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⇱ AI tools for debugging Python code | Glama

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AI tools for debugging Python code

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  • Why this server?

    Enables execution of Python code and supports interactive debugging sessions using command-line tools like LLDB and GDB, allowing AI assistants to programmatically control the debugging process.

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    Enables AI assistants to execute Python code with pexpect functionality for interactive debugging sessions with command-line tools like LLDB and GDB. Maintains a stateful Python session allowing programmatic control of interactive processes.
    Last updated
    74
    Apache 2.0

  • Why this server?

    Enables AI assistants to run and analyze pytest tests for debugging and comprehensive test automation workflows, which is essential for identifying and fixing Python code issues.

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    Enables AI assistants to run and analyze pytest tests for desktop applications through interactive commands. Supports test execution, filtering, result analysis, and debugging for comprehensive test automation workflows.
    Last updated
    2

  • Why this server?

    Focuses on providing LLM agents with secure, isolated sandbox environments to execute arbitrary Python code, crucial for testing potential fixes during the debugging process.

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    Enables LLM agents to execute arbitrary Python code in secure, isolated sandbox environments with automatic dependency management and file handling. Each code execution runs in a fresh virtual environment that gets destroyed after completion, providing safe and reproducible Python code execution.
    Last updated
    28
    MIT

  • Why this server?

    Provides an interactive Python REPL environment, allowing AI to execute and test snippets of Python code in real-time to debug logic errors.

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    Provides an interactive Python REPL environment that maintains persistent session state, allowing users to execute Python code and access session history.
    Last updated
    55

  • Why this server?

    Offers a safe, isolated Docker environment for users and LLMs to execute Python code and install necessary packages for testing and debugging without affecting the host system.

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    An interactive Python code execution environment that allows users and LLMs to safely execute Python code and install packages in isolated Docker containers.
    Last updated
    39
    Apache 2.0

  • Why this server?

    Dedicated to Python development tasks, including code analysis, file operations, and safe code execution, all of which are primary steps in debugging Python applications.

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    A Model Context Protocol server that enables AI assistants like Claude to perform Python development tasks through file operations, code analysis, project management, and safe code execution.
    Last updated
    9
    MIT

  • Why this server?

    Implements Claude Code functionality, allowing AI to analyze codebases, modify files, and execute commands—core capabilities required for debugging and fixing Python code.

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    An MCP server that implements Claude Code-like functionality, allowing the AI to analyze codebases, modify files, execute commands, and manage projects through direct file system interactions.
    Last updated
    15
    301
    MIT

  • Why this server?

    Specializes in analyzing code relationships, explicitly mentioning support for 'Python symbols,' which helps the AI understand code context and dependencies vital for tracking down bugs.

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    Enables querying and analyzing code relationships by building a lightweight graph of TypeScript and Python symbols. Supports symbol lookup, reference tracking, impact analysis from diffs, and code snippet retrieval through natural language.
    Last updated

  • Why this server?

    Exposes Python Rope refactoring capabilities for code analysis and restructuring, useful for improving code quality and applying fixes identified during the debugging process.

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    A Model Context Protocol server that exposes Python Rope refactoring capabilities to Claude Code, enabling safe symbol renaming, method extraction, code analysis, and more.
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    3