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Works with

Claude CodeClaude DesktopCursorVS CodeClineCodex CLIOpenClaw+ any MCP client

Install to Claude Code

This server doesn't publish a one-line install command. Follow the setup in the source repository.

Summary

An MCP server that provides Claude Desktop access to SmartScout's Amazon marketplace intelligence data stored in Domo.

README.md

SmartScout Domo MCP Server

An MCP (Model Context Protocol) server that provides Claude Desktop access to SmartScout's Amazon marketplace intelligence data stored in Domo.

Overview

This MCP server enables Claude to query SmartScout's comprehensive Amazon marketplace database, including:

  • 16M+ products with pricing, sales, and ranking data
  • 350K+ brands with performance metrics
  • 374K+ sellers with revenue and feedback data
  • 10M+ search terms with volume and CPC estimates
  • Historical data for trend analysis
  • Organic and paid search rankings

Installation

  1. Clone this repository:
git clone https://github.com/smartscout/mcp-smartscout-domo.git
cd mcp-smartscout-domo
  1. Install dependencies:
npm install
  1. Create a .env file from the example:
cp .env.example .env
  1. Update .env with your credentials:
DOMO_INSTANCE=your-instance
DOMO_ACCESS_TOKEN=your-access-token
  1. Build the project:
npm run build

Configuration for Claude Desktop

Add the following to your Claude Desktop configuration file:

Windows: %APPDATA%\Claude\claude_desktop_config.json macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "smartscout-domo": {
      "command": "node",
      "args": ["C:/Users/Aeciu/OneDrive/Desktop/Smartscout/mcp-smartscout-domo/dist/server.js"],
      "env": {
        "DOMO_INSTANCE": "recommercebrands",
        "DOMO_ACCESS_TOKEN": "DDCIa8d82cba537ecf54032551681695985167811ebb95a8ea02"
      }
    }
  }
}

Deployment to Railway (Public HTTP API)

This server can now be deployed to Railway as a public HTTP API:

1. Push to GitHub

git add .
git commit -m "Add HTTP wrapper for Railway deployment"
git push origin main

2. Deploy to Railway

  1. Create account at railway.app
  2. Create new project → "Deploy from GitHub repo"
  3. Select your repository
  4. Add environment variables in Railway dashboard:
  • DOMO_INSTANCE - Your Domo instance
  • DOMO_ACCESS_TOKEN - Your Domo access token
  • API_KEYS - Comma-separated API keys (e.g., key1,key2,key3)
  • CORS_ORIGINS - Allowed origins (e.g., https://yourdomain.com)

3. Access Your API

Once deployed, Railway will provide a URL like https://your-app.railway.app

Test the deployment: ```bash

Health check

curl https://your-app.railway.app/health

List tools (requires API key)

curl -X POST https://your-app.railway.app/mcp \ -H "Authorization: Bearer YOUR_API_KEY" \ -H "Content-Type: application/json" \ -d '{"jsonrpc":"2.0","method":"tools/list","params":{},"id":1}' ```

See API.md for full API documentation.

Available Tools

Product Tools

smartscout_product_search

Search for products by various criteria. `` Example: Find products with "coffee maker" in title, priced $50-200, with 100+ reviews ``

smartscout_product_details

Get detailed information about a specific product including sellers. `` Example: Get full details for ASIN B08N5WLMXB ``

smartscout_product_history

Get historical price and sales rank data for a product. `` Example: Show 30-day history for ASIN B08N5WLMXB ``

smartscout_top_products

Find top-selling products in categories. `` Example: Top 20 products in "Home & Kitchen" category ``

Brand Tools

smartscout_brand_search

Search brands by name or performance metrics. `` Example: Brands with >$100K monthly revenue and 30%+ growth ``

smartscout_brand_details

Get comprehensive brand information including top products and sellers. `` Example: Full analysis of brand "Anker" ``

smartscout_brand_coverage

Analyze seller coverage for brands. `` Example: Which sellers carry Nike products ``

smartscout_brand_growth

Find fastest-growing brands. `` Example: Top 20 fastest growing brands with >$50K revenue ``

Seller Tools

smartscout_seller_search

Search sellers by name, ID, or metrics. `` Example: Sellers with >$500K monthly revenue and 95%+ positive feedback ``

smartscout_seller_details

Get detailed seller profile with products and brands. `` Example: Full profile for seller ID A2VJCB1F3Q7JZX ``

smartscout_seller_products

List all products sold by a specific seller. `` Example: Products from seller A2VJCB1F3Q7JZX with >50% buy box ``

smartscout_top_sellers

Find top sellers by various metrics. `` Example: Top 20 sellers by 30-day revenue growth ``

