Provides Bambu Lab A1 mini printer workflows: slicing through installed Bambu Studio, inspecting the executable plate, uploading with checksum verification, confirming jobs via fresh printer telemetry, checking status, and launching prepared prints with safety and readiness checks.
Exports Blender scene objects for printing, including resolving the active scene’s Print collection, checking millimetres and mesh topology, and preserving the original model. Live export requires a running Blender MCP connection.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Bambu Workflow MCP Print the model in the current Blender scene's Print collection."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Model-aware Blender-to-printer workflows for Bambu Lab on Windows and macOS. Version 0.3.0.
Export Blender objects, check millimetres and mesh topology, slice with installed Bambu Studio, inspect the executable plate, upload with a full checksum verification and confirm the exact job through fresh printer telemetry. STL and supported 3MF projects are also accepted.
Jobs, source snapshots, launch intentions and printer locks survive MCP restarts. Retrying the same request cannot silently create a second print. Access codes stay in the operating system keyring.
Requirements: Python 3.12+, Git, installed Bambu Studio and a configured Bambu Lab printer on your local network. Live export additionally needs a running Blender MCP connection. Printer firmware and LAN permissions must permit local control; see setup.
git clone https://github.com/netuneed/bambu-workflow-mcp.git
cd bambu-workflow-mcp
python -m pip install build
python -m build --wheel
.\scripts\install.ps1 -WheelPath '.\dist\bambu_workflow_mcp-0.3.0-py3-none-any.whl' -Python python -InstallSkillThe installer creates a separate versioned environment under %LOCALAPPDATA%\BambuWorkflow\app. Bambu Studio, Blender and a Python interpreter are not bundled. Installation, updates and release ZIPs.
Run bambu-workflow configure in the installed environment, then bambu-workflow doctor and bambu-workflow install-codex. Configuration and persistent jobs live outside the checkout. Select a non-default configuration with BAMBU_WORKFLOW_CONFIG or --config.
Related MCP server: Blender MCP Server
Install the official Bambu Studio application and Python 3.12+, then:
git clone https://github.com/netuneed/bambu-workflow-mcp.git
cd bambu-workflow-mcp
python3 -m venv .build
.build/bin/python -m pip install build
.build/bin/python -m build --wheel
sh scripts/install.sh --python .build/bin/python --wheel-path dist/bambu_workflow_mcp-0.3.0-py3-none-any.whl --install-skillThe runtime is created under ~/Library/Application Support/BambuWorkflow/app/0.3.0. Access codes use the system keyring (Keychain on macOS). The installer reports the venv launcher path for Codex; it does not register the global Python interpreter. Installed application bundles under /Applications and ~/Applications, including Contents/Resources and Contents/resources, are discovered automatically.
Release ZIPs include a platform-specific installer. Dependencies download separately. For cameras using RTSPS, an optional ffmpeg executable is required; models using the TCP camera do not need it.
The printers share LAN protocols, with model-specific profiles, temperatures, storage routes, camera protocols and tool systems. list_models in MCP or bambu-workflow models shows exact operation support without reading printer credentials.
Models | Preparation | Automatic launch |
A1 mini, A1, P1P, P1S, X1, X1 Carbon, X1E | Supported | Single-material LAN workflow implemented |
P2S, H2S, A2L | Supported | Model-specific single-tool LAN workflow implemented |
H2D, H2D Pro, H2C | Single-material factory multi-tool profiles | Multi-tool launch adapter remains unavailable; launch using Bambu Studio |
X2D | Single-material factory multi-tool profile | Native eMMC uploader and multi-tool launch adapter remain unavailable |
Only A1 mini has physical launch evidence. Software coverage on another model is not a claim that hardware has been tested. Legacy models without live nozzle metadata require an explicit confirmation of the installed nozzle during setup; known live mismatches always block launch. Unknown models are rejected instead of silently using A1 mini settings. Detailed capabilities.
Install the included bambu-print skill, then ask:
$bambu-print Print the model in the current Blender scene's Print collection.For preparation only, ask to prepare or export. That does not authorize printing. An explicit print instruction covers normal checked preparation and launch.
The skill resolves the collection in the active scene, checks real slicer layers and preserves the original model. It never selects an old collection from another scene merely because it has the same base name.
Level | Behaviour |
Critical | Block launch. Invalid scale or mesh, oversized model, incompatible profile, unclassified slicer diagnostic, printer fault and missing physical bed readiness are blockers. Silence cannot override them. |
Medium | Keep the job prepared, describe the concern and offer a concrete optional change. If the owner does not answer after a reasonable opportunity and mandatory checks pass, continue with the original printable geometry. |
Clear | Continue the authorized print without another general approval. Informational notices do not force a review. |
An unanswered suggestion never authorizes scaling, cutting, remeshing or changing functional dimensions. Required repairs remain blocked. The skill handles the conversation; the server enforces mandatory checks and retains medium review across restarts. There is no unattended countdown that launches after a disconnected client.
The server speaks standard MCP over stdio:
python -m bambu_workflow.serverTools include list_models, prepare_print, print_model, print_assessment, start_prepared, job_status and mark_bed_ready. Supply one stable request_id per human instruction and reuse identical arguments on retries. A sent command is not proof of printing. An uncertain launch is reconciled, never blindly resent.
Usage and Python examples cover MCP clients and CLI calls. scripts/call_mcp.py lists tools by default; printing needs explicit arguments. Printer addresses are configurable.
Before every physical start, a human must observe a clear bed and the correct plate. A readiness token lasts at most 30 minutes and is consumed once. Camera images and idle status cannot prove an empty bed. A busy printer is never canceled to make room for another job.
The complete export, slice, upload and start path was exercised on A1 mini firmware 01.08.01.00 and Bambu Studio 02.08.02.61. One print reached its reported final layer and FINISH; a second independently reviewed model was launched and later stopped after reported bed detachment. Finished-part dimensions, strength and surface quality have not been certified. Validation.
One material per plate and stock Standard-flow nozzles are supported. High-flow variants and complex per-object 3MF modifiers are rejected. Self-intersections, minimum wall thickness, strength and physical collisions are not fully simulated. Multiple source shells become one slicer object; individual-object skipping is unavailable. AMS and individual pause, cancel, heat and fan commands have software tests but have not been hardware validated. Printer firmware, local-network permission and an installed compatible profile remain requirements.
python -m pip install -e ".[dev]"
python -m pytestRecovery · Capabilities · Protocol sources · Third-party notices
Own code: MIT. No access codes, printer addresses, private models, runtime state or proprietary network plugin are distributed. This project is not affiliated with Bambu Lab.
This server cannot be deployed
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