🤖 AI Analysis

Final verdict: SAFE

The package appears to be legitimate with no evident malicious activities. While it has a slightly higher metadata risk score, this does not strongly indicate malicious intent.

Low network, shell, obfuscation, and credential risks.
Moderate metadata risk, possibly due to low maintainer activity.

Per-check LLM notes

Network: The use of HTTP requests is common for fetching external resources or making API calls, indicating normal network behavior.
Shell: No shell execution patterns detected, which is expected and safe.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
Credentials: No credential harvesting patterns detected, indicating low risk of secret theft.
Metadata: The package shows some signs of low effort and could potentially be from an inactive or new maintainer, but there are no clear red flags indicating malicious intent.

📦 Package Quality Overall: Low (4.4/10)

✦ High Test Suite 9.0

Test suite present — 8 test file(s) found

8 test file(s) detected (e.g. test_client_error_handling.py)

◈ Medium Documentation 5.0

Some documentation present

Detailed PyPI description (15581 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

226 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 score 3.0

Found 2 network call pattern(s)

} async with httpx.AsyncClient(timeout=timeout_seconds) as client: try:
try: async with httpx.AsyncClient(timeout=config.external_timeout) as client: resp

✓ 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 6.0

3 maintainer concern(s) found

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 allstacks-mcp

Create a web-based dashboard application using Python and Flask that integrates with the Allstacks API through the 'allstacks-mcp' package. This application will serve as a comprehensive tool for users to visualize and analyze their Allstacks projects, metrics, and analytics data in real-time. The app should allow users to log in, view their current projects, and access detailed analytics reports. Additionally, it should provide interactive charts and graphs to help users better understand their data trends over time.

Key Features:
1. User Authentication: Implement a simple login system where users can sign in using their Allstacks credentials.
2. Project Management: Display a list of all the user's projects, including basic information such as project name, description, and status.
3. Detailed Analytics: Provide detailed views of each project's analytics, including metrics like engagement rates, conversion rates, and more.
4. Interactive Visualization: Use libraries like Plotly or Matplotlib to create dynamic charts and graphs that update in real-time based on selected metrics.
5. Real-Time Updates: Ensure that the dashboard updates automatically every minute to reflect any changes in the underlying data.
6. Customizable Views: Allow users to customize their dashboard layout and select which metrics they want to display prominently.

How to Utilize 'allstacks-mcp':
- Use the 'allstacks-mcp' package to establish a connection to the Allstacks API and retrieve necessary project and metric data.
- Leverage the package's capabilities to filter and sort retrieved data efficiently.
- Integrate the package's functionalities to handle real-time data streaming and updates within your Flask application.
- Ensure secure handling of user credentials when interacting with the Allstacks API via 'allstacks-mcp'.