"AI tools for debugging Python code" matching MCP servers:

MCP server that allows Claude AI to interact directly with MySQL databases, enabling query execution and table information retrieval through natural language.

Enables execution of Python code in a safe environment, including running scripts, installing packages, and retrieving variable values. Supports file operations and package management through pip.

An MCP server for securely executing Python code, supporting STDIO, Streamable HTTP, and SSE transports, with easy deployment on Heroku.

Controls a running Chrome/Chromium browser via the Chrome DevTools Protocol, enabling navigation, JavaScript evaluation, tab management, and raw CDP commands through MCP tools.

Enables AI agents to subscribe to a deterministic daily ethics feed drawn from a four-module curriculum and retrieve read-only tools, resources, and reflection prompts covering principles, case studies, and codes of conduct.

Provides 63 production-ready API tools for AI agents, including web scraping, AI generation, crypto data, OCR, image generation, audio transcription, text-to-speech, email, and domain lookup.

Free Industry 4.0 / IIoT tools, no API key or account: lint MQTT Sparkplug B topics, check a Unified Namespace (UNS) for naming and hierarchy problems, and run an industrial AI-readiness diagnostic for manufacturing digital transformation and smart-factory projects. Works in Claude Code, Codex and any MCP client.

Enables querying real-time adoption metrics, trends, and comparisons for popular AI coding tools like OpenAI SDK, Anthropic SDK, Cursor, GitHub Copilot, and LangChain through natural language.

MCP server that gives AI agents isolated, named Linux computers with stable IDs and lifecycle control. Supports multiple backends like Docker, Fly Machines, Modal, and E2B, with a dashboard for managing sandboxes.

Enables deterministic calculations for AI API and subscription costs, meeting time zones, recurring schedules, and cron next-run previews, returning normalized inputs, units, assumptions, dated sources, and links to results.

A production-grade MCP server providing a persistent Python REPL with multi-session support, sandboxing, and timeout protection, enabling LLM agents to execute Python code across multiple turns with variables that persist between calls.

A Model Context Protocol server that brings the capabilities of enigmapython library to LLMs, allowing them to encrypt and decrypt messages using historically accurate Enigma machine emulators

MCP server that connects any AI agent to MATLAB — execute code, async jobs, interactive Plotly plots, custom tools, and monitoring dashboard

A Model Context Protocol server that allows LLMs to interact with Python environments, execute code, and manage files within a specified working directory.

Integrates GitHub repository management and local file system access to enable AI agents to perform code reviews and manage pull requests. It provides tools for listing repositories, retrieving PR diffs, and searching or reading files within a specified workspace.

Integrates Jina AI Search Foundation APIs to provide web page content extraction and search capabilities. It supports automatic pagination, result caching, and both standard and VIP search endpoints for enhanced information retrieval.

Turns AI assistants into full-stack software engineers with 36 tools for cognitive reasoning, code validation, project scaffolding, and AI/IDE configuration generation across 130+ programming languages, databases, and frameworks.

Enables comprehensive security vulnerability scanning and code quality analysis for Python applications. Provides detailed reports with scoring, actionable suggestions, and comparison tracking specifically designed for backend developers working with frameworks like Django, Flask, and FastAPI.

Provides AI-powered tools to apply UX/UI best practices, Nielsen's heuristics, cognitive biases, and Material-UI patterns to React components. Enables automated application of responsive design, Apple design patterns, and complete UX guidelines through natural language commands.

Enables AI assistants to surgically extract and analyze code, reducing token usage and costs by up to 200x compared to reading entire files.