The Amazon Data Layer for Developers

Skip six months of Amazon API plumbing. Start building today.

Any AI you already use, plugged in (ChatGPT, Claude, Cursor, Copilot). Custom internal tools your team builds on top. Same reconciled Amazon data underneath all of it — replacing six SaaS subscriptions with one.

DataDoe gives developers a clean, structured data layer over Seller Central, Vendor Central and Amazon Ads — accessible through REST, MCP, or BigQuery on day one.
We handle auth, retries, rate limits, schema drift. You ship products.

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4 ways out
REST API, MCP, direct BigQuery and recurring exports.
40+ tables
Across Seller Central, Vendor Central and Amazon Ads.
OAuth
SP-API compliant. Encrypted at rest. One auth per Amazon account.
Live
Continuous sync on most feeds. Up to 735d backfill on connect.
Building from SP-API yourself

Six months. One dev. Forty-seven endpoints. All just to start the project.

OAuth + LWA flow per marketplace. Reports API is async — request, poll, download, parse. Settlement transactions reconciliation in SQL. Multi-region endpoints for NA/EU/FE. Rate limits everywhere. Then maintain it as Amazon ships breaking changes every quarter.

"Build internal margin tool on Amazon data."
→ Q4 sprint planning. Six months later, MVP ships.
Building on DataDoe

One auth. One schema. Every endpoint reconciled. Production-ready today.

OAuth each Amazon account once. Continuous sync runs in the background. Query 40+ canonical tables via REST API, MCP for AI agents, direct BigQuery, or pull recurring exports straight to your inbox.

"Build internal margin tool on Amazon data."
→ Connect Amazon. Hit the API. MVP shipped Friday.
Four ways to access the data

One schema.
Four access patterns.

DataDoe normalizes every Amazon data feed — Seller Central, Vendor Central, Advertising, Settlement, FBA, AWD — into one canonical schema. Pick the access pattern that fits your stack. Same data underneath.

  • APIREST API — versioned endpoints with JSON or CSV responses. Idiomatic HTTP, works with any backend, language or runtime that speaks it.
  • MCPMCP server — drop the connection into Claude, ChatGPT, Cursor, Codex, Copilot or Gemini CLI. Your AI assistant queries live Amazon data natively.
  • SQLDirect BigQuery — your tables mirrored into your BigQuery project, synced daily. Query with SQL, join with your own data, materialize to Looker, Hex, Metabase.
  • Recurring exports — schedule CSV, JSON, TSV, XML or Excel deliveries to your inbox or org-wide on a cron. No polling, no Reports API ceremony.
  • Initial load up to 735 days — backfill once on connect. Continuous fetch from there.
Pick one path. Pick all four. Same data, your stack.
REST APISynced live
Connect your application

JSON or CSV endpoints for backend services, automations, internal apps and serverless functions.

MCP serverSynced live
Add capabilities to your AI

Native MCP for Claude, ChatGPT, Cursor, Codex, Copilot and Gemini CLI. No middleware in between.

BigQuerySynced daily
Direct warehouse access

Your dataset, mirrored into your GCP project. Run SQL, join with internal data, plug into BI.

Recurring exportsOn schedule
Delivered on cron

CSV, JSON, TSV, XML or Excel files delivered to email recipients on the schedule you set.

What you can build

Three things devs ship on day one.

Same data across every path. Pick the workflow that fits your team — interactive queries, custom apps, or recurring exports feeding your warehouse and AI agents.

01

Query.

REST, SQL or MCP — your choice.

Hit the REST API from a serverless function. Run BigQuery SQL from Hex or Metabase. Drop the MCP connection into Claude or Cursor and query in plain English. Same data, three styles, all live.

  • REST endpoints from any backend
  • SQL straight in your warehouse
  • MCP from any AI client
  • Pre-aggregated KPIs and raw rows
For: data analysts, BI engineers, ad-hoc queries
02

Build.

Internal tools & customer apps.

Use the REST API in any codebase — TypeScript, Python, Go, anything that speaks HTTP. Ship internal margin dashboards, customer-facing apps, or agency-branded reporting.

  • Internal P&L & ops dashboards
  • Customer-facing white-label apps
  • Agency-branded reporting portals
  • Any HTTP client, any stack
For: in-house engineering, agency dev teams
03

Stream.

Continuous sync into your data stack.

Mirror tables into your BigQuery project. Schedule CSV, JSON or Excel exports on a cron. Feed your dbt models, Looker, Metabase or your own ML pipelines. No polling, no rate-limit handling.

  • BigQuery direct access
  • Recurring exports on schedule
  • Compatible with dbt, Looker, Hex
  • Per-Amazon-account scoping
For: data platform teams, ML engineers
Where the dev time is hiding

Six months of integration work, already done.

Building Amazon data infrastructure from SP-API takes months and never stops. Every problem below is solved before you write a line of code.

SP-API auth
2 – 4 wks
OAuth + LWA per marketplace
"Get tokens working across NA/EU/FE."

Login with Amazon, refresh token rotation, regional endpoints, multi-account selectors. We handle the entire OAuth flow. You get a single key.

Reports API
3 – 6 wks
async pipeline plumbing
"Pull settlement reports continuously."

