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650,501 tools. Updated 2026-10-13 23:30

"A tool for analyzing Python repository structure and code relationships" matching MCP tools:

  • Return the file-level import graph of a code repository folder as JSON, mapping internal Python and JavaScript/TypeScript dependencies.
    MIT
  • Retrieve a stored architecture overview of an analyzed code repository folder to understand its structure, listing files by PageRank with top classes, functions, and methods.
    MIT
  • Generate executable Python code for nonlinear programming, rootfinding, ODE/DAE simulation, and optimal control, with an explanation of the approach.
    MIT
  • Scan Python code with Bandit to uncover security vulnerabilities including SQL injection, hardcoded secrets, and unsafe functions.
    MIT No Attribution

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  • Generate executable Python code for Tidy3D FDTD and mode-solving simulations from a natural language problem description. Fixes failed code when given the previous code and error.
    MIT
  • Analyze Cloudflare D1 database schema structure, tables, columns, indexes, and relationships to understand database design and optionally include sample data for context.
    MIT
  • Analyze JavaScript code structure, dependencies, and patterns in Bitcoin Stamps to identify security risks, performance issues, and recursive relationships.
    MIT
  • Generate a grounded implementation plan for a repository task by analyzing code context, dependencies, and structure.
    MIT
  • Extract a structural outline from Python files—imports, classes, functions, docstrings—to simplify code review, navigation, and documentation.
    MIT
  • Returns the complete character relationship network for any open Scrivener project, enabling graph rendering and cast structure analysis.
    AGPL 3.0
  • Execute Python code with flexible execution modes including inline for speed and subprocess for isolation. Use to run Python scripts, test code snippets, or maintain session state across executions.
    MIT
  • Retrieve raw HTML source code from a page or a specific container for analyzing attributes, nesting, and debugging SSR or markup issues.
    MIT
  • Scan a repository for potential bugs using AST pattern matching across 10 languages. Detects issues like mutable default arguments, bare excepts, unreachable code, and empty catch blocks.
    MIT
  • Scan a Python repository to identify dead code and dependency issues without modifying files. Returns a human-readable report so you can fix problems safely.
    MIT
  • Fetches code from a GitHub repository URL and combines it into a single file. Filter by directory, extension, branch, or specific file to retrieve only the needed code.
    MIT