autocode-mcp

v1.0.5 suspicious
6.0
Medium Risk

MCP Server for competitive programming problem creation, based on AutoCode paper

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows minimal risks in terms of network usage, shell execution, and obfuscation. However, the incomplete author details and new/inactive account status raise concerns about potential supply-chain attacks.

  • Incomplete author details
  • New or inactive account
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external API interactions.
  • Shell: No shell execution patterns detected, indicating the package likely does not execute system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
  • Credentials: No credential harvesting patterns detected, suggesting no risk of secret theft.
  • Metadata: The author's details are incomplete and the account seems new or inactive, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Low (4.4/10)

✦ High Test Suite 9.0

Test suite present — 28 test file(s) found

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

Some documentation present

  • Detailed PyPI description (10212 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

  • 188 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

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

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 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 autocode-mcp 
Your task is to develop a mini-application called 'AutoProblemGen' that leverages the 'autocode-mcp' package to automate the generation of competitive programming problems. This tool will not only generate problem statements but also automatically create test cases and solutions for these problems. Here's a step-by-step guide to building this application:

1. **Setup**: Begin by installing the 'autocode-mcp' package along with any other necessary dependencies like Python and a virtual environment.
2. **Configuration**: Configure your application to connect to the MCP server provided by 'autocode-mcp'. This involves setting up authentication and ensuring your application can communicate effectively with the server.
3. **Problem Generation**: Implement a feature within 'AutoProblemGen' that allows users to specify certain parameters such as difficulty level, topic, and constraints. Based on these inputs, the application should use 'autocode-mcp' to generate a unique problem statement.
4. **Test Case Creation**: Once a problem is generated, your application should automatically create a set of test cases using 'autocode-mcp'. These test cases should cover a range of scenarios including edge cases and typical cases.
5. **Solution Generation**: In addition to generating problems and test cases, 'AutoProblemGen' should also provide a solution for each problem. The solution should be detailed enough to help users understand the logic behind solving the problem.
6. **User Interface**: Develop a simple yet effective user interface for 'AutoProblemGen'. This could be a command-line interface or a web-based interface depending on your preference and skills.
7. **Documentation**: Ensure that your application comes with comprehensive documentation explaining how to install it, how to use it, and any limitations or caveats.
8. **Testing**: Before releasing your application, thoroughly test it to ensure that all features work as expected and that there are no bugs or errors.
9. **Deployment**: Finally, deploy your application so that others can use it. Consider hosting it on a platform like GitHub or Heroku.

By following these steps, you'll create a powerful tool that simplifies the process of creating and testing competitive programming problems, making it easier for educators, competition organizers, and enthusiasts alike.

💬 Discussion Feed

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