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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

Related MCP server: Amazon Marketplace MCP Server by CData

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:

# 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

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

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

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

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]?"

  2. 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?"

  3. 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"

  4. 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?"

  5. 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.

  2. 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

  3. Connection Errors: Ensure your Domo credentials are correct and the instance URL is properly formatted.

Development

To run in development mode:

npm run dev

To run tests:

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.

Available Tools

26 tools
smartscout_brand_coverageC

Get seller coverage information for brands

Inputs: brand, limit, sellerId, minRevenue.

smartscout_brand_detailsC

Get detailed information about a specific brand

Inputs: brand (required).

smartscout_brand_growthC

Find fastest growing brands

Inputs: limit, period, minRevenue.

smartscout_check_datasetsC

Check the status and indexing of SmartScout datasets

Inputs: dataset, attemptIndex.

smartscout_competitor_analysisC

Analyze competitors for a specific product or brand

Inputs: asin, brand, limit.

smartscout_custom_queryC

Execute a custom SQL query on SmartScout data (advanced users)

Inputs: sql (required), table (required).

smartscout_dataset_statusC

Check the status and accessibility of SmartScout datasets in Domo

Inputs: datasetId.

smartscout_keyword_brandsC

Get brands associated with search terms

Inputs: brand, limit, keyword.

smartscout_keyword_productsC

Get products ranking for a specific keyword (organic and paid)

Inputs: keyword (required), type, limit.

smartscout_list_datasetsB

List all configured SmartScout datasets with their IDs

Inputs: no named parameters.

smartscout_market_analysisC

Analyze market metrics for a category or subcategory

Inputs: brand, category, subcategory.

smartscout_opportunity_finderC

Find market opportunities based on various criteria

Inputs: type, limit, category, minRevenue.

smartscout_product_detailsB

Get detailed information about a specific product by ASIN

Inputs: asin (required).

smartscout_product_historyC

Get historical data for a product including price and sales rank changes

Inputs: asin (required), days.

smartscout_product_keywordsC

Get keywords that a product ranks for

Inputs: asin (required), type, limit, maxPosition.

smartscout_raw_api_testC

Test raw Domo API endpoint to verify connectivity

Inputs: endpoint.

smartscout_seller_detailsC

Get detailed information about a specific seller

Inputs: sellerId (required).

smartscout_seller_productsC

Get products sold by a specific seller

Inputs: sellerId (required), limit, minBuyBoxPercent.

smartscout_system_infoC

Get information about available SmartScout databases and their schemas

Inputs: database.

smartscout_test_queryC

Test a simple query against a specific dataset

Inputs: datasetName (required), query.

smartscout_top_productsC

Get top selling products in a category or subcategory

Inputs: brand, limit, category, subcategory.

smartscout_top_sellersC

Get top sellers by revenue or other metrics

Inputs: limit, metric, minRevenue.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    B3/5.0

    Scored across 26 tools

    Disambiguation4/5

    Most tools target clearly distinct resources or actions, but the Domo/dataset diagnostics overlap: smartscout_dataset_status and smartscout_check_datasets are nearly interchangeable, and smartscout_test_query overlaps with smartscout_custom_query and smartscout_raw_api_test.

    Naming Consistency5/5

    All tools use the same smartscout_ prefix and snake_case convention, with predictable entity/action phrasing. Minor noun-vs-verb differences do not break the consistent style.

    Tool Count2/5

    26 tools is above the comfortable range for this server, especially with six separate Domo/dataset diagnostics inflating the surface. The data-domain tools are broad, but the total set is heavy and likely over-scoped.

    Completeness4/5

    Core entities such as products, sellers, brands, keywords, and markets each have search, detail, and analysis coverage, and custom SQL provides an escape hatch. Some gaps remain, such as category listing or historical trends for sellers/brands, but the surface is largely complete.

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