🤖 AI Analysis

Final verdict: SAFE

The package exhibits minimal risks in terms of network usage, shell execution, obfuscation, and credential handling. However, the low maintainer activity and poor metadata quality suggest some caution is warranted.

Low maintainer activity
Poor metadata quality

Per-check LLM notes

Network: No network calls detected, which is normal for a package focused on server time handling.
Shell: No shell execution detected, which is also expected for a package that appears to be related to asynchronous server time handling.
Obfuscation: No obfuscation patterns detected, suggesting legitimate use.
Credentials: No credential harvesting patterns detected, indicating no risk of secret theft.
Metadata: The package shows signs of low maintainer activity and poor metadata quality, which could indicate potential risks.

📦 Package Quality Overall: Low (3.0/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

1 test file(s) detected (e.g. test_time_server.py)

○ Low Documentation 1.0

No documentation detected

No documentation URL, doc files, or meaningful description found

○ 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

9 type-annotated function signatures (partial)

○ 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

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ 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 8.0

4 maintainer concern(s) found

Only one version has ever been released — brand new package
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 aiomcp-server-time

Create a fully functional mini-application called 'GlobalTimeSync' using the Python package 'aiomcp-server-time'. This application will serve as a time and timezone converter, allowing users to input their current location and desired location to see the current time in both places. Additionally, it will provide information on timezone differences and daylight saving adjustments if applicable.

Steps to follow:
1. Set up the project environment, including installing 'aiomcp-server-time' and any other necessary packages.
2. Design the user interface which could be a simple command-line interface or a more interactive web-based UI using Flask or Django.
3. Implement the functionality to accept user inputs for origin and destination locations.
4. Use 'aiomcp-server-time' to fetch the current time and timezone details for both locations.
5. Display the results to the user, showing the current time in both locations and the difference in hours between them.
6. Optionally, add features such as a history of past conversions, automatic detection of the user's current location based on IP address, or a feature to set reminders for specific times across different timezones.
7. Ensure the application handles errors gracefully, such as invalid location inputs or network issues.
8. Write tests to verify the correctness and reliability of your application.
9. Document the setup process and usage instructions for your application.