"3D modeling tutorial for creating a table tennis bat in Blender" matching MCP servers:

An MCP server that exposes 218 Blender tools for full 3D modeling pipelines, with a LangGraph agent layer for planning, executing, observing, and reviewing modeling tasks with evidence-based verification.

Connects Blender to LLMs, enabling prompt-driven 3D modeling, scene creation, and manipulation through natural language.

Provides deterministic decision and constraint evaluation for AI agents. Supports ruleset validation, fact evaluation, and constraint checking via MCP tools.

Enables AI-assisted 3D modeling workflows by connecting Blender with LLMs and CSM.ai, allowing text-based editing, asset retrieval from CSM.ai sessions, and humanoid animation using Mixamo files.

Enables AI agents to fully control Blender through 50+ tools for 3D modeling, animation, materials, and scene management via HTTP endpoints.

Create 3D models in Blender using natural language via an MCP server that lets AI agents directly control Blender, enabling complex 3D scene creation through conversation.

Enables AI-driven 3D model generation and manipulation using OpenSCAD through natural language commands. Users can create primitives, apply transformations, perform boolean operations, and export models to various formats like STL and OBJ.

Enables AI assistants to analyze Blender 3D models for topology issues like n-gons and provide real-time improvement suggestions directly within Blender through an integrated add-on.

MCP server for generating print-ready 3D models from text descriptions via a multi-agent pipeline, enabling AI assistants to create and optimize STL files.

Enables AI agents to control Blender 3D through 27 tools for scene manipulation, materials, modifiers, animation, and rendering, with native Python integration built in Rust.

Enables interactive control of Blender for 3D scene manipulation, geometry creation, material application, and viewport rendering via natural language prompts through the Model Context Protocol.

Unreal-Blender MCP is a unified server for controlling both Blender and Unreal Engine via AI agents using the MCP (Machine Control Protocol) approach.

A Model Context Protocol server that allows management and execution of Blender Python scripts, enabling users to create, edit and run scripts in a headless Blender environment through natural language interfaces.

An MCP relay that adds a use_jev tool to every connected server, letting the Jev model autonomously select and execute tool calls while the calling model supplies any required text values. It enables agents to delegate multi-step tool use across all configured MCP servers through a single unified interface.

Connects Blender to Claude AI through the Model Context Protocol (MCP), allowing Claude to directly interact with and control Blender for AI-assisted 3D modeling, scene manipulation, and rendering.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

An MCP server for Blender that exposes a physics-verified optical bench as JSON, enabling AI agents to read ground-truth geometry and beam data, and drive the bench through alignment and corrections.

Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.

Enables AI coding agents to perform automated Blender UI testing, user-story validation, and computer-use workflows inside an isolated GPU-partitioned Windows 11 VM without disrupting the host desktop.

Self-host a realtime voice-call companion for coding agents. Exposes an MCP endpoint that agents can poll as an alternate input stream.