DataDoe MCP

Paste the config below into your AI client (Claude, Cursor, Codex, Gemini, GitHub Copilot, ChatGPT, or any MCP-capable tool):

{ "mcpServers": { "datadoe": { "url": "https://mcp.datadoe.com/mcp/v1", "headers": { "datadoe-mcp-key": "<YOUR_DATADOE_MCP_KEY>" } } } }

Ask your AI agent:"Show my top 10 ASINs by revenue last month across all Amazon marketplaces."

That's it. DataDoe runs the MCP server on hosted infrastructure, so your team doesn't need to deploy anything locally or wait for Amazon SP-API developer approval.

DataDoe MCP gives your AI agent two layers over your Amazon account:

- A read layer- SKU-level orders, sales, ads spend, traffic, inventory, listings, returns, settlements, brand analytics, and catalog, returned as structured tool responses or downloadable CSV and JSON exports.
- A write layer (Actions)- your agent can change your Amazon account through the SP-API and Amazon Ads API: update listings, cancel orders, confirm shipments, and manage Amazon Ads campaigns, ad groups, targets, and ads.

Building your own Amazon SP-API integration typically requires SP-API developer registration, OAuth refresh-token flow, marketplace-specific endpoints, throttling logic, and 2-4 weeks of Amazon approval. DataDoe takes care of all of that. You get a single authenticated MCP URL for both reading and acting on your Amazon data.

- Amazon sellers (FBA, FBM, multi-marketplace)- get instant answers from your own seller data without context-switching to Seller Central.
- Amazon agenciesmanaging multiple client accounts - query across every connected Seller Central / Vendor Central account from one MCP server.
- Vendors with Vendor Central- read 1P data alongside 3P data with the same tools.
- AI builders and developers- ship Amazon-aware AI agents, dashboards, and internal tools without writing your own SP-API integration.
- Operations teams- automate recurring reports via Claude Code, Cursor, n8n, or any MCP-capable workflow tool.

Example questions your AI agent can answer with DataDoe MCP connected:

- "What were my top 20 ASINs by revenue last month across all Amazon marketplaces?"
- "Reconcile my Amazon settlements against orders for Q1, and show any discrepancies."
- "Which Amazon Ads campaigns had ACoS over 40% last week, and what was their total spend?"
- "Show inventory units at risk of stocking out in the next 14 days."
- "Build me a daily KPI dashboard with sales, traffic, and ad spend for the last 90 days."
- "Which search terms in my PPC reports drove the most clicks but zero conversions?"
- "Pull every Amazon return for SKU ABC-123 in the last 60 days and summarize the return reasons."
- "Compare my brand analytics search term share-of-voice month over month."

And withActionsenabled, your agent can act on what it finds:

- "Raise the daily budget on my top-ACoS Sponsored Products campaign by 20%."
- "Pause every campaign with ACoS over 50% last week."
- "Update the price of SKU ABC-123 to 19.99 and refresh its bullet points."
- "Confirm shipment for order 123-4567890-1234567 with UPS tracking 1Z999..."

Actions let your AI agent make changes on your connected Amazon Seller Central, Vendor Central, and Amazon Ads accounts through the SP-API and Amazon Ads API. Every Action is recorded and auditable.

- Listings- update the title, bullet points, description, price, generic keyword, and item-type keyword (AMAZON_LISTINGS_UPDATE).
- Orders- cancel an order item with a reason (AMAZON_ORDERS_CANCEL) or confirm shipment and upload tracking (AMAZON_ORDERS_CONFIRM_SHIPMENT).
- Amazon Ads- add, update, remove, and find campaigns, ad groups, targets, ads, and ad associations across Sponsored Products, Brands, Display, TV, and Amazon DSP.

How it works - the agent runs each Action through these MCP tools:
- actions_details_schema_get- get the payload schema for the Action type.
- actions_startwithdryRun=true- validate the payload without executing.
- actions_start- run the Action and get an action id.
- actions_get- poll until it completes, then read theresult.

Useactions_listto review past Actions (filter by status, type, creator, and date).

Exampledetailspayload forAMAZON_LISTINGS_UPDATE:

DataDoe MCP exposes the following tools to your AI client:

{ "mcpServers": { "datadoe": { "url": "https://mcp.datadoe.com/mcp/v1", "headers": { "datadoe-mcp-key": "<YOUR_DATADOE_MCP_KEY>" } } } }

claude mcp add datadoe \ --transport http \ --url https://mcp.datadoe.com/mcp/v1 \ --header "datadoe-mcp-key: <YOUR_DATADOE_MCP_KEY>"

Add to~/.cursor/mcp.json(global) or.cursor/mcp.json(per project):

{ "mcpServers": { "datadoe": { "url": "https://mcp.datadoe.com/mcp/v1", "headers": { "datadoe-mcp-key": "<YOUR_DATADOE_MCP_KEY>" } } } }

{ "mcpServers": { "datadoe": { "url": "https://mcp.datadoe.com/mcp/v1", "headers": { "datadoe-mcp-key": "<YOUR_DATADOE_MCP_KEY>" } } } }

Codex CLI · Gemini CLI · ChatGPT · n8n · NanoClaw · any other MCP client

DataDoe MCP works as ageneric remote MCP server. Configure your client with:

For step-by-step setup guides per AI client, see the dedicated DataDoe documentation pages:

DataDoe MCP exposes every Amazon data table available in DataDoe, including:

- Orders & sales: order line items, order performance, sales and traffic, refunds
- Amazon Ads: campaigns, ad groups, keywords, search terms, sponsored products / brands / display, ACoS / ROAS / impression-share metrics
- Inventory: FBA inventory, restock recommendations, stranded inventory, age, units at risk
- Listings & catalog: ASIN catalog, product attributes, buy box ownership, variations
- Finance: settlements, fees, reserves, reimbursements, deposits
- Returns: customer returns, return reasons, FBA returns
- Brand analytics: search query performance, market basket, repeat purchase, demographics
- Traffic: sessions, page views, conversion rate, by ASIN, by marketplace

To avoid confusion when evaluating Amazon MCP servers:

How to start and connect locally (for indexing and listing)

This compiles the TypeScript source intodist/index.js.

The server communicates over stdio, so the process is intended to be launched by your MCP client rather than opened in a browser.

For a local setup, point your client at the built entrypoint. A typicalmcp.jsonlooks like this:

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