"A search for creating animations using Blender" matching MCP servers:

Lets agents see and drive a live 3D application session through its addon socket: viewport screenshots, turntable and multi-mode renders, scene and object inspection, arbitrary Python execution, GLB import/export and asset validation, plus rig, pose-deformation and silhouette-likeness checks. This lets an agent visually judge a 3D result instead of guessing.

Connects MCP-compatible assistants to Blender to read scene and selection context, and optionally execute user-requested Python through Blender's native API when explicitly enabled.

Enables LLM clients like Claude to control Blender remotely, including scene inspection, object creation/modification, and Python code execution, via a socket-based MCP server.

Enables executing Python scripts, rendering scenes, and controlling 3D objects in Blender via Claude, with support for Cycles and EEVEE engines.

Enables AI assistants to drive a live Blender session over MCP by creating and transforming primitives, building and assigning materials, inspecting scenes and objects, capturing viewport screenshots, and executing arbitrary bpy Python. Commands are relayed over a local TCP bridge to a Blender add-on and executed on Blender's main thread, supporting multiple simultaneous AI clients.

BlenderMCP connects Blender to AI agents via the Model Context Protocol, enabling direct 3D object manipulation, material application, asset downloads, and Python code execution with secure token-authenticated local communication.

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 agents to inspect, discover, and execute batched Blender operations, capture renders/previews, and run arbitrary Python scripts for full bpy workflows, with on-demand operation discovery and bounded payload summaries.

Enables natural language control of Blender via Claude by converting MCP JSON-RPC calls to Blender's custom TCP protocol for scene manipulation, object creation, and Python execution.

Enables AI assistants to control Blender via MCP tools for scene manipulation, material assignment, rendering, and Python script execution.

Enables natural language control of Blender 3D through local AI models, allowing MCP clients to create, modify, and render scenes, apply materials, and execute Python code in Blender.

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

Enables Large Language Models to access and manipulate Autodesk Revit models through a pyRevit-based bridge and the Model Context Protocol.

Connects Blender to AI assistants through the Model Context Protocol, enabling direct AI control of 3D modeling, scene creation, and manipulation via natural language.

Enables Claude AI to control Blender 3D through natural language commands for object creation, modification, deletion, and Python script execution.

Enables Claude AI to directly interact with and control Blender for rapid, natural language-based 3D modeling. Supports parametric design and relational design through direct Blender integration.

Gives LLM agents spatial awareness inside Autodesk Maya, enabling scene inspection and measurement, aesthetic and engineering audits, camera planning, checkpoint/rollback safety, asset import, and viewport or render previews. Agents can also execute arbitrary Python in Maya to build and verify 3D scenes against engineering rules instead of writing blind.

A Python MCP server that allows programmatic interaction to find torrents programmatically on ThePirateBay, Nyaa and YggTorrent.

Enables AI agents to invoke a local Stata installation, including a Windows Stata build under Wine on Linux and macOS, for regression analysis, econometrics, paper replication, and empirical research with command guards, resource monitoring, and automatic log capture.

Enables integration of Perplexity's AI API with LLMs, delivering advanced chat completion by utilizing specialized prompt templates for tasks like technical documentation, code review, and API documentation.