• Achieve Feature Parity: Bring functionality (status detail, file operations, direct printing where possible, preset handling) for OctoPrint, Klipper, Duet, Repetier, Prusa Connect, and Creality Cloud up to the level of robustness planned for the Bambu implementation.
• Implement Full Bambu MQTT Status: Refactor getStatus for Bambu to subscribe to MQTT reports and maintain real-time state.
• Implement Robust AMS Mapping: Replace placeholder logic; correctly parse and use AMS mapping from .3mf slicer config or user overrides for the MQTT print command.
• Implement .3mf Print Overrides: Add logic to the print_3mf tool to handle user-provided overrides (e.g., calibration flags) and potentially common slicer settings if feasible via MQTT/G-code.
• Calculate MD5 Hash: Add logic to calculate and include the MD5 hash of the .3mf file in the MQTT print command (optional but recommended by protocol).
• Refactor Bambu File Ops: Investigate replacing bambu-js FTP operations (getFiles, uploadFile) with direct MQTT methods if possible/stable, or contribute FTPS support to bambu-js.
• Add Preset Discovery Logic: Improve preset resource listing (currently lists based on potential filenames, could parse index files if they exist).
• Expand .3mf Support: Add .3mf printing support for other printer types where applicable.
• Error Handling & Reporting: Enhance MQTT error handling and reporting of print progress/completion.
• Testing: Conduct thorough runtime testing of all new Bambu features.

Table of Contents

• Description
• Features
• Installation
  • Prerequisites
  • Install from npm
  • Install from source
  • Running with Docker
    • Using Slicers with Docker
• Configuration
• Usage
• Supported Printer Management Systems
  • OctoPrint
  • Klipper (via Moonraker)
  • Duet
  • Repetier
  • Bambu Labs
    • Finding Your Bambu Printer's Serial Number and Access Token
    • Bambu Communication Notes (MQTT & FTP)
  • Prusa Connect
    • Setting up Prusa Connect
  • Creality Cloud
    • Setting up Creality Cloud
• Available Tools
  • STL Manipulation Tools
  • Printer Control Tools
  • Bambu-Specific Tools
• Available Resources
  • Printer Resources
  • Bambu Preset Resources
• Example Commands for LLM
• Bambu Lab Printer Limitations
• Limitations and Considerations
  • Memory Usage
  • STL Manipulation Limitations
  • Visualization Limitations
  • Performance Considerations
  • Testing Recommendations
• Appendix: MCP Safety Notes
• Badges
• License

Description

This is a server that allows MCP users to connect with the API endpoints of these 3D Printers:

• OctoPrint
• Klipper (Moonraker)
• Duet
• Repetier
• Bambu Labs
• Prusa Connect
• Creality/Ender

This server is a Model Context Protocol (MCP) server for connecting Claude with 3D printer management systems. It allows MCP to interact with 3D printers through the APIs of various printer management systems such as OctoPrint, Klipper (via Moonraker), Duet, Repetier, and Bambu Labs printers.

Note on Resource Usage: This MCP server includes advanced 3D model manipulation features that can be memory-intensive when working with large STL files. Please see the "Limitations and Considerations" section for important information about memory usage and performance.

Features

• Get printer status (temperatures, print progress, etc.)
• List files on the printer
• Upload G-code files to the printer
• Start, cancel, and monitor print jobs
• Set printer temperatures
• Advanced STL file manipulation:
  • Extend base for better adhesion
  • Scale models uniformly or along specific axes
  • Rotate models around any axis
  • Translate (move) models
  • Modify specific sections of STL files (top, bottom, center, or custom)
• Comprehensive STL analysis with detailed model information
• Generate multi-angle SVG visualizations of STL files
• Real-time progress reporting for long operations
• Error handling with detailed diagnostics
• Slice STL files to generate G-code
• Confirm temperature settings in G-code files
• Complete end-to-end workflow from STL modification to printing
• Print .3mf files directly on Bambu Lab printers (via MQTT command)
• Read Bambu Studio preset files (printer, filament, process) as resources

Installation

Prerequisites

• Node.js 18 or higher
• npm or yarn

Install from npm

npm install -g mcp-3d-printer-server

Install from source

git clone https://github.com/dmontgomery40/mcp-3d-printer-server.git
cd mcp-3d-printer-server
npm install
npm link  # Makes the command available globally

Running with Docker

You can also run the server using Docker and Docker Compose for a containerized environment.

1. Ensure you have Docker and Docker Compose installed.
2. Copy .env.example to .env and configure your settings.
3. Build and run the container:

   docker-compose up --build -d
   

Using Slicers with Docker

Please note that the default Docker setup cannot directly use a slicer installed on your host machine. Mounting the slicer executable directly from the host into the container is unreliable due to operating system and library differences between your host and the container.

The recommended approach is to install your preferred slicer inside the Docker image. This makes the container self-sufficient.

To do this, you will need to modify the Dockerfile. Here's a conceptual example of how you might add PrusaSlicer or OrcaSlicer (specific commands may vary depending on the slicer, its dependencies, and current Alpine packages):

# ... other Dockerfile commands ...

# Example: Install PrusaSlicer or OrcaSlicer (adjust command as needed)
# Check Alpine package repositories first (e.g., apk add prusaslicer or apk add orcaslicer)
# If not available, download and install manually (e.g., AppImage):
# RUN apk add --no-cache fuse # FUSE might be needed for AppImages
# RUN wget https://example.com/path/to/OrcaSlicer_Linux_Vxxxx.AppImage -O /usr/local/bin/orcaslicer && \
#     chmod +x /usr/local/bin/orcaslicer

# Set the SLICER_PATH env var accordingly in docker-compose.yml or when running
# Example for installed executable:
ENV SLICER_PATH=/usr/local/bin/orcaslicer 

# ... rest of Dockerfile ...

After modifying the Dockerfile, rebuild your image (docker-compose build). You'll also need to ensure the SLICER_PATH environment variable in your .env file or docker-compose.yml points to the correct path inside the container (e.g., /usr/local/bin/orcaslicer). Set SLICER_TYPE to orcaslicer as well.

Apologies for not including a specific slicer out-of-t