Skip to main content

OrcaSlicer MCP — drive OrcaSlicer from Claude or any MCP client: load models, tune settings, slice, analyze

Project description

OrcaSlicer MCP

PyPI Python License MCP Badge

Let Claude drive a real, running OrcaSlicer. It loads models, arranges the plate, tunes settings, slices, and reads the result back. Every change lands in the GUI while you watch.

This package is an MCP server: it bundles no model and talks to nothing but OrcaSlicer, at an address you configure, localhost by default. The model comes from your MCP client. If that client uses a hosted one, your conversation goes there as any chat does; your models, profiles, and gcode stay on the machine running the slicer. Point the client at a local model and nothing leaves at all.

What it can do

Settings

Read and write any of roughly 800 OrcaSlicer settings on the live config, for the whole plate or scoped narrower: get_config, set_config, find_config_keys, set_layer_height, set_height_range for a band of layers, and set_object_config for one object's overrides.

Knowing what the settings mean

An offline settings reference ships with the package, carrying the authoritative label, tooltip, type, range, enum, and default for each key, so describe_setting, search_settings, and compare_settings answer from OrcaSlicer's own source instead of guessing. consult composes curated slicing knowledge and your saved notes by topic, symptom, or goal.

check_profile_physics is a deterministic gate. It overlays proposed changes on the live config, runs flow, temperature, geometry, and cooling math, then returns ok, warnings, or blocked. Accelerations your printer cannot reach and speeds past the flow ceiling get caught before they reach a print.

Presets

list_presets, select_preset, get_preset_config, edit_preset, save_preset, rename_preset, delete_preset.

Slicing, and reading the result back

slice, slice_and_wait, apply_and_slice, cancel_slice, get_slice_status, get_slice_warnings, get_gcode.

get_slice_breakdown returns per-feature time, filament, and flow. OrcaSlicer shows the same information in the legend beside its preview, sized for a screen; this returns it as numbers an assistant can compare and act on:

role                    time      share   filament   mean flow
inner_wall              5m 41s    30.8%     6.43 g    16.0 mm3/s
outer_wall              3m 19s    18.0%     3.20 g    13.6 mm3/s
sparse_infill           3m 07s    17.0%     3.57 g    17.0 mm3/s
internal_solid_infill   2m 01s    11.0%     1.72 g    11.8 mm3/s
bridge                     52s     4.7%     0.26 g     4.4 mm3/s
support_interface          36s     3.2%     0.52 g    12.3 mm3/s
overhang_perimeter         28s     2.5%     0.13 g     3.7 mm3/s
internal_bridge            21s     1.9%     0.45 g    19.9 mm3/s
top_surface                19s     1.7%     0.29 g    12.5 mm3/s
brim                       12s     1.1%     0.21 g    14.7 mm3/s
bottom_surface              7s     0.7%     0.10 g    11.8 mm3/s
                        18m 24s            16.89 g

It answers which feature is eating the time without slicing repeatedly to find out. A prediction_check rides along and flags any role where the profile's requested speed got throttled at the flow ceiling.

Models and the plate

load_model (.stl, .obj, .3mf, plus .step and .stp on fork v2.3.2-mcp.3 and later), list_objects with each object's world-space bounding box and an on_plate flag, transform_object, duplicate_object, delete_object, arrange_plate, auto_orient, check_placement, diagnose_plate, get_job_status.

Plate renders

render_plate hands back a PNG, so the assistant can look instead of inferring from coordinates. A rotation reads instantly as a picture and barely at all as three Euler angles. Seven camera angles cover iso, top, front, left, right, rear, and bottom. Use frame="plate" to stand back for the whole bed, or frame="object" to lean in on the part. Requires fork v2.3.2-mcp.4 or later.

view="editor" view="preview"
A press-fit tube connector sitting on the bed The same part sliced, toolpaths coloured by feature role
Your models on the bed. Answers orientation, plate contact, and first-layer footprint. Sliced toolpaths coloured by feature role, so support placement is plain to see.

Live state and memory

get_status and watch_events report what the slicer is doing now. remember persists machine, user, and project facts for later sessions, as plain local files in ~/.orcaslicer-mcp/notes/, relocatable with ORCA_MCP_NOTES_DIR.

What you need

Stock OrcaSlicer ships without a control API, so a matching build does that half of the job.

  1. The OrcaSlicer MCP build. OrcaSlicer 2.3.2 with an embedded local API, token-authenticated and bound to localhost until you say otherwise. Get it from the releases page. If no binary is up for your platform yet, build the remote-api branch from source.
  2. This package (orcaslicer-mcp). The MCP server that connects your AI client to that build.

Updating: take new builds from the releases page, never from inside the app. The in-app updater offers stock OrcaSlicer, which drops the control API. Builds mcp.2 and later turn that updater off for you. On an older build, click Skip this Version if a "new version available" prompt appears.

Quickstart

Install uv first, because it provides the uvx command that runs the server. One line does it: curl -LsSf https://astral.sh/uv/install.sh | sh on macOS and Linux, or irm https://astral.sh/uv/install.ps1 | iex in PowerShell on Windows.

  1. Install the OrcaSlicer MCP build, launch it, and finish the one-time setup by picking your printer. A fresh install may show a “Bambu Network Plug-in Required” dialog. Click Skip for Now, since that plug-in only serves Bambu cloud printing. The control API starts once setup is finished.

