atomno-mcp-cbr-rates

v0.1.3 safe
3.0
Low Risk

MCP server for Central Bank of Russia (CBR) data: currency rates, key rate, inflation, macro stats.

🤖 AI Analysis

Final verdict: SAFE

The package appears to have legitimate functionality without any malicious indicators. The primary concern lies in the sparse metadata, but this does not conclusively point towards a supply-chain attack.

  • Low risk in network, shell, obfuscation, and credential areas.
  • Sparse author information suggesting possible new or less transparent development.
Per-check LLM notes
  • Network: The network calls appear to be for fetching currency rates from the Central Bank of Russia, which is expected behavior for a package named 'atomno-mcp-cbr-rates'.
  • Shell: No shell execution patterns were detected, indicating no immediate risk related to shell command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The author's information is sparse, indicating potential lack of transparency or newness.

📦 Package Quality Overall: Medium (5.8/10)

✦ High Test Suite 9.0

Test suite present — 10 test file(s) found

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

Some documentation present

  • Documentation URL: "Documentation" -> https://github.com/atomno-labs/mcp-cbr-rates#readme
  • Detailed PyPI description (6447 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 7.0

Partial type annotation coverage

  • Classifier: Typing :: Typed
  • 78 type-annotated function signatures detected in source
○ Low Multiple Contributors 2.0

Single-author or unverifiable project

  • 1 unique contributor(s) across 9 commits in atomno-labs/mcp-cbr-rates
  • Single author with few commits — possibly a personal or throwaway project

🔬 Heuristic Checks

⚠ Outbound Network Calls score 4.5

Found 3 network call pattern(s)

  • self._client = http_client or httpx.AsyncClient( timeout=timeout, headers={"User-A
  • ORY_TTL) http_client = httpx.AsyncClient( timeout=timeout, headers={ "
  • by respx.""" async with httpx.AsyncClient( base_url="https://www.cbr.ru", timeout=5.
✓ 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

Email domain looks legitimate: atomno-labs.ru>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository atomno-labs/mcp-cbr-rates appears legitimate

⚠ 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 atomno-mcp-cbr-rates 
Create a financial dashboard application using Python that integrates real-time economic data from the Central Bank of Russia (CBR). Your application should be able to fetch and display the latest currency exchange rates, the key interest rate, inflation rates, and macroeconomic statistics. Use the 'atomno-mcp-cbr-rates' package as your primary data source. Here are the steps and features you need to implement:

1. **Setup**: Install the necessary packages including 'atomno-mcp-cbr-rates'. Ensure your environment is set up correctly.
2. **Data Fetching**: Implement functions to fetch currency rates, key interest rate, inflation data, and macroeconomic statistics from the CBR using the 'atomno-mcp-cbr-rates' package.
3. **Data Visualization**: Create a user-friendly interface where users can view the fetched data. Consider using libraries like Matplotlib or Plotly for visual representation.
4. **User Interaction**: Allow users to select specific dates for historical data and choose which types of data they want to view (currency rates, key rate, etc.).
5. **Real-Time Updates**: Implement a feature that updates the displayed data periodically without requiring a page refresh.
6. **Export Data**: Enable users to export the displayed data into CSV or Excel format for further analysis.
7. **Error Handling**: Include robust error handling mechanisms to manage any issues that arise during data fetching or processing.
8. **Documentation**: Provide clear documentation on how to run the application and use its features.

This project aims to showcase the practical application of economic data in a real-world scenario, making it easier for users to understand and analyze financial trends.

💬 Discussion Feed

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