Catalog CLI

PyPI version

Agent-native Amazon catalog auditing tool

The first AI-agent-friendly Amazon catalog analysis tool. Query your CLRs with structured input, integrate via MCP server, and automate catalog audits.

Hosted API available at api.catalogcli.com — persistent storage, unlimited scans, and API access for $9.99/mo. Learn more

What's New in v2.3

• Seller Central AJAX lookup - Fetch Amazon's live Seller Central listing JSON with catalog listing fetch <asin>
• Live listing vs CLR diff - Compare Amazon's current listing fields against your Category Listing Report with catalog listing diff <asin> <clr-file>
• Agent-ready Seller Central tools - New MCP tools catalog_seller_listing_fetch and catalog_seller_listing_diff
• Local cookie auth - Use --cookie, --cookie-file, or CATALOG_SELLER_CENTRAL_COOKIE; Seller Central cookies stay local

v2.2 Title Readiness

• Amazon title readiness - mobile-title-readiness flags titles over 75 characters for Amazon's mobile title update
• Rewrite-ready output - Returns first-75-character title segments, overflow text, significant terms, item highlight status, and recommended next actions
• Agent workflow friendly - Aliases title-75 and amazon-title-75 make it easy to call from Claude, MCP clients, and automation workflows
• 14 built-in checks - Adds a title triage workflow while keeping the classic 200-character long-titles check unchanged

v2.0 Agent Foundations

• Shared core architecture - Business logic separated into catalog/core/, powering both CLI and MCP
• MCP server - catalog mcp launches a stdio MCP server with 4 tools, ready for Claude Desktop and any MCP client
• JSON input - --json and --stdin flags for structured agent input
• Schema introspection - catalog schema --format json returns full request/response schemas
• Field masks - --fields sku,severity,details to reduce output size
• Pagination - --limit and --offset for controlling result size
• NDJSON streaming - --format ndjson for line-by-line streaming of large results
• Input hardening - Pydantic validation rejects path traversal, injection, and malformed input
• Environment variables - CATALOG_CLI_DEFAULT_FORMAT=json for headless/CI use
• Backward compatible - All v1.x commands work unchanged

Features

• Agent-Native - CLI + MCP server as equal citizens, JSON/NDJSON output, schema introspection
• Fast - Query 1000+ SKU catalogs in seconds
• Extensible - Plugin system for custom queries
• Comprehensive - 14 built-in catalog health checks
• Intent Optimized - COSMO-inspired shopper intent coverage for bullets

Installation

pip install amazon-catalog-cli

Or install from source:

git clone https://github.com/BWB03/amazon-catalog-cli.git
cd amazon-catalog-cli
pip install -e .

Quick Start

For Humans

# Run all catalog checks
catalog scan my-catalog.xlsx

# Detailed results
catalog scan my-catalog.xlsx --show-details

# Run specific check
catalog check intent-bullets my-catalog.xlsx

# Audit titles for Amazon's 75-character mobile title update
catalog check mobile-title-readiness my-catalog.xlsx

# List available queries
catalog list-queries

For AI Agents

# JSON output with field mask and limit
catalog scan my-catalog.xlsx --format json --fields sku,severity,details --limit 20

# Title rewrite triage for agents
catalog check mobile-title-readiness my-catalog.xlsx --format json \
  --fields sku,details,title_char_count,mobile_visible_title,overflow_title,all_significant_terms

# Structured JSON input
catalog scan --json '{"file": "my-catalog.xlsx", "queries": ["missing-attributes"], "limit": 10}'

# Piped input
echo '{"file": "my-catalog.xlsx"}' | catalog scan --stdin --format json

# NDJSON streaming for large results
catalog scan my-catalog.xlsx --format ndjson

# Schema introspection (discover queries, params, response shapes)
catalog schema --format json

# Fetch live Seller Central listing JSON for an ASIN
CATALOG_SELLER_CENTRAL_COOKIE='session-id=...' catalog listing fetch B000TEST01 --format json

# Compare live Seller Central JSON with a CLR row
catalog listing diff B000TEST01 my-catalog.xlsx --sku SKU-123 --format json

MCP Server (for Claude Desktop, CLR Pro, etc.)

