🤖 AI Analysis

Final verdict: SAFE

The package appears to be safe with minimal risks identified. It lacks network calls, shell execution, and obfuscation techniques that could indicate malicious activity.

No network calls detected.
No shell execution patterns detected.

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires online data access.
Shell: No shell execution patterns detected, indicating no immediate risk of command injection or system compromise.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package shows some signs of low effort and potential lack of transparency, but there are no clear indicators of malicious intent.

📦 Package Quality Overall: Low (3.8/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

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

◈ Medium Documentation 5.0

Some documentation present

Detailed PyPI description (6798 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

50 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

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 akshare-stock-mcp

Create a real-time stock monitoring application using the Python package 'akshare-stock-mcp'. This application will allow users to track multiple stocks in real-time, receive alerts when specific conditions are met, and visualize stock performance over time. Here’s a detailed plan on how to build it:

1. **Setup Environment**: Ensure you have Python installed along with the necessary packages including 'akshare-stock-mcp'. Use pip to install 'akshare-stock-mcp' if it's not already available.
2. **User Interface**: Design a simple but intuitive UI where users can input stock symbols they want to monitor. Consider using libraries like Tkinter for desktop applications or Streamlit for web-based interfaces.
3. **Real-Time Data Fetching**: Utilize 'akshare-stock-mcp' to fetch real-time stock prices and other relevant data. Integrate this data fetching into your application to update stock information dynamically.
4. **Alert System**: Implement an alert system that triggers notifications (email, SMS, or in-app) based on predefined conditions such as price reaching a certain threshold or significant volume changes.
5. **Data Visualization**: Provide visual representations of stock trends using matplotlib or seaborn for historical data analysis and dynamic graphs for real-time data visualization.
6. **User Management**: Allow users to save their preferences and monitor lists across sessions. Implement basic user management features like login/signup.
7. **Testing and Optimization**: Conduct thorough testing to ensure all functionalities work correctly under various conditions. Optimize the application for performance and reliability.
8. **Deployment**: Prepare the application for deployment either as a desktop app or a web service depending on your chosen platform.

This project aims to leverage 'akshare-stock-mcp' to provide a comprehensive solution for stock enthusiasts looking to stay informed about their investments in real-time.