HeronIntelligence-mcp

v1.4.5 suspicious
4.0
Medium Risk

Heron Intelligence — MCP server for AI assistants

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low individual risks but raises concerns due to missing repository and incomplete maintainer profile, suggesting potential issues with transparency and accountability.

  • Metadata risk due to missing repository and incomplete maintainer profile
  • Low individual risk scores across other categories
Per-check LLM notes
  • Network: The observed network call patterns are typical for making HTTP requests and likely part of the package's intended functionality.
  • Shell: No shell execution patterns were detected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
  • Credentials: No credential harvesting patterns detected, indicating safe handling of secrets and credentials.
  • Metadata: The repository not being found and the maintainer having an incomplete profile raises suspicion.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 7.5

Found 5 network call pattern(s)

  • ecret).""" async with httpx.AsyncClient(timeout=_HTTP_TIMEOUT) as http: resp = await htt
  • cached[0] async with httpx.AsyncClient(timeout=_HTTP_TIMEOUT) as http: try:
  • ) -> bool: async with httpx.AsyncClient(timeout=_HTTP_TIMEOUT) as http: resp = await htt
  • ientView]: async with httpx.AsyncClient(timeout=_HTTP_TIMEOUT) as http: resp = await htt
  • ) -> str: async with httpx.AsyncClient(timeout=_HTTP_TIMEOUT) as http: resp = await htt
✓ 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 score 3.0

Repository not found (deleted or private)

  • Repository not found (deleted or private)
⚠ 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 HeronIntelligence-mcp 
Create a fully-functional mini-app called 'AI Butler' that integrates the HeronIntelligence-mcp package to manage and control AI assistant functionalities within a smart home environment. This app should serve as a central hub for various AI-driven tasks such as scheduling, automation, and interaction management.

Step 1: Set up the Project Environment
- Initialize a new Python project.
- Install the HeronIntelligence-mcp package via pip.
- Set up a virtual environment for dependency isolation.

Step 2: Define Core Features
- Implement a scheduling system where users can set reminders and schedule events.
- Develop an automation module that can trigger actions based on time, user commands, or environmental conditions (e.g., turning off lights after sunset).
- Integrate a conversation manager to handle user interactions, providing responses and executing commands based on voice or text input.

Step 3: Utilize HeronIntelligence-mcp Package
- Use the MCP server provided by HeronIntelligence-mcp to manage AI assistant instances.
- Configure the server to support multiple AI assistants if needed, each specialized for different tasks or rooms in the house.
- Implement a command-line interface (CLI) for users to interact with the AI Butler, utilizing the HeronIntelligence-mcp package to process these commands and execute corresponding actions.

Step 4: Enhance User Experience
- Design a simple yet intuitive CLI interface.
- Add voice recognition capabilities using an external service (like Google Speech-to-Text), ensuring seamless integration with the HeronIntelligence-mcp server.
- Incorporate feedback mechanisms so that the AI Butler can learn from user interactions and improve its responses over time.

Step 5: Testing and Deployment
- Thoroughly test the application to ensure all features work as expected.
- Document the setup process and how to use the CLI effectively.
- Deploy the application on a local server for continuous use within the smart home environment.

This project aims to showcase the versatility of the HeronIntelligence-mcp package while providing a practical solution for managing smart homes through AI.

💬 Discussion Feed

Leave a comment

No discussion yet. Be the first to share your thoughts!