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

Enables LLMs to drive Blender through socket-based two-way communication, letting them create and modify 3D objects, apply materials, run Blender Python, and fetch or generate assets while visually verifying results. Supports prompt-assisted 3D modeling, scene creation, and manipulation.

Enables Claude to function as a full-stack software engineer with comprehensive development capabilities including project creation, database management, frontend/backend development, testing, deployment, and DevOps operations across multiple frameworks and technologies.

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.

Connects an AI client to a locally running Blender instance via a local MCP server plus addon, exposing scene queries, viewport previews and renders, file import/export, and script execution so the model can author its own modeling and material scripts. Defaults to a compact 12-tool script-oriented profile, with an optional compatibility mode exposing the full tool set.

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.

Enables AI clients to control Blender through its official MCP add-on: running arbitrary bpy code or background CLI jobs, auditing scenes and blend files, searching Blender API and manual docs, capturing screenshots and renders, and searching or importing free Poly Haven models, HDRIs and textures at real-world scale. All 28 tools are served over one stdio connection to a single Blender instance.

Enables AI agents to safely inspect, edit, and test code within a bounded repository environment to solve software engineering tasks and verify fixes.

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.

Build Blender scenes through 4 tools and 338 tokens of fixed context: on-demand operation schemas, batches of up to 100 edits, preview captures and permission-gated Python for full bpy access.

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.

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.

Lets an AI engine drive a Blender instance the user runs themselves over stdio JSON-RPC, enabling scene inspection, viewport capture and picking, sandboxed code execution, and gated asset search/import and 3D generation. Telemetry is disabled before import, outbound tools are withheld until per-run network consent, and VRAM gating plus a surface-policy tool report what is live and what a station has cleared.

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.

Connects an AI agent to Blender 5.2 LTS over stdio, letting it read the scene hierarchy, create and transform primitive meshes, assign Principled BSDF materials, delete objects, save .blend files, and run raw bpy scripts through 12 tools. A two-process socket bridge keeps bpy calls on Blender's main thread, so no pip packages or admin rights are needed inside Blender.

Enables AI agents to control a live Blender session for scene/object manipulation, rendering, code execution, and PolyHaven asset/texture management. It also supports runtime switching among Ollama, LM Studio, llama.cpp, OpenAI-compatible, and Azure backends.

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.

Lets AI agents drive a live Blender session — reading scene and object data, creating, modifying and deleting objects, setting materials, rendering images, executing code, and downloading PolyHaven assets. Prompts flow through a swappable, provider-agnostic LLM backend (Ollama, LM Studio, llama.cpp, OpenAI-compatible, Azure) that can be reconfigured at runtime without restarting.

Enables AI agents to control a live Blender session — inspecting and editing scenes, objects and materials, rendering images, executing code, and pulling PolyHaven assets — through MCP tools. It also routes prompts to a provider-agnostic LLM backend (Ollama, LM Studio, llama.cpp, OpenAI-compatible, or Azure) that can be switched at runtime.

Enables AI agents to control a live Blender session via MCP tools for scene and object operations, rendering, code execution, and PolyHaven asset management. It supports provider-agnostic LLM backends that can be configured at startup or switched at runtime.

Enables AI agents to control a live Blender session with scene/object manipulation, rendering, PolyHaven asset tools, and runtime-switchable LLM provider backends.

Enables AI agents to drive a live Blender session over MCP — inspecting scenes, creating, modifying and deleting objects, applying materials, rendering images, importing PolyHaven assets, and executing code — while routing prompts through a provider-agnostic LLM backend (Ollama, LM Studio, llama.cpp, OpenAI-compatible, Azure) that can be switched at runtime.

Enables AI agents to generate dimensionally accurate mechanical parts (gears, enclosures, brackets, assemblies) in headless Blender from plain-English specs or JSON parameters, then verify them against manifold, bounding-box and print-production gates and export glTF/STL assets. It also scaffolds interactive Three.js CAD viewer pages with orbit controls, wireframe toggles and exploded-view scrubbing.

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.

A simple MCP server implementation in TypeScript that communicates over stdio, allowing users to ask questions that end with 'yes or no' to trigger the MCP tool in Cursor.

Enables LLM routing through multiple providers (OpenAI, Anthropic, xAI) via LiteLLM and provides a bridge to Blender for 3D scene management, asset integration from PolyHaven/Sketchfab, and automation workflows. Combines unified text generation with comprehensive Blender integration through a persistent TCP connection.