"Information about Blender (software or appliance)" matching MCP servers:

Facilitates interactive software development planning by managing tasks, tracking progress, and creating detailed implementation plans through the Model Context Protocol.

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

Enables AI agents to drive a live Blender session over stdio, inspecting the scene graph, searching and calling operators, reading and writing RNA properties, rendering viewable images, and checkpointing or restoring the file across a multi-turn conversation. It also exposes gallery and scene-reset helpers so the agent can check its own work and start over cleanly.

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.

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.

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.

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.

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.

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

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.

An MCP server that enables AI agents to control Blender through natural language for 3D scene creation, animation, and rendering. It provides over 550 actions and direct Python execution via a bridge to a live local Blender session.

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.

MCP server that enables AI agents to analyze legacy code, plan and execute software migrations, generate modern source code, and validate production-ready artifacts through a multi-agent pipeline.

Enables users to generate complete, production-ready software projects from simple ideas by coordinating 8 specialized AI agents through the Model Context Protocol.

Enables AI assistants in Google Antigravity to drive Blender for 2D-image-to-3D reconstruction, running a multi-stage pipeline to analyze reference images, generate models, compare renders, refine geometry, and produce reports.

Connects Blender to Claude AI, enabling AI-assisted 3D modeling, scene creation, object manipulation, material control, and code execution directly in Blender through natural language prompts.

Connects Blender to AI through the Model Context Protocol to enable prompt-assisted 3D modeling and scene manipulation. It supports object creation, material control, and arbitrary Python code execution directly within the Blender environment.

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.

MCP server that integrates Blender with CSM.ai 3D assets and LLM agents, enabling AI-assisted 3D modeling and animation through natural language commands.

Enables AI agents to invoke registry-governed, fail-closed tools such as requesting child tasks in other domains, reporting results, querying a domain's context and contracts, and submitting or approving plans. All work is gated on real evidence (analysis, independent review, actual test runs), so a task can never be marked done without proof.

A Minecraft MCP Server powered by Mineflayer API. It allows to control a Minecraft character in real-time, allowing AI assistants to build structures, explore the world, and interact with the game environment through natural language instruction

A local MCP reasoning gate that enables structured engineering thought through step-by-step reasoning, branching, merging, validation, and quality metrics without calling external LLM APIs.

MCP server orchestrating API-first cross-review between Claude, ChatGPT Codex, Gemini, DeepSeek, Grok, and Perplexity with unanimous convergence gates.

The coordination layer for AI agent networks, providing persistent memory, task management, inter-agent messaging, and human oversight through native MCP tools.

Enables an autonomous agent wallet on Base to make payments, approve tokens, swap on Uniswap V3, Aerodrome, 0x and CoW Protocol, lend/borrow via Aave V3 and Morpho Blue, trade perps on Hyperliquid, and enforce risk policies via blacklists, caps, simulation, and audit logs.

Aziel Runtime is a node-meshed MCP software orchestration suite for digital forensics, auditing, provenance, research, intelligence-support, and secure agent workflows, with a single gated execution path, compartmentalized engines, verifiable receipts, temporal integrity, and explicit capability refusal. It is not merely an API aggregator or generic tool router.

Enables agents to get fast, calibrated probabilistic answers from Jev (Typesafe AI) to yes/no, scale, or choice questions about provided material, without using a generative model.

An improved implementation of persistent memory using a local knowledge graph with a customizable --memory-path. This lets Claude remember information about the user across chats.