Amazon MCP for sellers: your data in any AI assistant
MCP is the protocol. Nova MCP is the seller-side data model behind it. Claude, ChatGPT or Gemini answer profit, PPC and inventory questions in one call, on live Amazon data, across 21 marketplaces.
What is Amazon MCP?
Amazon MCP is the use of the Model Context Protocol to let an AI assistant query Amazon seller data directly. An MCP server exposes that data as tools the assistant calls inside a conversation. Amazon's own MCP server covers advertising. Nova MCP covers the whole business: SKU-level profit across 40+ fee types, Sponsored Products down to the search term, FBA and AWD inventory, listing health and BSR, in 21 marketplaces, refreshed hourly and read-only.
From fragmented Amazon APIs to any AI assistant, in one flow
Nova absorbs SP-API, Ads, and Reports complexity. Your AI reads one clean schema.
Amazon APIs
Fragmented, schema-shifting
We absorb the chaos so Your AI does not have to.

One schema, pre-modeled for AI
Sales & Profit
Advertising & Discoverability
Catalog & Inventory
Your AI
Reads Nova in one query. Returns profit, fees, ads, inventory answers in seconds.
What an Amazon MCP server actually is
MCP (Model Context Protocol) is the open standard for letting AI assistants call tools. An Amazon MCP server wraps Amazon data and exposes it as callable functions. Nova MCP is live today for Claude, ChatGPT, Gemini and any other MCP-ready client.
Amazon ships an official Ads MCP server. The community publishes SP-API wrappers. They all do the same thing: hand the AI a phone line to Amazon. What they do not hand it is a seller-grade data model.
That gap is the difference between "the assistant tried to compute my margin and timed out" and "the assistant told me the 5 SKUs that lost money this week and why."
Why "give the AI SP-API" rarely works
Token bills explode
8 to 20 tool calls per question, with pagination and retries. One question can burn dollars in tokens.
No profit model
SP-API returns orders, fees and settlements in different shapes. The AI tries to reconcile them in the prompt. It gets the answer wrong.
Schema fragility
Amazon ships breaking changes regularly. Every change breaks your AI workflows until someone patches the wrapper.
Amazon Ads MCP vs raw SP-API wrappers vs Nova MCP
Same assistant, same prompt, three very different context layers.
The tools Nova MCP exposes to your assistant
Nine read-only tools. Each one answers a class of seller question in a single call.
query_metricsAny metric over any period, grouped by SKU, ASIN, marketplace, account or a time grain. Ranking and thresholds run server side.
find_moversThe SKUs whose value moved most between a period and a baseline, in either direction. This is the 'what changed' tool.
explain_movementFor one SKU, the causal bundle: traffic, conversion, price, buy box, promotions, ads and rank versus a baseline.
query_advertisingSponsored Products at campaign, ad group, targeting type, keyword, attributed ASIN or SKU, plus any time grain. 13 KPIs per row.
query_search_termsThe customer queries behind the spend. Negative-keyword candidates and auto-campaign discoveries, on demand.
query_inventoryFBA and AWD stock health: available, inbound, reserved, sales velocity, days of inventory, out-of-stock risk.
query_listing_healthCurrent listing state: suppressed, removed, not buyable, buy box lost, hijackers, plus published catalog content and backend keywords.
query_bsrBest Seller Rank for your own ASINs, latest or as a time series, with the category and rank pair kept intact.
list_cost_inputsThe per-SKU COGS, merchant-fulfilment cost and VAT category you configured, so the assistant can audit your cost setup.
What sellers actually ask
Three real questions, and the tools behind each answer.
"Which keywords burned more than $100 with zero sales last month?"
One query_search_terms call with a spend threshold and a zero-sales filter. The answer comes back as a ranked table: query, campaign, match type, spend, clicks. That is a negative-keyword list, not a report.
"Which SKUs lost the most net profit versus last month, and why?"
find_movers ranks the losers, then explain_movement pulls the causal signals for the worst one: price change, buy box share, ad spend, conversion rate, rank.
"What runs out of stock in the next three weeks across all marketplaces?"
query_inventory sorted by days of inventory, with AWD stock counted in coverage. The assistant returns the reorder shortlist with velocity and projected cover.
Use both. MCP for actions. Nova for answers.
The smart stack pairs an MCP action layer with Nova as the read layer.
MCP action layer
Use Amazon's Ads MCP and SP-API wrappers to push changes: bid updates, listing edits, inbound creation.
Good at: writes, mutations, single-record actions.
Nova read layer
Point your AI at Nova for everything it needs to reason: profit, fees, ads efficiency, inventory risk, listing health, organic share.
Good at: analytics, planning, alerting, briefings, agents.
Live in 24 hours, not 24 weeks
Four steps from Amazon to your assistant via Nova MCP.
Connect Amazon
Auth your Seller Central and Ads accounts in Nova. 21 marketplaces supported.
Let Nova model it
Orders, settlements, 40+ fee types, ads and inventory are joined at SKU level and refreshed hourly.
Add the MCP endpoint
Point Claude, ChatGPT or Gemini at Nova MCP. Read-only, per-account credentials, revocable anytime.
Ask anything
Profit, wasted ad spend, stockout risk, suppressed listings. One question, one call.
About Amazon MCP for Sellers
Common questions about MCP, SP-API, and Nova as the seller read layer
Give your AI seller-grade Amazon data
Live in 24 hours. Profit-accurate. 21 marketplaces.