awslabs.aws-support-mcp-server

v0.1.20 safe
4.0
Medium Risk

An Model Context Protocol (MCP) server for AWS SupportAPI.

🤖 AI Analysis

Final verdict: SAFE

The package is deemed safe with low risk indicators. While there is a moderate credential risk due to the use of environment variables for AWS credentials, this is a standard practice. The other risks are minimal.

  • Moderate credential risk due to use of environment variables
  • Low obfuscation risk from base64 decoding
Per-check LLM notes
  • Network: No network calls detected, which is normal for packages not requiring external services.
  • Shell: No shell execution patterns detected, indicating no direct system command execution.
  • Obfuscation: Base64 decoding is commonly used for data serialization and not necessarily indicative of malicious intent.
  • Credentials: Using environment variables to store AWS credentials is a common practice but should be done securely to prevent unauthorized access.
  • Metadata: The maintainer has a new or inactive PyPI account with only one package, which could indicate potential risk.

📦 Package Quality Overall: Low (4.8/10)

✦ 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. test_aws_support_mcp_server.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (5360 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 7.0

Partial type annotation coverage

  • Type checker (mypy / pyright / pytype) referenced in project
  • 61 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

No suspicious network call patterns found

⚠ Code Obfuscation score 6.0

Found 3 obfuscation pattern(s)

  • file_bytes = base64.b64decode(raw_data) except Exception:
  • inner = base64.b64decode(decoded_text) if len(inner) < len(fi
  • amespace packages. __path__ = __import__('pkgutil').extend_path(__path__, __name__) # Copyright Amazon.com, In
✓ Shell / Subprocess Execution

No shell execution patterns detected

⚠ Credential Harvesting score 5.0

Found 2 credential access pattern(s)

  • rtClient( region_name=os.environ.get('AWS_REGION', DEFAULT_REGION), profile_name=os.environ.ge
  • REGION), profile_name=os.environ.get('AWS_PROFILE'), ) except Exception as e: logger.error(f'F
✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ 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 awslabs.aws-support-mcp-server 
Create a fully-functional mini-application that leverages the 'awslabs.aws-support-mcp-server' Python package to interact with the AWS Support API using the Model Context Protocol (MCP). This application will serve as a bridge between users and AWS Support, enabling them to manage their support cases more efficiently. Here’s a detailed step-by-step guide on how to develop this application:

1. **Setup Environment**: Begin by setting up your development environment. Ensure you have Python installed along with virtual environments. Install the 'awslabs.aws-support-mcp-server' package via pip.

2. **Authentication**: Implement a secure way of handling AWS credentials. Use the Boto3 library to handle authentication and ensure that these credentials are stored securely, perhaps using AWS IAM roles if running in an EC2 instance.

3. **Server Initialization**: Utilize the 'awslabs.aws-support-mcp-server' package to initialize a MCP server that connects to the AWS Support API. Configure this server to listen for incoming requests from clients.

4. **Client Interface**: Develop a simple command-line interface (CLI) or a basic web frontend that allows users to interact with the server. Users should be able to submit new support cases, view existing ones, and update their status.

5. **Support Case Management**: Integrate functionalities that allow users to create, retrieve, update, and delete (CRUD) support cases through the MCP server. Each operation should reflect the corresponding actions available through the AWS Support API.

6. **Logging and Monitoring**: Implement logging mechanisms to track all interactions with the AWS Support API. Additionally, set up monitoring to alert administrators about any issues or errors encountered during operations.

7. **Security Enhancements**: Secure the communication between the client and server using HTTPS. Also, implement rate limiting to prevent abuse of the AWS Support API.

8. **Documentation and Testing**: Write comprehensive documentation explaining how to use the application and its features. Conduct thorough testing to ensure reliability and security.

Suggested Features:
- Support for multiple AWS accounts
- Detailed error messages and retry logic for failed API calls
- User-friendly CLI commands and web forms
- Integration with popular logging services like AWS CloudWatch
- Optional email notifications for case updates

By following these steps, you will create a versatile tool that simplifies interaction with AWS Support, enhancing user experience and operational efficiency.

💬 Discussion Feed

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