amazon-seller-operations-mcp

v0.1.1 suspicious
7.0
High Risk

Amazon Seller Operations MCP

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits high credential risk due to potential exposure of AWS credentials, along with low maintainer activity and poor metadata quality. These factors suggest a non-trivial risk that could indicate a supply-chain attack.

  • High credential risk due to direct access to AWS credentials
  • Low maintainer activity and poor metadata quality
Per-check LLM notes
  • Network: Network calls are expected for packages interacting with external APIs, like those related to Amazon services.
  • Shell: No shell execution patterns detected.
  • Obfuscation: No obfuscation patterns detected.
  • Credentials: High risk of credential harvesting observed with direct access to AWS credentials via environment variables.
  • Metadata: The package shows signs of low maintainer activity and poor metadata quality, raising suspicion but not definitive evidence of malice.

📦 Package Quality Overall: Low (4.4/10)

✦ High Test Suite 9.0

Test suite present — 6 test file(s) found

  • 6 test file(s) detected (e.g. test_amazon_ads_connector.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (4015 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 33 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

  • No GitHub repository linked — contributor count unavailable

🔬 Heuristic Checks

⚠ Outbound Network Calls score 4.5

Found 3 network call pattern(s)

  • ncode("utf-8") request = urllib.request.Request( api_url, data=body, head
  • ) try: with urllib.request.urlopen(request, timeout=8) as response: data =
  • client = self.http_client or httpx.AsyncClient(timeout=self.config.timeout_seconds) try:
✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

⚠ Credential Harvesting score 7.5

Found 3 credential access pattern(s)

  • region, os.getenv("AWS_ACCESS_KEY_ID", "").strip() or None, os.getenv("
  • .strip() or None, os.getenv("AWS_SECRET_ACCESS_KEY", "").strip() or None, os.gete
  • .strip() or None, os.getenv("AWS_ROLE_ARN", "").strip() or None, ) SP_API_HOSTS = {
✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ Maintainer History score 6.0

3 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
  • Package has no PyPI classifiers (low effort / metadata quality)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with amazon-seller-operations-mcp 
Create a Python-based command-line tool called 'SellerOpsCLI' that leverages the 'amazon-seller-operations-mcp' package to assist Amazon sellers in managing their listings efficiently. This tool should allow users to perform various operations on their product listings such as updating prices, managing inventory levels, and retrieving listing information directly from their Amazon seller account. Here’s a detailed breakdown of what the tool should include:

1. **User Authentication**: Implement a secure method for users to authenticate their Amazon seller accounts using OAuth2.0 or similar protocols supported by the 'amazon-seller-operations-mcp' package.
2. **Price Update Functionality**: Allow users to update the price of one or multiple listings based on predefined rules or manually inputted values. For example, users could set up automatic price adjustments based on competitor pricing data.
3. **Inventory Management**: Provide options to check current inventory levels and adjust them as needed. Users should be able to specify quantities to add or remove from stock, and the tool should automatically update the Amazon listings accordingly.
4. **Listing Information Retrieval**: Enable the retrieval of detailed information about individual listings including title, description, images, and pricing history. This feature will help sellers keep track of their listing performance over time.
5. **Competitor Analysis**: Integrate a feature that fetches competitor data for similar products and presents it alongside the user's own listing details. This can help sellers make informed decisions about pricing strategies and promotional activities.
6. **Reporting and Analytics**: Generate reports summarizing sales data, inventory turnover rates, and other key metrics relevant to sellers. These reports should be customizable and exportable into common formats like CSV or Excel.
7. **Scheduled Tasks**: Implement a scheduler that allows users to set recurring tasks for routine operations such as daily price updates or weekly inventory checks.
8. **Error Handling and Logging**: Ensure robust error handling mechanisms are in place to manage potential issues during API calls and other operations. Logs should be maintained for troubleshooting purposes.

The 'amazon-seller-operations-mcp' package will be the backbone of this application, providing the necessary APIs and functionalities required to interact with the Amazon Selling Partner API. Your task is to design and implement this tool in Python, ensuring it is user-friendly, efficient, and capable of scaling with the needs of growing businesses.

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