🤖 AI Analysis

Final verdict: SAFE

The package appears to be safe with no signs of malicious activities such as network calls, shell executions, or credential harvesting. However, the metadata suggests potential new or inactive maintainer activity, which warrants further investigation.

No network calls, shell executions, or credential harvesting detected.
Potential new or inactive maintainer activity noted.

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires internet access for its functionality.
Shell: No shell execution patterns detected, indicating no immediate signs of executing system commands.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package shows signs of potential new or inactive maintainer activity with no community engagement.

📦 Package Quality Overall: Low (3.8/10)

○ Low Test Suite 1.0

No test suite detected

No test files or test-runner configuration detected

◈ Medium Documentation 7.0

Some documentation present

Documentation URL: "Documentation" -> https://docs.agentrecall.cloud
Detailed PyPI description (2724 chars)

○ Low Contributing Guide 4.0

No contributing guide or governance files found

Development Status classifier >= Beta

○ Low Type Annotations 1.0

No type annotations detected

No type annotations, py.typed marker, or stub files detected

◈ Medium Multiple Contributors 6.0

Limited contributor diversity

2 unique contributor(s) across 40 commits in MarsHeer/agentrecall
Two distinct contributors found

🔬 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

Email domain looks legitimate: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: Repository has zero stars and zero forks

Repository has zero stars and zero forks

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

Author name is missing or very short
Author "" 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 agentrecall-mcp

Create a personal knowledge management system called 'AI Notekeeper' using the 'agentrecall-mcp' package. This application will allow users to store, retrieve, and manage their notes with the assistance of an AI-powered memory system. Here’s a detailed breakdown of what the application should include:

1. **User Registration and Login**: Users should be able to create accounts and log in securely.
2. **Note Creation**: Users can write and save notes. Each note can have a title, content, tags, and timestamps.
3. **Note Retrieval**: Utilize 'agentrecall-mcp' to enable intelligent search capabilities. Users can search for notes by keyword, tag, date range, or even through natural language queries.
4. **Tag Management**: Users can add, edit, and delete tags associated with their notes.
5. **AI-Powered Suggestions**: Based on the user's past notes and searches, provide suggestions for related topics or notes.
6. **Data Persistence**: Ensure all data is stored persistently using the 'agentrecall-mcp' package, which acts as a reliable backend for storing and retrieving information.
7. **User Interface**: Develop a simple yet intuitive UI for easy interaction with the app.
8. **Security Measures**: Implement basic security measures such as hashing passwords and ensuring data privacy.

**How 'agentrecall-mcp' is Utilized**:
- For storing user notes and metadata in a structured format.
- To facilitate efficient retrieval of notes based on various criteria.
- Enhancing the search functionality to understand context and provide more accurate results.

This project aims to demonstrate the power of integrating advanced AI memory systems into everyday applications, making it easier for users to organize and recall information efficiently.