Origin MCP

by ZNaiGaomu

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Python

Local

origin_plot

Create a table-based plot from Origin data by selecting chart kind, columns, style, and optional export.

Instructions

Create a table-based plot selected by kind.

A single parameterized entry point for common table plots and the Plot Type ID routes that each also have a dedicated origin_plot_* tool. For the common line/scatter/line_symbol/column routes, selected_cols uses the first column as X and the remaining columns as Y. A one-column selection is treated as Y-only. Matrix-range plots still use origin_plot_matrix_id.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`kind`	Yes	Table plot kind. The schema lists every compact-route kind supported by this tool.
`path`	Yes	Filesystem path consumed or produced by this tool; see the tool description.
`title`	No	Optional Origin page long name or graph title.
`graph_name`	No	Origin graph page name. Omit to use the active graph or create a new page.
`style_mode`	No	Graph styling policy: origin_default preserves the Origin template; nature applies the origin-mcp scientific preset.	origin_default
`export_path`	No	Optional output path for exporting the created graph.
`show_legend`	No	Legend visibility override; null uses cross-chart rules based on series count and chart type.
`palette_name`	No	Optional registered color palette name used by the selected style mode.
`selected_cols`	No	Column names or zero-based indexes to include in the plot.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 25, 2026

TDQS

A4.1/5.0

Behavior3/5

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

With no annotations, the description carries the full behavioral disclosure burden. It adds useful detail about selected_cols interpretation (first column as X, remaining as Y, one-column as Y-only), but it does not discuss side effects such as whether a new graph page is created, whether existing pages are modified, or what the path must point to.

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

Conciseness5/5

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

Three concise sentences that front-load the tool's purpose and then immediately address routing and selected_cols behavior. No filler or redundancy; every sentence earns its place.

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

Completeness3/5

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

Given the tool has 9 parameters and a 31-value enum, the description covers the core plot creation logic and selected_cols convention but leaves the required 'path' parameter unexplained ('see the tool description', yet the description never ties path to a table file). Other parameter interactions (style_mode, palette_name, export_path) are left entirely to schema definitions, which is acceptable but not comprehensive.

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?

Schema coverage is 100%, so the baseline is 3. The description adds extra meaning to selected_cols, explaining the X/Y column mapping that the schema's 'include in the plot' does not. It also frames the kind enum as a compact-route selector, enriching the schema's simple 'kind' description.

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 states a specific verb and resource ('Create a table-based plot selected by kind') and clearly distinguishes this generic entry point from dedicated origin_plot_* tools and origin_plot_matrix_id. It names the exact kind-based routing, making the tool's role unambiguous.

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

Usage Guidelines4/5

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

The description explicitly says matrix-range plots should use origin_plot_matrix_id, providing a clear when-not case, and mentions that dedicated origin_plot_* tools exist as alternatives for each route. However, it does not address when to prefer this over sibling origin_plot_auto, leaving some selection ambiguity.

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