  2. Open Preferences (Ctrl+P), go to Remote API, and tick Enable Remote API. Copy the token shown on that page. Access stays localhost-only unless you also switch on "Allow LAN access".

  3. Connect your MCP client.

    Claude Desktop: download orcaslicer-mcp-<version>.mcpb from the releases page and open the file. Claude Desktop offers to install it. Open the extension's settings afterwards, paste the token from step 2, and enable it.

    Ignore any guide that tells you to hand-edit claude_desktop_config.json. Current Claude Desktop builds rewrite that file themselves and drop added mcpServers entries, so the edit will not stick. The extension leaves the file alone and finds uvx by itself.

    Claude Code and other MCP clients: add the server to your client's MCP config. For Claude Code that means a project .mcp.json:

    {
      "mcpServers": {
        "orcaslicer": {
          "command": "uvx",
          "args": ["orcaslicer-mcp"],
          "env": {
            "ORCA_API_TOKEN": "<token from Preferences>"
          }
        }
      }
    }
    

    ORCA_API_URL defaults to http://127.0.0.1:13130. Set it only if you changed the port, or if OrcaSlicer runs on another machine with LAN access enabled there.

    macOS note for GUI clients other than Claude Desktop: apps launched from the Dock do not inherit your terminal's PATH, so "command": "uvx" can fail silently. Run which uvx in Terminal, then paste the full path it prints into "command". It is usually ~/.local/bin/uvx.

  4. Restart your client and ask: "Load benchy.stl, slice it with the current profile, and tell me the print time."

Security

  • The control API binds 127.0.0.1 only by default. LAN access is an explicit opt-in in Preferences.
  • Every request must carry the API token. OrcaSlicer generates it on first run and can regenerate it at any time.
  • The MCP server runs as a local stdio process and opens no connection except to OrcaSlicer. No telemetry.

Development

uv venv && uv pip install -e ".[dev]"
uv run pytest   # unit tests against a mock API, plus a guarded live smoke test

The live smoke test skips itself unless ORCA_API_URL and ORCA_API_TOKEN point at a running OrcaSlicer MCP build.

Protocol notes, design specs, and verification results live in docs/.

Privacy policy

The server talks to OrcaSlicer's local API at the address you configure, localhost by default, and to nothing else. It has no backend, so there is no service of ours for anything to reach. What leaves your machine is whatever your MCP client sends its model: the conversation, plus any settings or file contents you or the assistant put into it. Their terms govern that traffic, and it is the same traffic any other use of that client produces. A local model removes it entirely.

  • Data collection: none. The server collects nothing about you or your usage.
  • Usage and storage: models, settings, and gcode stay on the computer running OrcaSlicer, held in memory only for the duration of each request. The API token authenticates the server to OrcaSlicer, and your MCP client stores it. Claude Desktop keeps extension settings in the operating system's credential store.
  • Third-party sharing: none by this server, which has no analytics and no backend. Traffic between your client and its model provider sits outside this project and falls under their policies.
  • Data retention: the only data written to disk is notes you save yourself with remember, stored as plain files under ~/.orcaslicer-mcp/notes/. Read or delete them whenever you like. Delete the folder and nothing remains.
  • Contact: questions and concerns go in an issue.

Status

Early public release, soft launch. The server carries 183 unit tests and gets exercised on real print jobs. Prebuilt OrcaSlicer MCP builds cover Windows, macOS, and Linux on the releases page. Issues and reports are welcome.

License

AGPL-3.0, matching OrcaSlicer, from whose source the bundled settings schema derives. See LICENSE.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

orcaslicer_mcp-0.1.7.tar.gz (438.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

orcaslicer_mcp-0.1.7-py3-none-any.whl (141.7 kB view details)

Uploaded Python 3

File details

Details for the file orcaslicer_mcp-0.1.7.tar.gz.

File metadata

  • Download URL: orcaslicer_mcp-0.1.7.tar.gz
  • Upload date:
  • Size: 438.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.11.29 {"installer":{"name":"uv","version":"0.11.29","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}

File hashes

Hashes for orcaslicer_mcp-0.1.7.tar.gz
Algorithm Hash digest
SHA256 284e0d7dba964f0d5c354ac8e4fc6aa5e26e427d09f663dcdb39133837dd7d24
MD5 e36aa90f543d7dbd68bd34e095a19477
BLAKE2b-256 32bc1cb27a87fcf77e5c9f4f34ba6d9a0ea6a340f41ddf9fb508c512c9b6c803

See more details on using hashes here.

File details

Details for the file orcaslicer_mcp-0.1.7-py3-none-any.whl.

File metadata

  • Download URL: orcaslicer_mcp-0.1.7-py3-none-any.whl
  • Upload date:
  • Size: 141.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.11.29 {"installer":{"name":"uv","version":"0.11.29","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}

File hashes

Hashes for orcaslicer_mcp-0.1.7-py3-none-any.whl
Algorithm Hash digest
SHA256 f4e843ec66476bfd057e89258369234e9056d9eac940bb243b194adb361beac3
MD5 4c08135245327f7af445ff3f5c70e2d8
BLAKE2b-256 dd1fcbc8333e6c73e062f23dff5e0e889dcfde9c718709546527cf5c4e394143

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page