aws-dms-troubleshoot-mcp

v1.0.1 safe
3.0
Low Risk

AWS DMS Troubleshooting MCP Server - Root Cause Analysis tool for AWS Database Migration Service replication issues

🤖 AI Analysis

Final verdict: SAFE

The package is considered safe based on the analysis. It uses standard practices for AWS interaction and does not exhibit signs of malicious behavior.

  • No shell execution or obfuscation detected.
  • AWS credentials are retrieved from environment variables, a common practice.
Per-check LLM notes
  • Network: The use of network calls is likely for legitimate purposes such as interacting with AWS services.
  • Shell: No shell execution patterns detected, which is normal and expected.
  • Obfuscation: No obfuscation patterns detected in the provided code snippet.
  • Credentials: The code is retrieving environment variables for AWS credentials which is a common practice but should ensure proper handling and validation to prevent misuse.
  • Metadata: The author has only one package, which may indicate a new or less active account, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Medium (5.8/10)

✦ High Test Suite 9.0

Test suite present — 2 test file(s) found

  • Test runner config found: pyproject.toml
  • 2 test file(s) detected (e.g. __init__.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (13243 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

  • 14 type-annotated function signatures detected in source
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 4 unique contributor(s) across 10 commits in aws-samples/sample-smb-solutions
  • Small but multi-author team (3–4 contributors)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • try: async with httpx.AsyncClient() as client: response = await client.post(
✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

⚠ Credential Harvesting score 5.0

Found 2 credential access pattern(s)

  • onment variables AWS_REGION = os.environ.get('AWS_REGION', 'us-east-1') AWS_PROFILE = os.environ.get('AWS_PROF
  • ', 'us-east-1') AWS_PROFILE = os.environ.get('AWS_PROFILE', 'default') # Remove default logger and add custom
✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: users.noreply.github.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository aws-samples/sample-smb-solutions appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Amazon Web Services" appears to have only 1 package on PyPI (new or inactive account)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with aws-dms-troubleshoot-mcp 
Your task is to develop a comprehensive, user-friendly command-line interface (CLI) utility that leverages the 'aws-dms-troubleshoot-mcp' Python package to provide root cause analysis for AWS Database Migration Service (DMS) replication issues. This utility will enable database administrators and developers to quickly diagnose and resolve problems encountered during the migration process, enhancing their efficiency and reducing downtime.

The utility should include the following core functionalities:
1. **Replication Task Status Check**: Allow users to input the ARN of a specific DMS replication task and fetch its current status along with any associated errors or warnings.
2. **Detailed Error Analysis**: For any given error message, the utility should analyze it using 'aws-dms-troubleshoot-mcp' and provide a detailed explanation of the possible causes, recommended solutions, and best practices to avoid similar issues in the future.
3. **Automated Troubleshooting Workflow**: Implement a feature where the utility can automatically run through a series of predefined checks based on common issues, such as network connectivity problems, incorrect endpoint configurations, or insufficient storage space, and generate a report summarizing potential issues and their resolutions.
4. **Customizable Alert System**: Enable users to set up alerts for critical issues like replication lag exceeding a certain threshold or failure to apply changes. These alerts can be configured to notify via email or SMS.
5. **Integration with AWS Management Console**: Provide a seamless experience by integrating with the AWS Management Console for easy access to DMS tasks and detailed monitoring capabilities.

To achieve these functionalities, you will need to utilize the 'aws-dms-troubleshoot-mcp' package to handle the root cause analysis and troubleshooting aspects. Your implementation should demonstrate proficiency in Python, including handling AWS services, parsing error messages, and working with command-line arguments. Additionally, ensure your utility is well-documented, with clear instructions for installation, configuration, and usage.

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