awslabs.amazon-translate-mcp-server

v1.0.1 safe
4.0
Medium Risk

A Model Context Protocol server for Amazon Translate to provide text translation, custom terminology management, and batch translation processing

🤖 AI Analysis

Final verdict: SAFE

The package appears safe based on the analysis notes, with low risks across most categories. The credential risk is slightly elevated due to access to AWS credentials via environment variables.

  • No network or shell execution risks detected
  • Base64 decoding present but not suspicious
  • Access to AWS credentials via environment variables
Per-check LLM notes
  • Network: No network calls detected, which is not necessarily suspicious for a package interfacing with AWS services like Amazon Translate, as it may rely on local SDKs.
  • Shell: No shell execution patterns detected, indicating the package does not execute external commands that could pose a risk.
  • Obfuscation: The detected pattern suggests the use of base64 decoding which is commonly used for data serialization and not necessarily indicative of malicious activity.
  • Credentials: The package is accessing environment variables related to AWS credentials which could be legitimate but also poses a risk if not handled securely.
  • Metadata: The author has only one package, which may indicate a new or less active account, but there are no other red flags.

📦 Package Quality Overall: Medium (7.0/10)

✦ High Test Suite 9.0

Test suite present — 33 test file(s) found

  • Test runner config found: conftest.py
  • Test runner config found: pyproject.toml
  • 33 test file(s) detected (e.g. __init__.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://awslabs.github.io/mcp/servers/amazon-translate-mcp-s
  • Detailed PyPI description (5429 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 131 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 42 unique contributor(s) across 100 commits in awslabs/mcp
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 4.0

Found 2 obfuscation pattern(s)

  • ent decoded_content = base64.b64decode(file_content) # Create temporary file with
  • amespace packages. __path__ = __import__('pkgutil').extend_path(__path__, __name__) # Copyright Amazon.com, In
✓ Shell / Subprocess Execution

No shell execution patterns detected

⚠ Credential Harvesting score 10.0

Found 6 credential access pattern(s)

  • ( region_name or os.getenv('AWS_REGION') or os.getenv('AWS_DEFAULT_REGION') )
  • or os.getenv('AWS_REGION') or os.getenv('AWS_DEFAULT_REGION') ) self._profile_name = prof
  • rofile_name = profile_name or os.getenv('AWS_PROFILE') self._aws_access_key_id = aws_access_key_i
  • key_id = aws_access_key_id or os.getenv('AWS_ACCESS_KEY_ID') self._aws_secret_access_key = aws_se
  • ey = aws_secret_access_key or os.getenv('AWS_SECRET_ACCESS_KEY') self._aws_session_token = aws_se
  • _token = aws_session_token or os.getenv('AWS_SESSION_TOKEN') # Connection pool configuration
✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: users.noreply.github.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository awslabs/mcp appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Amazon Web Services" 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 awslabs.amazon-translate-mcp-server 
Create a fully-functional mini-app named 'TranslationWorkbench' using the Python package 'awslabs.amazon-translate-mcp-server'. This app will serve as a versatile tool for managing text translations, custom terminologies, and batch translation processes. Here's a detailed breakdown of what your project should include:

1. **User Interface**: Develop a simple yet intuitive web-based interface using Flask or Django. The UI should allow users to input text, select source and target languages, and manage custom terminologies.
2. **Text Translation**: Implement a feature that allows users to translate text from one language to another in real-time. Use the 'awslabs.amazon-translate-mcp-server' package to connect to Amazon Translate's services and perform these translations efficiently.
3. **Custom Terminology Management**: Enable users to upload and manage their own custom terminology files (e.g., CSV or JSON). These files should help improve the accuracy of translations by providing context-specific terms.
4. **Batch Translation Processing**: Allow users to upload multiple text files for batch translation. The app should process these files asynchronously and provide download links for the translated files once they are ready.
5. **Logging and Monitoring**: Integrate logging capabilities to monitor the performance and usage of the TranslationWorkbench. This could include tracking the number of translations performed, errors encountered, and user activity.
6. **Security Measures**: Ensure all interactions with the 'awslabs.amazon-translate-mcp-server' are secure by implementing proper authentication and authorization mechanisms. Also, consider encrypting sensitive data such as custom terminology files.
7. **Documentation**: Provide comprehensive documentation on how to install, configure, and use the TranslationWorkbench. Include examples of API usage and best practices for custom terminology management.

The 'awslabs.amazon-translate-mcp-server' package plays a crucial role in this project by serving as the bridge between the app and Amazon Translate's powerful translation services. It enables efficient management of model contexts, which is essential for handling custom terminologies and ensuring accurate translations. By leveraging this package, you can streamline the development process and focus more on enhancing the user experience and functionality of your mini-app.

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