Server data from the Official MCP Registry
Hosted Amazon Seller and Vendor MCP server for Claude, ChatGPT, Cursor, Codex, Gemini, Copilot.
Hosted Amazon Seller and Vendor MCP server for Claude, ChatGPT, Cursor, Codex, Gemini, Copilot.
Remote endpoints: streamable-http: https://mcp.datadoe.com/mcp/v1
Valid MCP server (1 strong, 1 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry.
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Remote Plugin
No local installation needed. Your AI client connects to the remote endpoint directly.
Add this to your MCP configuration to connect:
{
"mcpServers": {
"com-datadoe-amazon-seller-mcp": {
"url": "https://mcp.datadoe.com/mcp/v1"
}
}
}From the project's GitHub README.
Hosted Amazon Seller Central & Vendor Central MCP server. Connect Claude, ChatGPT, Cursor, Codex, Gemini, and GitHub Copilot to live Amazon SP-API and Amazon Ads API data. DataDoe handles the SP-API developer approval, OAuth, and rate limits so your AI agent starts querying in under a minute.
š Start a free trial Ā· š Documentation Ā· š Amazon data schema Ā· š„ Video demo
Sign up at DataDoe and connect your Amazon Seller Central or Vendor Central account.
Create a DataDoe MCP API key in DataDoe MCP Integrations.
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 is a hosted Model Context Protocol (MCP) server for Amazon sellers, vendors, and agencies. It exposes your live Amazon Selling Partner API (SP-API) and Amazon Ads API data through MCP tools that work with Claude, ChatGPT, Cursor, Codex CLI, Gemini CLI, GitHub Copilot, Claude Desktop, n8n, NanoClaw, and any other MCP-capable client.
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, and SKU-level Amazon data - orders, sales, ads spend, traffic, inventory, listings, returns, settlements, brand analytics, catalog - comes back as structured tool responses or downloadable CSV and JSON exports.

exports_create accepts SQL-like filter groups, GROUP BY, aggregations, and date intervals, so your AI agent can build complex reports from one tool call.Example questions your AI agent can answer with DataDoe MCP connected:
DataDoe MCP exposes the following tools to your AI client:
| Tool | Category | What it does |
|---|---|---|
sellers_and_vendors_list | Account | Lists every Amazon Seller Central and Vendor Central account connected to your DataDoe organization, with marketplace, region, and Amazon Ads account info. |
organization_and_subscription_details_get | Account | Returns your DataDoe organization profile and active subscription plan. |
exports_sources_get | Data | Searches DataDoe's catalog of pre-built Amazon data export templates (orders, sales and traffic, ads performance, inventory, listings, settlements, returns, brand analytics, and more). |
exports_create | Data | Creates an Amazon data export from any source. Supports SQL-like filters, GROUP BY, aggregations (sum / avg / count / countDistinct / min / max), date intervals (DAY / WEEK / MONTH), pagination, and CSV or JSON output. |
exports_get | Data | Returns status and metadata for an in-flight or completed export job. |
exports_raw_url_get | Data | Returns a one-time presigned download URL for a completed export. |
exports_raw_download | Data | Returns the raw export content (CSV or JSON) inline in the tool response. |
datadoe_user_docs_table_of_contents_get | Docs | Returns the table of contents of the DataDoe user documentation, useful when an agent needs to look up features or capabilities on demand. |
datadoe_user_docs_page_get | Docs | Returns the full content of a named DataDoe documentation page. |
The snippets below are the minimum config you need. For step-by-step guides per AI client, see the Per-client setup guides list at the end of this section.
{
"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>"
}
}
}
}
Add to your VS Code mcp.json:
{
"mcpServers": {
"datadoe": {
"url": "https://mcp.datadoe.com/mcp/v1",
"headers": {
"datadoe-mcp-key": "<YOUR_DATADOE_MCP_KEY>"
}
}
}
}
DataDoe MCP works as a generic remote MCP server. Configure your client with:
https://mcp.datadoe.com/mcp/v1datadoe-mcp-key: <YOUR_DATADOE_MCP_KEY> (create a key in DataDoe MCP Integrations)For step-by-step setup guides per AI client, see the dedicated DataDoe documentation pages:
Full documentation root: app.datadoe.com/hub/docs
DataDoe MCP exposes every Amazon data table available in DataDoe, including:
Full schema: app.datadoe.com/hub/data-scheme
To avoid confusion when evaluating Amazon MCP servers:
mcp.datadoe.com. This GitHub repository is the schema facade used to publish DataDoe MCP to public MCP registries (Official MCP Registry, mcpservers.org, glama.ai, mcpmarket.com, Cline, smithery.ai, and others).MIT. The DataDoe MCP schema facade in this repository is open-source. The hosted MCP server, DataDoe application, and DataDoe infrastructure are proprietary and operated by Deltologic.
This server is just a schema facade of the actual DataDoe MCP server, made for exposing DataDoe MCP to various MCP registries. It is a no-op server: it does not do anything beyond exposing the schema of DataDoe MCP. If you want to actually use DataDoe MCP, see the DataDoe MCP documentation.
yarn install
yarn build
This compiles the TypeScript source into dist/index.js.
yarn start
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 typical mcp.json looks like this:
{
"mcpServers": {
"datadoe": {
"command": "node",
"args": ["/absolute/path/to/datadoe-mcp/dist/index.js"]
}
}
}
If your client supports environment-based workspace paths, you can usually swap the absolute path for the actual clone location on your machine.
DataDoe is operated by Deltologic Ā· datadoe.com
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