AI Analysis
The package appears to be legitimate based on the analysis notes provided, with low risks across all categories except credential handling, which is a common concern but not indicative of malicious intent.
- Low network and shell execution risks
- Standard module extension method used
- Credentials retrieved from environment variables
Per-check LLM notes
- Network: No network calls detected, which is normal if the package does not require external communication.
- Shell: No shell execution patterns detected, indicating no immediate signs of executing system commands.
- Obfuscation: The observed pattern is a standard method to extend the search path for modules within a package and does not indicate malicious obfuscation.
- Credentials: The code snippet retrieves AWS credentials from environment variables which is a common practice but should be handled with caution to prevent accidental exposure.
- Metadata: The maintainer has only one package, which might indicate a new or less active account, but no other red flags are present.
Package Quality Overall: Medium (6.6/10)
Test suite present β 9 test file(s) found
Test runner config found: conftest.pyTest runner config found: pyproject.toml9 test file(s) detected (e.g. __init__.py)
Some documentation present
Documentation URL: "Documentation" -> https://awslabs.github.io/mcp/servers/amazon_mq-mcp-server/Detailed PyPI description (8959 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
62 type-annotated function signatures detected in source
Active multi-contributor project
42 unique contributor(s) across 100 commits in awslabs/mcpActive community β 5 or more distinct contributors
Heuristic Checks
No suspicious network call patterns found
Found 1 obfuscation pattern(s)
amespace packages. __path__ = __import__('pkgutil').extend_path(__path__, __name__) # Copyright Amazon.com, In
No shell execution patterns detected
Found 2 credential access pattern(s)
ts: aws_profile = os.environ.get('AWS_PROFILE', 'default') self.clients[client_key] =e): aws_profile = os.environ.get('AWS_PROFILE', 'default') return boto3.Session(profil
No typosquatting candidates detected
Email domain looks legitimate: users.noreply.github.com>
All external links appear legitimate
Repository awslabs/mcp appears legitimate
1 maintainer concern(s) found
Author "Amazon Web Services" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a mini-application named 'AMQBrokerManager' that leverages the 'awslabs.amazon-mq-mcp-server' package to provide an intuitive interface for managing Amazon MQ brokers. This application will allow users to easily provision, configure, and monitor their brokers through a simple command-line interface (CLI). Hereβs a detailed breakdown of the functionalities you need to implement: 1. **User Authentication**: Implement user authentication to ensure only authorized users can interact with the application. Users should be able to log in using AWS credentials. 2. **Broker Management**: Enable users to create, delete, and update Amazon MQ brokers. Each broker should have configurable parameters such as broker type, engine type, and storage types. 3. **Configuration Management**: Allow users to apply configurations to their brokers including setting up users, groups, and access policies. 4. **Monitoring**: Provide real-time monitoring capabilities to track the status, performance, and health of each broker. Display metrics such as CPU usage, memory usage, and network throughput. 5. **Logs and Alerts**: Integrate logging functionality to record all actions performed on the brokers. Additionally, set up alerting mechanisms to notify users via email or SMS if any broker encounters critical issues. 6. **Documentation and Help**: Include comprehensive documentation and help guides within the CLI to assist new users in understanding how to use the application effectively. The 'awslabs.amazon-mq-mcp-server' package will be central to enabling communication between the application and Amazon MQ services. It will facilitate the execution of commands related to broker management and configuration. Ensure that the application is well-structured, modular, and easy to extend with additional features in the future.
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