# Start MCP server
catalog mcp

Add to Claude Desktop config:

{
  "mcpServers": {
    "catalog": {
      "command": "catalog",
      "args": ["mcp"]
    }
  }
}

MCP tools: catalog_scan, catalog_scan_summary, catalog_check, catalog_seller_listing_fetch, catalog_seller_listing_diff, catalog_list_queries, catalog_schema

Available Queries

Attribute Audits

• missing-attributes - Find mandatory attributes missing from listings
• missing-any-attributes - Find all missing attributes (required + conditional)
• new-attributes - Find unused template fields that might add value

Content Quality

• intent-bullets - Score bullet points against shopper intent coverage
• bullet-prohibited-content - Find bullet points with prohibited chars, emojis, claims, or placeholders
• bullet-formatting - Check bullet formatting (capitalization, length, punctuation)
• bullet-awareness - Soft violations in bullets (excessive caps, problematic chars)
• mobile-title-readiness - Find titles over 75 characters and prepare rewrite inputs
• long-titles - Find titles exceeding 200 characters
• title-prohibited-chars - Find titles with prohibited characters
• prohibited-chars - Find prohibited characters in title/brand

Catalog Structure

• product-type-mismatch - Find mismatched product types and item keywords
• missing-variations - Find products that should be variations but aren't

CLI Commands

catalog scan

Run all queries on a CLR file.

catalog scan <clr-file> [OPTIONS]

Options:
  --format [terminal|json|csv|ndjson]  Output format (default: terminal)
  --output PATH                        Output file path
  --show-details / --no-details        Show detailed results
  --include-fbm-duplicates             Legacy: include repeated exact-SKU rows
  --json TEXT                          JSON request body
  --stdin                              Read JSON request from stdin
  --queries TEXT                       Comma-separated query names
  --fields TEXT                        Comma-separated field mask
  --limit INTEGER                      Max issues to return
  --offset INTEGER                     Skip first N issues

catalog check

Run a specific query.

catalog check <query-name> <clr-file> [OPTIONS]

Options:
  --format [terminal|json|csv|ndjson]  Output format (default: terminal)
  --output PATH                        Output file path
  --show-details / --no-details        Show detailed results
  --json TEXT                          JSON request body
  --stdin                              Read JSON request from stdin
  --fields TEXT                        Comma-separated field mask
  --limit INTEGER                      Max issues to return
  --offset INTEGER                     Skip first N issues

catalog listing fetch

Fetch Amazon's live Seller Central listing JSON for an ASIN.

Requires a logged-in Seller Central cookie from your own browser session. Pass it with --cookie, --cookie-file, or the CATALOG_SELLER_CENTRAL_COOKIE environment variable.

catalog listing fetch <asin> [OPTIONS]

Options:
  --format [terminal|json]  Output format (default: terminal)
  --output PATH             Output file path
  --cookie TEXT             Seller Central Cookie header value
  --cookie-file PATH        File containing the Cookie header value
  --timeout FLOAT           HTTP timeout in seconds
  --json TEXT               JSON request body
  --stdin                   Read JSON request from stdin

catalog listing diff

Compare Amazon's live Seller Central listing JSON with a matching CLR row.

Rows match by --sku when provided. Otherwise Catalog CLI looks for Product Id Type = ASIN and Product Id = <asin> in the CLR.

catalog listing diff <asin> <clr-file> [OPTIONS]

Options:
  --sku TEXT                Optional SKU to match in the CLR
  --format [terminal|json]  Output format (default: terminal)
  --output PATH             Output file path
  --cookie TEXT             Seller Central Cookie header value
  --cookie-file PATH        File containing the Cookie header value
  --timeout FLOAT           HTTP timeout in seconds
  --json TEXT               JSON request body
  --stdin                   Read JSON request from stdin

catalog schema

Show schema for queries, params, and response shapes.

catalog schema [query-name] [OPTIONS]

Options:
  --format [terminal|json]  Output format

catalog list-queries

List available queries.

catalog list-queries [OPTIONS]

Options:
  --format [terminal|json]  Output format

catalog mcp

Start the MCP server (stdio transport).

catalog mcp

catalog setup-claude

Configure Claude Code to use Catalog CLI as an MCP tool server.