Request → poll → download → decompress → parse → reconcile. Per report type. Per marketplace. We've built the pipeline once. You get live tables.

Reconciliation
2 – 3 mo
true profit math
"Match settlements to orders to fees."

FBA fees post days late. Returns offset weeks later. Promotions ripple across rows. Multi-currency. We've reconciled all of it. The settlements table just works.

Rate limits
Ongoing
retry, backoff, queue
"Don't get throttled at scale."

Per-endpoint limits, dynamic burst windows, regional differences, 429 handling. We run the queue against Amazon. You query our API instead.

Schema drift
Quarterly
Amazon ships breaking changes
"Don't break when SP-API changes."

Amazon adds fields, deprecates endpoints, changes formats. We absorb the changes upstream. Your queries against the canonical schema stay stable.

Multi-account onboarding
2 – 4 wks
per Amazon connection
"Onboard the Nth account in minutes."

Each Amazon account runs its own LWA OAuth flow under your workspace. Sellers and Vendors are scoped by ID. Encrypted at rest.

The schema

Every Amazon data feed.
One canonical schema.

40+ tables across Seller Central, Vendor Central, Advertising and AWD — reconciled, typed, BigQuery-compatible. Common keys (marketplace_id, child_asin, date) are normalized across every feed, so you join without aliasing twelve columns to make it work.

Settlements arrive with full P&L breakdown and COGS already matched. FBA inventory ships with sales velocity, age buckets and Amazon's own recommendations. Vendor side covers NPPM, demand forecasting with confidence levels, repeat purchase and market basket — the same data Brand Analytics shows, queryable.

One schema, four ways out: REST for services, MCP for AI agents, direct BigQuery for the data team, recurring exports for warehouse handoff.

Most-used tablesColumns
amazon_settlements_with_cogs91
amazon_fba_inventory_health91
amazon_ads_performance_by_campaign_by_date22
amazon_order_items_with_cogs37
amazon_seller_performance98
amazon_vendor_sales_traffic_and_inventory57
amazon_fba_reimbursements20
+ 30 more tables across SC, VC, AdsDocs
RESTMCPBigQueryExports
Who is it for

Teams that build on data

From a solo dev shipping an internal tool to a platform team running customer-facing infrastructure — DataDoe scales from one workspace to multi-account fleets.

EngineeringIn-house

In-house engineering teams

You're at an 8–9 figure brand with internal eng. Stop spending Q4 building SP-API plumbing. Use DataDoe as your Amazon data layer, ship internal margin dashboards and ops tools in days.

Replaced our six-month SP-API integration plan with their REST API. Two devs shipped the margin dashboard the same week.
PlatformAgency & SaaS

Platform & agency dev teams

Building customer-facing tools — agency portals, B2B SaaS, multi-brand operations. DataDoe runs OAuth and continuous sync for every Amazon account you connect. Ship without ever touching SP-API.

We ship Amazon-aware features in our SaaS without touching SP-API. Each new client connects, we query, the rest is product code.
DataBI & analytics

Data analysts & BI engineers

Skip the ETL. DataDoe mirrors directly into your BigQuery project — reconciled, typed, ready for dbt, Looker, Hex, Metabase. Or query the REST API straight from your notebook. Analyst hours back, infrastructure work gone.

First time we got Amazon settlement data into BigQuery without a custom Airflow DAG. dbt models built on top in two days.
The math

From a six-month sprint
to a single connection.

Building Amazon data infrastructure in-house means a senior dev for 4–6 months minimum, plus ongoing maintenance as Amazon ships breaking changes every quarter. Multi-marketplace and multi-account double the timeline.

DataDoe replaces the data layer underneath. The same endpoints, the same reconciled schemas, the same OAuth per Amazon connection — exposed as REST, MCP, BigQuery and recurring exports. You write product code, not SP-API plumbing.

SP-API integration build4 – 6 months
Settlement & COGS reconciliation2 – 3 months
Multi-marketplace plumbing+50% to all
Per-account OAuth + sync2 – 4 weeks
Ongoing breaking-change patchingEvery quarter
Data team ETL setup2 – 4 weeks
↓ One layer instead ↓
REST · MCP · BigQuery · ExportsOne canonical schema · 40+ tables

FAQ

What does DataDoe expose to developers?
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Can I plug DataDoe into our existing internal data stack?
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How do we connect multiple Amazon accounts?
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Which programming languages and stacks are supported?
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Is DataDoe compliant with Amazon's SP-API terms?
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How fresh is the data?
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Can our analysts run their own SQL on the data?
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Do you support Vendor Central as well as Seller Central?
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What happens when Amazon ships breaking SP-API changes?
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What if we want to stop using DataDoe later?
Faq Plus

Set up in under 5 minutes.
Try free for 14 days. Then $97/month.

Every integration. Full onboarding support. If it’s not the best decision you made in 2026, you can cancel anytime.

GET STARTED FOR FREEBook a demo

Skip six months of SP-API integration

Hands-on onboarding by the build team

Connect anything with API & MCP

Replace SaaS tools with your own apps

Access Amazon-audited infrastructure

Set up in under
5 minutes.
Try free for 7 days. Then $97/month.

Every integration. Full onboarding support. If it’s not the best decision you made in 2026, you can cancel anytime.

GET STARTED FOR FREEBook a demo