"A guide to creating 3D models in Blender" matching MCP servers:

3D Printing MCP By OctoEverywhere

Lets AI assistants control the physical Return to Dark Tower board game tower via Bluetooth, enabling connection, calibration, sound, lights, drum rotation, seal breaking, and game sequences through natural language.

Enables MCP clients to submit, slice, and start 3D prints with configurable gates, preview approval, and monitoring, via a self-hosted print daemon.

Enables AI assistants to query Bambuddy-managed 3D printers' status, current prints, diagnostics, camera snapshots, and archived print sources, and to safely start prints via a two-stage confirmation token while keeping sensitive credentials out of MCP output.

Enables natural-language control of DG-LAB Coyote V2/V3 hardware from any MCP client, with QR pairing, real-time telemetry, waveform playback, and built-in safety limits.

Enables comprehensive control and monitoring of Bambu Lab 3D printers through Claude using local MQTT, FTPS, and X.509 authentication. Users can manage print jobs, monitor real-time status, handle filament through AMS, and adjust hardware settings like temperature and lighting.

Enables LLM agents to control Bambu Lab 3D printers via the bambu-gateway HTTP API, supporting printer listing, filament management, print session creation, and safe print initiation with user confirmation.

Enables remote cloud control and live LAN camera access for Bambu Lab 3D printers through 31 MCP tools.

An MCP server for controlling Bambu Lab 3D printers that enables users to manipulate STL files, slice 3MF files, and manage end-to-end print workflows directly from Claude. It provides real-time status monitoring, file management via FTPS, and printer control through MQTT for a focused, lean Bambu-only implementation.

Connects your Meticulous espresso machine to an LLM, enabling recipe generation from natural language, shot analysis, grinder dial-in, and a persistent shot diary through Claude.

Links IoT devices to AI large models using the MCP and MQTT protocols, enabling natural language control, real-time AI responses, and complex instruction execution for interconnected IoT devices.

A bridge connecting physical hardware with AI large language models through the Model Context Protocol (MCP), enabling natural language control of TCP devices.

A bridge that connects physical hardware devices with AI large language models via serial communication, allowing users to control hardware using natural language commands.

Enables AI models to interact with TagoIO IoT platform accounts, providing access to device management, real-time data analysis, and AI-powered code generation for IoT development workflows.

An integration server that connects AI models with ThingsPanel IoT platform, allowing AI assistants to interact with IoT devices through natural language for device control, data retrieval, and management operations.

Exposes a Home Assistant instance as an MCP tool set, running as a stateful agent on Cloudflare Workers, enabling clients to read entity states, call services, run scripts and automations, and send commands to phones.

This MCP server enables AI agents to read MQTT and Sparkplug B data via tools like list_topics, get_latest, and read_all, providing read-only access to latest sensor values.

A robot-control MCP server enabling LLMs to control Unitree robots and DJI Tello drones with mock and hardware backends, built-in routines, and sequence execution.

Enables LLMs to list, inspect, snapshot, and control Scrypted home-automation/NVR devices such as switches, locks, and cameras through natural language.

Enables users to manage and control their Plex media library through natural language commands in MCP-compatible AI clients. It supports searching content, managing playlists, tracking library statistics, and monitoring live viewing sessions.