# Free (local) — data stays on your machine
catalog setup-claude

# Pro (hosted API) — persistent storage, unlimited scans
catalog setup-claude --pro --api-key YOUR_KEY

# Per-project instead of global
catalog setup-claude --project

After setup, restart Claude Code and try: "Scan my-catalog.xlsx and tell me the biggest issues"

Example JSON Output

{
  "timestamp": "2026-03-05T10:30:00Z",
  "marketplace": "US",
  "is_us_marketplace": true,
  "total_queries": 14,
  "total_issues": 47,
  "total_affected_skus": 23,
  "results": [
    {
      "query_name": "missing-attributes",
      "description": "Find mandatory attributes missing from listings",
      "total_issues": 12,
      "affected_skus": 8,
      "issues": [
        {
          "row": 7,
          "sku": "ABC-123",
          "field": "brand",
          "severity": "required",
          "details": "Missing required field: brand",
          "product_type": "HAIR_STYLING_AGENT",
          "extra": {}
        }
      ]
    }
  ]
}

Agent Integration

Via CLI (subprocess)

import subprocess, json

result = subprocess.run(
    ['catalog', 'scan', 'my-catalog.xlsx', '--format', 'json',
     '--fields', 'sku,severity,details', '--limit', '20'],
    capture_output=True, text=True
)
data = json.loads(result.stdout)

Via Python (direct import)

from catalog.core import execute_scan, ScanRequest

request = ScanRequest(
    file="my-catalog.xlsx",
    queries=["missing-attributes", "intent-bullets"],
    fields=["sku", "severity", "details"],
    limit=20,
)
response = execute_scan(request)

Via MCP

Add the MCP server to any MCP client (Claude Desktop, CLR Pro, etc.) and call catalog_scan, catalog_check, catalog_seller_listing_fetch, catalog_seller_listing_diff, catalog_list_queries, or catalog_schema.

Intent-Based Bullet Optimization

The intent-bullets query evaluates bullet points against COSMO-inspired shopper intent coverage:

• Audience / need fit: Who it is for, preferences, or problem state
• Function / use case: The job, activity, event, or use flow
• Context / compatibility: Where, when, or what it works with
• Decision evidence: Specs, attributes, trust signals, or differentiators
• All bullets: Checked for intent coverage, length, vague marketing, ALL CAPS

Scores 1-5 with actionable suggestions. The old rufus-bullets query name still works as a deprecated compatibility alias.

Extending with Custom Queries

from catalog.query_engine import QueryPlugin

class MyCustomQuery(QueryPlugin):
    name = "my-custom-check"
    description = "My custom catalog check"

    def execute(self, listings, clr_parser):
        issues = []
        for listing in listings:
            if some_condition:
                issues.append({
                    'row': listing.row_number,
                    'sku': listing.sku,
                    'field': 'FieldName',
                    'severity': 'warning',
                    'details': 'Issue description',
                    'product_type': listing.product_type
                })
        return issues

Requirements

• Python 3.10+
• openpyxl
• click
• rich
• pydantic
• mcp

How to Get Your CLR

1. Go to Amazon Seller Central > Catalog > Category Listing Report
2. Click Generate Report
3. Download the .xlsm or .xlsx file
4. Run catalog CLI on it

Free vs Pro

Get started at catalogcli.com | API Docs

Contributing

This is an open-source project. Contributions welcome!

• Add new query plugins
• Improve parsing logic
• Enhance output formats
• Build integrations

License

MIT License - Free to use, modify, and distribute.

Author

Built by Brett Bohannon (@BWB03)

Related Projects

• amazon-catalog-auditor-skill - OpenClaw skill for agent workflows
• clr-auditor - Original CLR auditing tool
• amazon-tool - Amazon variation creator

Agent-native Amazon catalog tool. Built for the future of catalog management.