awslabs.redshift-mcp-server

v0.0.24 safe
3.0
Low Risk

An AWS Labs Model Context Protocol (MCP) server for Redshift

🤖 AI Analysis

Final verdict: SAFE

The package is deemed safe based on the low risk scores across all categories. While there is a moderate credential risk, it is likely due to legitimate AWS service configuration needs.

  • Low network and shell risks
  • Moderate credential risk, possibly for AWS service configuration
  • No signs of supply-chain attack
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires external services.
  • Shell: No shell execution patterns detected, indicating no direct system command execution.
  • Obfuscation: The obfuscation pattern detected is a common method to extend the search path for packages and does not indicate malicious intent.
  • Credentials: The credential harvesting patterns detected are likely for legitimate use, such as configuring AWS services, but could pose a risk if not properly secured.
  • Metadata: The author has only one package, which may indicate a new or less active account, but no other suspicious activities were flagged.

📦 Package Quality Overall: Medium (6.6/10)

✦ High Test Suite 9.0

Test suite present — 4 test file(s) found

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

Some documentation present

  • Documentation URL: "docs" -> https://awslabs.github.io/mcp/servers/redshift-mcp-server/
  • Detailed PyPI description (15609 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

  • 21 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 2.0

Found 1 obfuscation pattern(s)

  • amespace packages. __path__ = __import__('pkgutil').extend_path(__path__, __name__) # Copyright Amazon.com, In
✓ Shell / Subprocess Execution

No shell execution patterns detected

⚠ Credential Harvesting score 7.5

Found 3 credential access pattern(s)

  • on__}', ), aws_region=os.environ.get('AWS_REGION'), aws_profile=os.environ.get('AWS_PROFILE'), )
  • AWS_REGION'), aws_profile=os.environ.get('AWS_PROFILE'), ) # Global session manager instance session_mana
  • edentials chain (IAM roles, ~/.aws/credentials, etc.). - AWS_PROFILE environment variable (if set). - Regi
✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: amazon.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.redshift-mcp-server 
Develop a real-time data analytics dashboard for Amazon Redshift using the 'awslabs.redshift-mcp-server' package. This dashboard will allow users to visualize and interact with live data from their Redshift clusters. The application should include the following core functionalities:

1. **Data Ingestion**: Implement a feature where the application periodically fetches new data from a specified Redshift cluster using the MCP server provided by 'awslabs.redshift-mcp-server'. Ensure that the data is fetched in real-time or near-real-time based on user preference.
2. **Data Visualization**: Use a popular JavaScript library like D3.js or Chart.js to create interactive charts and graphs that update dynamically as new data comes in. Users should be able to select which metrics they want to view and customize chart types (line, bar, pie, etc.).
3. **User Authentication**: Integrate a simple authentication system to restrict access to the dashboard. Users must log in before they can view or manipulate data.
4. **Customizable Dashboards**: Allow users to save their dashboard configurations so they can return to them later. Each user should have the ability to create multiple dashboards tailored to different analytical needs.
5. **Alert System**: Set up an alert mechanism that notifies users via email or SMS when certain thresholds are met or exceeded based on the data being monitored.

The 'awslabs.redshift-mcp-server' package plays a crucial role in this project by serving as the interface between your application and the Redshift cluster. It enables efficient and scalable data retrieval, which is essential for real-time analytics. Your task is to demonstrate how to set up this server, connect it to your application, and retrieve data in a structured format suitable for visualization.

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