intelligence in the hands of enterprise teams. Jungle Scout MCP simply extends it into the AI workflows those teams already use.
If you’re new to Jungle Scout, the MCP is the most direct way to tap into Amazon intelligence — just ask. If you’re already a Cobalt customer, it’s a faster, more flexible way to put the data you rely on to work.
What’s available today
The MCP gives your AI platform access to the full breadth of Jungle Scout data: market share and growth, top sellers and brands, product attributes, price-tier analysis, keyword volume, Share of Voice, and your own sales and ad performance.
On top of that, your AI platform unlocks live Q&A, pinned scorecards, scheduled briefings, cross-tool actions, and mobile access. More is coming — including review sentiment analysis and packaged agent skills built for common workflows.
It works across the platforms teams already standardize on — Claude, ChatGPT, Gemini Enterprise, and Microsoft Copilot — so there’s nothing new to learn.
Bring Amazon intelligence into your workflow
The teams that move fastest aren’t the ones with the most dashboards. They’re the ones that can get from a business question to a confident decision without losing a day in between.
If you’re already a Jungle Scout or Cobalt customer, talk to your customer success manager or account rep about getting access. If you’re not yet, request a demo and see what your AI can do once it speaks Amazon.
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