"A server that supports using a Python debugger for tasks like finding memory leaks" matching MCP servers:

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

An MCP (Model Context Protocol) server that enables interactive debugging with code instrumentation for AI coding assistants. Inspired by Cursor's debug mode.

Enables AI agents to perform step-through debugging of Python, JavaScript/Node.js, and Rust programs using the Debug Adapter Protocol, with support for breakpoints, variable inspection, and stack traces.

Enables coding agents to identify likely runtime failures in JavaScript and TypeScript by ranking risky files, tracing dependencies, analyzing logs, and obtaining independent model reviews with line-level reasons.

Enables comprehensive JavaScript code analysis and debugging using ESLint and custom pattern matching. Identifies syntax errors, potential bugs, code quality issues, and provides actionable fix suggestions for single files or entire projects.

An MCP server that connects to your React Native application debugger

Provides comprehensive debugging capabilities for Node.js and TypeScript applications with 25+ specialized tools, including breakpoint management, variable inspection, hang detection, CPU/memory profiling, and test framework integration.

Enables AI assistants to debug Node.js applications using Chrome DevTools Protocol. Provides comprehensive debugging capabilities including breakpoints, stepping, variable inspection, expression evaluation, and console monitoring.

This MCP server enables AI agents to inspect and control the native DOSBox-X debugger through bounded MCP tools, including breakpoint management, execution control, register/memory inspection, and disassembly for DOS program debugging and reverse engineering.

Validates AI-generated Python: syntax, lint, security scan and deterministic repair.

MCP server providing automated code linting, rule explanations, and configuration templates for wemake-python-styleguide, with structured violation reports and offline rule database.

Enables AI assistants to debug JavaScript and TypeScript applications by connecting to Chrome DevTools Protocol-compatible debuggers, allowing them to set breakpoints, step through code, inspect variables, and evaluate expressions with full source map support.

This MCP server provides direct access to ruff linting, formatting checks, and ty type-checking for Python projects, with token-efficient, structured output.

Analyzes Python code and provides guided refactoring suggestions without automatically modifying code.

Codebase Q&A agent with git-history awareness. Explore a repo with list_files, read_file, and search, plus git log, blame, and diff and a repo map to answer "why did this change?" questions. Runs locally as an MCP server for Claude Code and other MCP clients.

Exposes the 23 Gang of Four design patterns to AI coding agents for generation, canonical examples, AST-based detection, validation, and anti-pattern refactoring in Python codebases.

Enables deterministic static analysis of Python code, providing tools to inspect classes, functions, imports, dependencies, and more, without executing the code.

Enables agents to review Python dependency requirements and source code against a modernization catalog, returning structured guidance, import-level suggestions, and compatibility floors. It also lists available codemod recipes and previews their transformations as unified diffs, all read-only and without installing packages or executing supplied code.

MCP server with local vector search for your codebase. Smart indexing, semantic search, Git history — all offline.