ansible-know-mcp

v0.1.0 suspicious
6.0
Medium Risk

Ansible Knowledge MCP Server — module discovery, documentation, and skill generation for AI agents

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits elevated credential risk and metadata concerns, indicating potential malicious intent or poor development practices. While network and shell risks are moderately elevated, they do not independently suggest malicious behavior.

  • Elevated credential risk due to code reading '/etc/passwd'
  • Limited maintainer history and single version release
Per-check LLM notes
  • Network: GET requests might be used for fetching configuration files or updates, which is common and not necessarily suspicious.
  • Shell: Subprocess execution can be legitimate if the package is designed to run system commands, but it also poses a higher risk for potential misuse or unintended consequences.
  • Obfuscation: No obfuscation patterns detected.
  • Credentials: Code attempting to read '/etc/passwd' may indicate an attempt to harvest credentials or system information.
  • Metadata: The package shows several red flags including a lack of maintainer history, a single version release, and an author with limited activity.

📦 Package Quality Overall: Medium (5.4/10)

✦ High Test Suite 9.0

Test suite present — 6 test file(s) found

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

Some documentation present

  • Detailed PyPI description (5363 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

  • 41 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 44 commits in leogallego/ansible-know-mcp
  • Two distinct contributors found

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • [source_name] async with httpx.AsyncClient(timeout=30) as client: resp = await client.get(url)
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

  • gs] try: result = subprocess.run( cmd, capture_output=True,
⚠ Credential Harvesting score 5.0

Found 2 credential access pattern(s)

  • = await get_module_doc("../../etc/passwd") assert "error" in result @pytest.mark.asynci
  • esult = await get_skill("../../etc/passwd") assert "invalid" in result.lower() or "error" in
✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: gallego.red>

✓ 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 6.0

3 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • 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 ansible-know-mcp 
Create a comprehensive, user-friendly web application named 'AI-MCP-Explorer' using Python and Flask, which leverages the 'ansible-know-mcp' package to provide interactive exploration of Ansible modules and their capabilities. This application will serve as a powerful tool for both novice and experienced Ansible users to discover new modules, understand their functionalities, and even generate sample code snippets tailored to specific tasks.

### Core Features:
1. **Module Discovery**: Users can search for specific Ansible modules by name or category. The application should utilize the 'ansible-know-mcp' package to fetch and display detailed information about each module, including parameters, examples, and usage tips.
2. **Documentation Generation**: Upon selecting a module, the app should dynamically generate and present comprehensive documentation, utilizing the 'ansible-know-mcp' package to ensure accuracy and completeness.
3. **Skill Assessment & Code Snippets**: For each module, the application should assess the user's proficiency level based on their input regarding familiarity with similar modules or tasks. Using the 'ansible-know-mcp' package, it should then suggest and generate custom code snippets that cater to the user's skill level and task requirements.
4. **Interactive Learning Path**: Based on user interactions and selections, the application should recommend a personalized learning path, suggesting additional modules and tasks that would enhance the user's Ansible skills.
5. **Feedback & Community Integration**: Allow users to rate and review modules, providing feedback directly within the application. Additionally, integrate a community feature where users can share their experiences, ask questions, and collaborate on projects.

### Technical Requirements:
- Utilize the 'ansible-know-mcp' package to interact with its APIs for fetching module data, generating documentation, and assessing skill levels.
- Develop the front-end using HTML, CSS, and JavaScript, ensuring a responsive design suitable for various devices.
- Implement the back-end using Python and Flask, integrating the 'ansible-know-mcp' package effectively to handle API requests and responses.
- Ensure the application is secure, handling user data responsibly and protecting against common web vulnerabilities.
- Deploy the application on a cloud platform like Heroku or AWS, making it accessible to a global audience.

### Expected Outcome:
By the end of this project, you should have a fully functional web application that not only serves as a valuable resource for Ansible users but also enhances their learning experience through interactive and personalized content.

💬 Discussion Feed

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