arduino-cli-mcp

v0.1.6 suspicious
4.0
Medium Risk

Arduino CLI MCP Server for VSCode and GitHub Copilot integration - a LLM Machine Communication Protocol implementation

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows signs of potential credential risk due to its interaction with sensitive files, despite attempts to mitigate this. The low activity from the maintainer's account also adds to the suspicion.

  • Potential credential risk
  • Low activity from maintainer's account
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require internet access.
  • Shell: Detection of shell execution suggests it might be used to interact with system commands, possibly for installing or configuring Arduino libraries via CLI, but requires further investigation.
  • Obfuscation: No obfuscation patterns were detected in the provided code snippet.
  • Credentials: The code attempts to prevent access to sensitive files like /etc/passwd, which suggests an attempt to avoid credential harvesting but the context indicates potential risk for credential handling.
  • Metadata: The maintainer has a new or inactive account and lacks detailed author information, raising some concerns but not definitive evidence of malice.

📦 Package Quality Overall: Medium (5.0/10)

✦ 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_cli_exec.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://github.com/oliver0804/arduino-cli-mcp#readme
  • Detailed PyPI description (10098 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

  • 35 type-annotated function signatures detected in source
○ Low Multiple Contributors 2.0

Single-author or unverifiable project

  • 1 unique contributor(s) across 11 commits in oliver0804/arduino-cli-mcp
  • Single author with few commits — possibly a personal or throwaway project

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

  • result = subprocess.run( args, capt
⚠ Credential Harvesting score 5.0

Found 2 credential access pattern(s)

  • rm("esp32:esp32 --config-file /etc/passwd") tokens = run.call_args.args[0] assert "--config-
  • le" not in tokens assert "/etc/passwd" not in tokens """Smoke tests: catch the kind of packaging
✓ 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

Repository oliver0804/arduino-cli-mcp appears legitimate

⚠ 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 arduino-cli-mcp 
Create a mini-application that integrates Arduino development with AI-driven assistance through the 'arduino-cli-mcp' package. This tool will serve as a bridge between your Arduino board and an AI language model, allowing you to receive real-time coding suggestions and insights directly from the AI while working on your Arduino projects. Here’s a step-by-step guide on how to build this application:

1. **Setup**: Begin by setting up your development environment. Ensure you have Python installed, along with the 'arduino-cli-mcp' package. Additionally, install any necessary dependencies such as libraries for interfacing with Arduino boards.

2. **Project Initialization**: Initialize a new Python project. Create a main script file where the core logic of your application will reside.

3. **Integration with Arduino CLI**: Use the 'arduino-cli-mcp' package to establish a connection between your application and the Arduino CLI. This will allow your application to communicate with the Arduino board and execute commands.

4. **AI Integration**: Integrate an API endpoint for an AI language model (such as ChatGPT or Claude). Your application will send code snippets to the AI for analysis and suggestion generation.

5. **Real-Time Suggestions**: Implement functionality within your application that sends current lines of code being written to the AI for suggestions. Display these suggestions in a user-friendly manner within your application interface.

6. **Error Handling and Feedback**: Add robust error handling to manage any issues that arise during communication with the Arduino board or the AI model. Provide feedback to the user about the status of their requests.

7. **User Interface**: Develop a simple yet effective user interface that allows users to interact with both their Arduino board and the AI model seamlessly. Consider using a GUI toolkit like Tkinter for this purpose.

8. **Testing and Validation**: Test your application thoroughly to ensure it works as expected. Validate its performance with various Arduino sketches and observe how well it integrates with the AI model.

9. **Documentation**: Document your project thoroughly, explaining each component and how they work together. Include setup instructions, usage guidelines, and troubleshooting tips.

**Suggested Features**:
- Live Code Analysis: As users type, automatically analyze the code and provide suggestions.
- Error Detection: Identify potential errors in the code and suggest corrections.
- Example Code Generation: Generate example code snippets based on user input or context.
- Interactive Debugging: Allow users to debug their code interactively with the help of AI insights.
- Integration with Popular IDEs: Extend functionality to integrate with popular IDEs like VSCode, enhancing the development experience.

By following these steps and incorporating these features, you'll create a powerful tool that leverages the capabilities of both the 'arduino-cli-mcp' package and AI-driven assistance, making Arduino development more accessible and efficient.

💬 Discussion Feed

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