Amazon knowledge retrieval MCP server (Amazon Agent Atlas)

io.github.KuudoAI由 GitHub 账号 KuudoAI 发布v1.0.0更新于 Oct 24, 2026

MCP retrieval server for indexed Amazon Ads, Seller Central, and Vendor Central knowledge.

发布方自己的服务：Red Atlas Api

已验证Streamable HTTP可网页运行知识与记忆商业与电商

服务详情

标识符: io.github.KuudoAI/amazon-agent-atlas-mcp
传输: Streamable HTTP
运行时: Web executable
信任: Verified
发布于: Sep 16, 2026

安全提示

MCP 服务会接收对话中的工具调用请求，并可能执行外部操作。启用前请先了解该服务能做什么，并只授予它所需的权限。

注册中心已验证此条目所属的 GitHub 账号 KuudoAI。这并不表明该账号就是产品方。

SourceWeft 的检查只涵盖条目是否完整、端点是否响应；不审查服务器的代码，也不审查其工具的行为。

在 README 中添加徽章

向读者展示该 MCP 服务已收录于 SourceWeft，徽章链接到本页。

[![Listed on SourceWeft](https://sourceweft.com/badge/mcp/io.github.KuudoAI%2Famazon-agent-atlas-mcp.svg)](https://sourceweft.com/mcp/io.github.KuudoAI%2Famazon-agent-atlas-mcp?utm_source=readme&utm_medium=badge)

概览

AI 生成的概览

远程 MCP 检索层，让助手浏览、搜索并调用已索引的 Amazon Ads、Seller Central 与 Vendor Central 知识工具。

可以做什么: 按标签或查询浏览和搜索工具目录，结果按相关度排序
读取指定工具的参数结构，便于正确调用
在一个沙箱 Python 代码块中串联多次工具调用并返回最终结果
通过仅含目录的本地存根查看工具列表、目录资源与连接提示
适用场景: 适合在回答前需要基于 Amazon Ads、Seller Central 与 Vendor Central 运营知识做检索的场景，且你已在自己的云环境中运行 Kuudo 部署。
运行要求: 需要你自己的 Kuudo 部署提供的远程 streamable HTTP 端点，以及携带 Kuudo API 密钥或部署 bearer 令牌的 Authorization 请求头。部分工具可能另有自己的服务商凭据。公开仓库只是目录存根，实际执行发生在你的部署中。

安装前请注意

Authorization 请求头中携带 Kuudo API 密钥或 bearer 令牌，应视为机密。execute 工具被标记为写入类工具，在带时间、内存和导入限制的沙箱中运行 Python。各工具的服务商凭据与上述 bearer 相互独立。服务器源码未公开，公开存根只返回错误而非真实 Amazon 数据。

安装

在 SourceWeft 中

打开控制台中的 Amazon knowledge retrieval MCP server (Amazon Agent Atlas)，将其添加到工作区。
为需要使用其工具的对话启用该服务。

Web executable，通过 Streamable HTTP。远程服务在工作区中配置后即可从网页运行时运行。

其他 MCP 客户端

参照仓库中的启动说明。

README

Amazon knowledge retrieval MCP server (Amazon Agent Atlas) by Kuudo

A retrieval layer your agent checks before it answers. It indexes Amazon operating knowledge across Ads, Seller Central, and Vendor Central.

[MCP] [Registry] [License: MIT] [Community]

Product page: https://www.kuudo.com/features/agent-atlas/ · Docs: https://www.kuudo.com/docs/amazon-agent-atlas/ · Pricing: https://www.kuudo.com/pricing.md

Connect

Kuudo runs in your own cloud. The Community plan deploys one instance of each Amazon MCP server into your account, and your client connects to that deployment:

json

{  "mcpServers": {    "amazon-agent-atlas-mcp": {      "url": "https://<your-host>/mcp",      "headers": {        "Authorization": "Bearer <your Kuudo API key>"      }    }  }}

{  "mcpServers": {    "amazon-agent-atlas-mcp": {      "url": "https://<your-host>/mcp",      "headers": {        "Authorization": "Bearer <your Kuudo API key>"      }    }  }}

Replace <your-host> with the hostname of your deployment and the bearer value with your Kuudo API key.

A tool may document a provider credential of its own. That is separate from the bearer above, it belongs to the service the tool calls, and the tool's own entry says so.

What this repository is

This repository holds registry metadata and a catalog-only stub. Live execution runs in your Kuudo deployment. The server source is not published. The stub in src/ answers tools/list with the catalog below, serves the same catalog as one resource (kuudo://catalog/tools.json), offers one prompt (connect) carrying the setup guidance, and returns an error with that guidance on any call, so registries and clients can inspect the surface without any access to Amazon.

Inspect the catalog locally with Docker

The image runs the same catalog-only stub over stdio. It is not the live server.

Point a client at it with a stdio entry:

json

{  "mcpServers": {    "amazon-agent-atlas-mcp-catalog": {      "command": "docker",      "args": ["run", "-i", "--rm", "amazon-agent-atlas-mcp"]    }  }}

{  "mcpServers": {    "amazon-agent-atlas-mcp-catalog": {      "command": "docker",      "args": ["run", "-i", "--rm", "amazon-agent-atlas-mcp"]    }  }}

Tools

4 tools, read from a running instance of this server. Four tools front the whole corpus: browse tags, search, read a schema, then run a chained call.

Each tool carries the argument schema the live server publishes, so a client can inspect the full call signature here before it connects to your deployment.

Every tool (4)

Tool	Access	What it does
`tags`	read	List available tool tags. Use to browse available tools by tag before searching.
`search`	read	Search for available tools by query. Returns matching tools ranked by relevance.
`get_schema`	read	Get parameter schemas for specific tools. Use after searching to get the detail needed to call a tool.
`execute`	write	Chain `await call_tool(...)` calls in one Python block and return the final value. Only `call_tool(tool_name: str, params: dict) -> Any` is available as an external function. Supported imports: asyncio, datetime, json, math, os, pathlib, re, sys, typing. Other standard-library and third-party imports, including collections, are unavailable in the sandbox. Use f-strings because str.format is unavailable. Limits: 10 seconds, 50,000,000 bytes of memory, and recursion depth 100.

Set up your client

Reads, writes, approvals

Read tools are safe to call freely. Write tools do work inside your deployment and never change anything on Amazon. Each tool's access is recorded beside it in tools.json.