asqav-mcp

v0.3.7 suspicious
5.0
Medium Risk

MCP server for Asqav AI agent governance

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has a moderate risk score due to potential network interactions and concerns over metadata quality and maintainer activity.

  • Network risk is present, suggesting possible interaction with external services.
  • Metadata quality and maintainer activity are poor, raising suspicion.
Per-check LLM notes
  • Network: The presence of network calls suggests the package may be designed to interact with external services, but further investigation is needed to confirm legitimacy.
  • Shell: No shell execution patterns detected, indicating low risk of direct system command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package shows signs of low maintainer activity and poor metadata quality, raising suspicion.

📦 Package Quality Overall: Low (4.4/10)

✦ High Test Suite 9.0

Test suite present — 6 test file(s) found

  • Test runner config found: pyproject.toml
  • 6 test file(s) detected (e.g. test_proxy_call_tool_integration.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (15795 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

  • 73 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 4.5

Found 3 network call pattern(s)

  • ication/json"} async with httpx.AsyncClient() as client: response = await client.request(
  • y: async with httpx.AsyncClient() as client: fwd = await client.post(
  • ication/json"} async with httpx.AsyncClient() as client: response = await client.post(
✓ 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 score 2.0

Found 1 suspicious link(s) on the package page

  • Non-HTTPS external link: http://sql-service/execute
✓ 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 asqav-mcp 
Develop a fully-functional mini-application called 'AsqavGuard' that serves as a management dashboard for the Asqav AI agents. This application will leverage the 'asqav-mcp' package to interact with and manage these AI agents effectively. Here are the key functionalities and steps to implement this project:

1. **Setup Environment**: Begin by setting up your development environment. Ensure you have Python installed along with the 'asqav-mcp' package.
2. **Core Functionality**: Utilize 'asqav-mcp' to establish a connection to the MCP server. This server acts as a central hub for managing all AI agents under Asqav governance.
3. **Agent Management Interface**: Create a user-friendly interface where users can view, add, modify, and delete AI agents registered with the MCP server. Each operation should reflect changes in real-time on the server.
4. **Monitoring and Analytics**: Implement a feature that allows users to monitor the performance of AI agents. This could include metrics like response time, error rates, and usage statistics.
5. **Security Features**: Incorporate security measures such as user authentication and authorization. Only authorized users should be able to perform certain actions like modifying or deleting AI agents.
6. **Documentation and Support**: Provide comprehensive documentation for both end-users and developers. Include examples of how to integrate 'AsqavGuard' into existing systems or workflows.

This project aims to demonstrate the power and flexibility of the 'asqav-mcp' package while providing a valuable tool for managing AI agents efficiently.

💬 Discussion Feed

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