mansournorouzi/amazon-sp-mcp

Description and use

**Brief Summary (2‑3 sentences)**
mansournorouzi/amazon-sp-mcp is an open‑source MCP (Model Context Protocol) server that bridges Claude‑style AI assistants with Amazon’s Selling Partner API. It provides LWA‑only authentication—so no AWS credentials are needed—and exposes endpoints for sales, inventory, orders, fees, and analytics, enabling AI agents to query real‑time Seller Central data through a standard protocol.

**Value**

• **Standardised AI‑to‑tool integration** – By wrapping the Amazon SP‑API in an MCP server, developers can connect any MCP‑compatible AI (e.g., Claude, ChatGPT plugins) without writing custom adapters for each endpoint.
• **Zero‑AWS‑credential hassle** – LWA‑only auth removes the need to manage long‑lived AWS keys, simplifying security and compliance for teams that only need read‑only access to seller data.
• **Rich e‑commerce data** – Sales, inventory, order status, fees, and analytics become directly consumable by LLMs, unlocking use‑cases such as automated reporting, inventory forecasting, and conversational order management.

**Practical Adoption Path**

1. **Spin up the server** – Clone the repo, run npm install && npm run build && npm start (Docker image also available).
2. **Configure LWA credentials** – Supply the client ID/secret and refresh token for the Amazon seller account in the .env file.
3. **Register the MCP endpoint** – Point your AI platform (Claude, LangChain, etc.) to the server’s /mcp endpoint and declare the supported methods (e.g., listOrders, getInventory).
4. **Develop prompts / agents** – Use the MCP schema to call the exposed methods from your LLM prompts or agent logic, treating the Amazon data as a native tool.
5. **Iterate & monitor** – Leverage built‑in logging and health checks; add caching or rate‑limit handling as needed for production traffic.

**Production Readiness**

• **Activity & community** – 38 stars, 8 forks, recent commits (as of 2026‑06‑30), and a TypeScript codebase with clear module boundaries indicate an actively maintained project.
• **Security posture** – Uses LWA (OAuth2) only, eliminating the need to store AWS secret keys; however, a final security audit of the token handling and exposed endpoints is recommended.
• **Scalability** – The server is stateless and can be containerised; horizontal scaling is straightforward with standard Node/TS deployment patterns.
• **Ecosystem fit** – Aligns with the emerging Model Context Protocol ecosystem, making it a solid candidate for pilots that need a “real‑world” data source for AI agents.

Overall, mansournorouzi/amazon-sp-mcp offers a low‑friction, standards‑based bridge between Amazon seller data and LLM‑driven agents, and its recent activity, clear architecture, and simple auth model make it ready for serious pilot deployments, pending a final security and licensing review.

Use in a workflow

mansournorouzi/amazon-sp-mcp helps connect AI assistants to real tools and data through a standard protocol.

• connect AI agents to tools
• ship Model Context Protocol servers
• standardize integrations

Limitations and review notes

High for an OSS candidate: recent activity, adoption, and ecosystem signals are strong enough for a serious pilot.