astra-mcp

v1.0.0 safe
3.0
Low Risk

MCP server giving Claude Code, Cursor, Codex and Windsurf permanent AST-powered code memory. 98.9% token reduction. 100% local.

🤖 AI Analysis

Final verdict: SAFE

The package has minimal risks associated with it, primarily due to the potential misuse of shell commands. However, there's no clear indication of malicious intent.

  • Low obfuscation and credential risk
  • Shell risk due to potential misuse of shell commands
  • New package with limited author information
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires external communications.
  • Shell: The use of shell execution to run other commands may indicate legitimate functionality but also poses a risk if not properly sanitized or controlled.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
  • Credentials: No credential harvesting patterns detected, suggesting safe handling of secrets and credentials.
  • Metadata: The package shows some red flags such as being brand new and having an author with limited information, but no concrete evidence of malicious intent is present.

📦 Package Quality Overall: Medium (6.4/10)

✦ High Test Suite 9.0

Test suite present — 5 test file(s) found

  • 5 test file(s) detected (e.g. test_daemon.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://github.com/Charan-place/ASTra-MCP#readme
  • Detailed PyPI description (22141 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

  • Type checker (mypy / pyright / pytype) referenced in project
  • 148 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 5.0

Limited contributor diversity

  • 1 unique contributor(s) across 31 commits in Charan-place/ASTra-MCP
  • Single author but highly active (31 commits)

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 4.0

Found 2 shell execution pattern(s)

  • as log_f: proc = subprocess.Popen( [sys.executable, "-m", "astra.daemon.runner
  • f run(cmd, cwd=None): subprocess.run(cmd, cwd=cwd or repo_dir, check=True,
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository Charan-place/ASTra-MCP appears legitimate

⚠ 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 astra-mcp 
Create a fully-functional Python mini-application named 'CodeMemoryEnhancer' that leverages the 'astra-mcp' package to enhance code development efficiency by reducing repetitive coding tasks through AST-powered code memory. This application will serve as a local code memory assistant that developers can use to store, retrieve, and optimize their code snippets efficiently. Here are the key steps and features for building this application:

1. **Setup Environment**: Begin by setting up your Python environment and installing the 'astra-mcp' package along with any other necessary dependencies.
2. **Initialization of Code Memory Server**: Use 'astra-mcp' to initialize a local MCP server that acts as a repository for storing code snippets in AST format.
3. **User Interface Development**: Develop a simple command-line interface (CLI) for interacting with the code memory server. Users should be able to add, delete, update, and search for code snippets using this CLI.
4. **AST Conversion and Storage**: Implement functionality within the application that converts user-provided code snippets into Abstract Syntax Trees (ASTs) before storing them in the 'astra-mcp' server. Ensure that the process achieves at least a 98.9% token reduction as advertised by 'astra-mcp'.
5. **Code Snippet Retrieval**: Allow users to query the server for specific code snippets based on keywords or tags. The application should return the most relevant snippets in a readable format.
6. **Optimization Suggestions**: Utilize the AST-based code memory to provide optimization suggestions for code snippets. For example, if a snippet is inefficient, suggest a more optimized version based on stored patterns.
7. **Security Measures**: Since the application stores sensitive code snippets, implement basic security measures such as encryption for data at rest and in transit.
8. **Documentation**: Provide comprehensive documentation explaining how to install, configure, and use the 'CodeMemoryEnhancer' application effectively.

By following these steps and incorporating these features, you'll create a powerful tool that significantly enhances developer productivity by reducing the need to rewrite common code snippets and offering real-time optimization suggestions.

💬 Discussion Feed

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