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704,896 tools. Updated 2026-10-26 10:41

"Python Code for Data Analysis" matching MCP tools:

  • Generate executable Python code for fitting parametric models to data using the ax_core.model_fitter JAX library. Describe your model and data, and receive code with an explanation of the approach.
    MIT
  • Static-analysis check on a Python lrvx strategy: AST parses, expected hooks present (on_trade / on_bar), no forbidden patterns (eval, exec, __import__ tricks). Use this before running user-authored strategy code. Does NOT execute the code.
    MIT
  • Scan Python code with Bandit to uncover security vulnerabilities including SQL injection, hardcoded secrets, and unsafe functions.
    MIT No Attribution
  • Execute Python code in a restricted subprocess to deterministically verify math, logic, and code analysis tasks using symbolic engines.
    Apache 2.0

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  • Retrieve detailed information about a Panther data model, including Python body code and UDM mappings for security monitoring analysis.
    Python
    Apache 2.0
  • Execute Python code with automatic retry and intelligent error analysis. On failure, it diagnoses the error, searches past solutions, and suggests fixes for robust execution.
    MIT
  • Run Python code locally on sensitive files to compute aggregates without exposing raw data. Returns masked, size-capped output for safe analysis.
    MIT
  • Detect resource leaks, security vulnerabilities, and logic flaws in Python code via static AST analysis. Use before committing or running to catch defects without executing code.
    MIT
  • 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
  • Audit Python code to detect deprecated APIs, version mismatches, and outdated patterns. Returns a report with severity levels and replacement suggestions.
    MIT
  • Export routing history to CSV or JSON for analysis in Excel, Python, R, or other data tools. Get a file path and record count to track model performance.
    MIT
  • Execute Python code on virtual computers to process data, manipulate files, and run scripts through the Orgo MCP Server.
    MIT
    Destructive
  • Execute Python code in a sandboxed environment using Gemini. Captures stdout, stderr, and execution results for analysis.
    MIT