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orcaslicer-mcp

orcaslicer-mcp

by MaxEllis
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Get OrcaSlicer status

get_status
Read-only

Retrieve a read-only snapshot of the current OrcaSlicer session to orient before slicing or editing, check preset drift, unsaved edits, slice validity, and running slice state.

Instructions

Start here: a snapshot of the OrcaSlicer session (build or plugin, project, active presets and their unsaved edits, whether the last slice still holds); for slice numbers use get_slice_status.

Also lists which keys of each active preset are modified (dirty) and whether a slice is running. Read-only.

Call it first to orient before slicing or editing, to see which settings drift from their preset, or to check slice_result_valid before trusting earlier stats. On fork v2.4.2-mcp.15 and later project is {name, path, dirty}: path is empty until the project has been saved, and dirty says File > Save has something to write, so an agent knows when to save_project and when the user has been editing in the window. Older builds report project as the bare path string.

connected_to says in words which one answered: the OrcaSlicer MCP build, or backend: "plugin", the OrcaSlicer MCP plugin on stock OrcaSlicer: note says what it can do. Tell the user before attempting anything it cannot (loading models, slicing, renders, plates, projects, saving presets). When that plugin is older than the newest release, plugin_update says where to get the new one; pass its note on to the user.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_status"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.8

TDQS

A4.8/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations only declare readOnlyHint=true; the description goes well beyond that by disclosing version-conditional return shape (`project` is an object with name/path/dirty only on fork v2.4.2-mcp.15+, path empty until saved, otherwise a bare string), the meaning of `connected_to`, that `backend: "plugin"` implies missing capabilities, and that `plugin_update`/`note` carry user-facing guidance. This is exactly the kind of operational context annotations cannot express.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The lead sentence is front-loaded with the 'start here' directive and the core payload list, and every subsequent sentence carries distinct information (sibling routing, version-conditional shape, plugin limitations). It is dense and somewhat long, with version-specific branching that could be tightened, but no sentence is filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, so the description carries the burden of describing returns, and it does: top-level contents, the conditional `project` shape, `connected_to`, `note`, and `plugin_update`. It also flags a downstream dependency (checking slice_result_valid before trusting stats), leaving nothing critical unstated for a zero-parameter status tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, so there is nothing for the description to disambiguate; baseline is 4. Its extra text explains returned fields rather than inputs, which is valuable but belongs to contextual completeness rather than parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb-and-resource framing ('a snapshot of the OrcaSlicer session') and enumerates what the snapshot contains: build or plugin, project, active presets with unsaved edits, and last-slice validity. It explicitly routes numeric slice data to get_slice_status, so the agent can distinguish this from the sibling without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It states an explicit ordering rule ('Call it first to orient before slicing or editing'), three concrete situations that select this tool (orientation, detecting settings drift, validating slice_result_valid before trusting earlier stats), and names the alternative for slice numbers. It also tells the agent to warn the user before attempting capabilities the plugin lacks.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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