Search/Keyword Tools

smartscout_keyword_search

Find keywords with search volume and CPC data. `` Example: Keywords containing "wireless" with >10K monthly searches ``

smartscout_keyword_products

Get products ranking for a specific keyword. `` Example: Top organic and paid results for "bluetooth speaker" ``

smartscout_product_keywords

Find keywords that a product ranks for. `` Example: All keywords where ASIN B08N5WLMXB ranks in top 50 ``

smartscout_keyword_brands

Analyze brand presence for keywords. `` Example: Which brands dominate "coffee maker" searches ``

Analytics Tools

smartscout_market_analysis

Comprehensive market analysis for categories. `` Example: Full market analysis for "Pet Supplies" category ``

smartscout_competitor_analysis

Find and analyze competitors. `` Example: Find competitors for ASIN B08N5WLMXB ``

smartscout_opportunity_finder

Discover market opportunities. `` Example: Find low-competition subcategories with >$50K revenue ``

smartscout_custom_query

Execute custom SQL queries (SELECT only). `` Example: SELECT * FROM PRODUCTS WHERE BRAND = 'Apple' LIMIT 10 ``

smartscout_system_info

Get information about available databases and schemas. `` Example: Show schema for products database ``

Example Queries in Claude

Here are some example prompts you can use with Claude:

  1. Product Research:
  • "Find the top 10 best-selling yoga mats under $50"
  • "Show me the price history for ASIN B08N5WLMXB over the last 30 days"
  • "What products are competing with [ASIN]?"
  1. Brand Analysis:
  • "Which brands are growing fastest in the Home & Kitchen category?"
  • "Give me a full analysis of the Anker brand"
  • "Which sellers have the most revenue from Nike products?"
  1. Seller Intelligence:
  • "Find the top sellers in Pet Supplies with over 95% positive feedback"
  • "What products does seller A2VJCB1F3Q7JZX sell?"
  • "Show me sellers with the highest 30-day revenue growth"
  1. Keyword Research:
  • "What are the top keywords for wireless headphones?"
  • "Which products rank #1 organically for 'coffee maker'?"
  • "What keywords does ASIN B08N5WLMXB rank for?"
  1. Market Opportunities:
  • "Find low-competition subcategories in Sports & Outdoors"
  • "Show me high-revenue products with ratings under 3.5 stars"
  • "What subcategories have the largest price gaps?"

Token Management

The server automatically limits results to prevent token overflow:

  • Default limit: 100 results per query
  • Maximum limit: 1000 results
  • Results include a count and truncation notice when applicable
  • Complex queries return summarized data

Database Schema

The server provides access to these SmartScout databases:

  • PRODUCTS: Product catalog (16.1M rows)
  • BRANDS: Brand performance (350K rows)
  • SELLERS: Seller profiles (374K rows)
  • SEARCHTERMS: Keyword data (10.5M rows)
  • SELLERPRODUCTS: Seller-product relationships (17.7M rows)
  • BRANDCOVERAGES: Brand-seller relationships (997K rows)
  • PRODUCTHISTORIES: Historical product data (1.2B rows)
  • And more...

Use smartscout_system_info to explore available databases and their schemas.

Query Approach

This MCP server uses Domo's SQL query API. Key points about how queries work:

  1. Dataset Selection: Each tool targets a specific dataset ID, and queries use FROM dataset syntax
  2. Single Dataset Queries: Due to Domo API design, each query operates on one dataset at a time
  3. Column Names: All queries use the actual column names from the SmartScout schema (e.g., ASIN, MONTHLYSALES)

Troubleshooting

Common Issues

  1. Rate Limiting: The server handles Domo API rate limits automatically. If you encounter rate limit errors, wait a moment before retrying.
  1. Large Result Sets: If queries return too much data, try:
  • Adding more specific filters
  • Reducing the limit parameter
  • Using aggregation queries instead of raw data
  1. Connection Errors: Ensure your Domo credentials are correct and the instance URL is properly formatted.

Development

To run in development mode: ``bash npm run dev ``

To run tests: ``bash npm test ``

Security

  • API credentials are stored in environment variables
  • Only SELECT queries are allowed in custom SQL
  • All user inputs are sanitized to prevent SQL injection
  • Token limits prevent data exfiltration

Support

For issues or questions:

License

Copyright (c) 2024 SmartScout. All rights reserved.

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