"Python" matching MCP servers:

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.

A Model Context Protocol server for deep codebase understanding of Python projects, focusing on data analysis and scientific computing. It provides architectural analysis, pattern detection, dependency mapping, test coverage analysis, and AI-optimized context generation.

Generates GCP architecture diagrams, sequence diagrams, flow charts, and class diagrams using Python diagrams DSL via MCP.

Enables AI assistants to directly control Autodesk 3ds Max through natural language to create models, set materials, adjust lighting, and automate animations. It bridges the Model Context Protocol with 3ds Max via a TCP socket to execute Python and MAXScript commands.

Enables creation of infrastructure and architecture diagrams as code using the Python diagrams library, supporting 15+ cloud providers, 500+ node types, custom icons, and flowcharts with multiple output formats.

Architectural sensor for Python codebases. Scores structural health (modularity, acyclicity, depth, equality), detects import cycles, enforces YAML layer rules, and runs a snapshot/diff loop so AI-assisted edits do not silently regress structure.

MCP server for repository mapping, dependency analysis, and architecture diagram generation for JavaScript, TypeScript, and Python projects.

This MCP server enables AI models to analyze local Python codebases using abstract syntax trees, providing tools for file structure analysis, symbol search, import graphing, docstring auditing, and refactoring prompts without loading entire source files into context.

Enables inspection and analysis of project structures to detect languages, frameworks, entry points, and dependencies across multiple programming languages including Node.js, Python, PHP, Go, Java, and Rust.

Generate 25+ types of hand-drawn Excalidraw diagrams - flowcharts, sequence, architecture, mind maps, ER, UML, kanban, bar/line/radar charts - from structured input with Sugiyama auto-layout and CJK support. Reads and modifies .excalidraw files, exports SVG. Python, local, no API keys required.

An MCP server that generates professional infrastructure diagrams using the Python diagrams DSL, with first-class Azure support and GitHub Copilot integration for natural language diagram generation.

Enables users to control FreeCAD through natural language for creating, editing, and managing 3D objects and documents. It supports executing Python code, capturing screenshots of the workspace, and importing parts from the FreeCAD library.

An MCP server that designs software projects by drafting design documents with an LLM, refining them, answering questions, and creating projects via the AI2DEV API.

BlenderMCP enables Claude AI to directly interact with and control Blender for prompt-assisted 3D modeling, scene creation, and manipulation. It supports object and material control, scene inspection, and execution of Python code through natural language commands.

AI-assisted COBOL to modern stack bridge that parses COBOL programs, maps to Python/Java/Go, generates test harnesses, and plans migration for legacy mainframe modernization.

Enables creating, manipulating, and managing Mermaid diagrams with automatic saving and multi-format conversion from JSON, CSV, Python, Markdown, and plain text.

GOLEM-3DMCP implements the Model Context Protocol to give AI agents direct, programmatic control of Rhino 8 — create geometry, run booleans, drive Grasshopper, capture viewports, and execute arbitrary Python scripts, all through natural language. Works with Claude Code, Cursor, Windsurf, and any MCP-compatible host.

Enables generating GCP architecture, sequence, flow, and class diagrams using natural language or Python code via the diagrams library.

Connects ParaView to LLM assistants via the Model Context Protocol, enabling direct Python code execution and pipeline control within the ParaView GUI.

Enables interactive MATLAB development by allowing users to execute scripts and specific code sections, manage workspace variables, and capture generated plots. It integrates with the MATLAB Python Engine to provide persistent execution context for MCP-compatible clients.