🤖 AI Analysis

Final verdict: SAFE

The package exhibits low risk across all assessed categories, with no indications of malicious activity or supply-chain attacks.

No network calls detected
No shell execution patterns
No obfuscation or credential harvesting patterns
Maintainer has only one package

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires external services.
Shell: No shell execution patterns detected, indicating no immediate risk of command injection or privilege escalation.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent related to code obfuscation.
Credentials: No credential harvesting patterns detected, suggesting no immediate risk of secret or sensitive information being stolen.
Metadata: The maintainer has only one package, which could indicate a new or less active account, but no other red flags are present.

📦 Package Quality Overall: Medium (6.2/10)

✦ High Test Suite 9.0

Test suite present — 6 test file(s) found

Test runner config found: conftest.py
Test runner config found: pyproject.toml
6 test file(s) detected (e.g. conftest.py)

◈ Medium Documentation 7.0

Some documentation present

Documentation URL: "Documentation" -> https://github.com/jenreh/appkit/tree/main/docs
Brief PyPI description (310 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

30 type-annotated function signatures detected in source

✦ High Multiple Contributors 8.0

Active multi-contributor project

3 unique contributor(s) across 100 commits in jenreh/appkit
Small but multi-author team (3–4 contributors)

🔬 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

Repository jenreh/appkit appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "Jens Rehpöhler" 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 appkit-mcp-user

Create a user analytics dashboard application using the Python package 'appkit-mcp-user'. This application will allow users to track and analyze their online behavior across multiple platforms. The goal is to provide insights into user engagement, session duration, page views, and more, helping users understand their digital footprint better.

Step-by-Step Instructions:
1. Set up a development environment with Python installed.
2. Install the 'appkit-mcp-user' package via pip.
3. Design a simple UI for inputting user IDs and selecting time ranges for analysis.
4. Implement functionality to fetch analytics data from the MCP User Analytics Server using 'appkit-mcp-user'.
5. Display fetched data in a tabular format, including metrics like total sessions, average session duration, and unique page views.
6. Add visualizations such as bar charts and line graphs to represent trends over time.
7. Include filters to allow users to refine their data based on specific criteria (e.g., date range, platform).
8. Ensure the application logs any errors encountered during data retrieval or processing.
9. Test the application thoroughly to ensure it handles various edge cases gracefully.
10. Document your code and include a README file detailing setup instructions and usage examples.

Suggested Features:
- Real-time updates of analytics data.
- Export options to save analytics data in CSV or JSON formats.
- Integration with popular charting libraries for dynamic visual representations.
- Support for multiple languages to cater to a global audience.

How 'appkit-mcp-user' is Utilized:
The 'appkit-mcp-user' package provides essential functionalities for connecting to the MCP User Analytics Server, retrieving user data, and managing server interactions. It simplifies the process of fetching analytics data, allowing developers to focus on building the user interface and implementing additional features.