🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has moderate risk due to low maintainer engagement and poor metadata quality, although there are no clear signs of malicious activity.

Low maintainer engagement
Poor metadata quality

Per-check LLM notes

Network: The network call suggests the package interacts with an API, which is common for packages that require external services or updates.
Shell: No shell execution patterns were detected, indicating no immediate risk from executing system commands.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
Credentials: No credential harvesting patterns detected, suggesting no risk of credential theft.
Metadata: The package shows signs of low maintainer engagement and poor metadata quality, raising some suspicion but not definitive evidence of malicious intent.

📦 Package Quality Overall: Low (4.4/10)

✦ High Test Suite 9.0

Test suite present — 2 test file(s) found

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

◈ Medium Documentation 5.0

Some documentation present

Brief PyPI description (700 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

59 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 1.5

Found 1 network call pattern(s)

", DEFAULT_API_URL) with httpx.Client( base_url=api_url, headers={"Authorization":

✓ 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 aivibe-mcp

Your task is to develop a mini-application that leverages the 'aivibe-mcp' Python package to manage and manipulate data within the AIVibe platform. This application will serve as a bridge between users and the AIVibe platform, enabling them to interact with their organization's data more efficiently. Here’s a step-by-step guide on what your application should achieve:

1. **User Authentication:** Allow users to log into the application using their AIVibe credentials. Once authenticated, the application should automatically scope all subsequent actions to the logged-in user's active organization.
2. **Data Ingestion:** Implement a feature that allows users to ingest new data into their organization's database through the Cowork JD ingestion tool provided by 'aivibe-mcp'. This could include uploading CSV files or directly entering data via a form interface.
3. **Consultant App Prepopulation:** Develop a functionality that prepopulates data from the AIVibe platform into a consultant's app. Users should be able to select which fields they want to prepopulate and specify the target app.
4. **Org-Chart Management:** Integrate the ability to import and export organizational charts using the org-chart ingestion feature of 'aivibe-mcp'. This includes adding, removing, or updating employees in the org chart.
5. **Library Role Template Deployment:** Provide a module that deploys role templates across different departments within an organization. These templates should be customizable to fit specific needs.
6. **Session Scoping:** Ensure that every write operation performed through the application is scoped to the active organization of the logged-in user, adhering to the security guidelines outlined in 'aivibe-mcp'.
7. **User Interface Design:** Design a clean, intuitive UI where users can easily navigate these features. Consider including tooltips or help sections to guide users through complex operations.
8. **Testing and Documentation:** Before deployment, thoroughly test each feature to ensure it works as expected. Also, provide comprehensive documentation detailing how to use each feature and troubleshoot common issues.

By following these steps and utilizing the core functionalities of 'aivibe-mcp', you'll create a powerful yet user-friendly tool that enhances interaction with the AIVibe platform.