AI Analysis
The package exhibits typical behavior for a web scraping tool with minimal risks identified. While there is some concern about the recent activity and maintainer status, there are no definitive signs of malicious activity.
- Low network, shell, obfuscation, and credential risks
- Metadata risk due to recent commit activity and maintainer status
Per-check LLM notes
- Network: The observed network call pattern is typical for a web scraping tool, suggesting it fetches data from the internet.
- Shell: No shell execution patterns were detected.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The recent burst of commits and the maintainer's new or inactive status raise some concerns, but there are no clear signs of typosquatting or other malicious intent.
Package Quality Overall: Low (3.4/10)
No test suite detected
No test files or test-runner configuration detected
Some documentation present
Detailed PyPI description (4262 chars)
No contributing guide or governance files found
Development Status classifier >= Beta
Partial type annotation coverage
3 type-annotated function signatures (partial)
Single-author or unverifiable project
1 unique contributor(s) across 10 commits in yubinkim444/ai-first-scraper-mcpSingle author with few commits — possibly a personal or throwaway project
Heuristic Checks
Found 1 network call pattern(s)
] = max_tokens async with httpx.AsyncClient(timeout=DEFAULT_TIMEOUT) as client: resp = await cli
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
No author email provided
All external links appear legitimate
Git history flags: All 10 commits happened within 24 hours
All 10 commits happened within 24 hours
1 maintainer concern(s) found
Author "yubinkim444" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a web-based utility named 'MarkdownMagnet' that allows users to input any URL and retrieve its content as clean, ad-free Markdown text. Utilize the 'ai-first-scraper-mcp' package to handle the web scraping and ensure the content is free from ads and unnecessary elements. The application should also provide a simple interface where users can search through the scraped Markdown text for specific keywords or phrases. Additionally, implement a feature that saves the scraped Markdown files locally or uploads them to a cloud storage service like Google Drive or Dropbox. Users should be able to authenticate their cloud storage accounts within the app. To make the app more user-friendly, include a preview pane that displays the scraped content in a readable format before downloading or uploading. The project should be built using Flask for the backend and React for the frontend, ensuring a seamless integration between the two.
💬 Discussion Feed
No discussion yet. Be the first to share your thoughts!
Report Abuse / Security Issue