mcp-plotting-server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| logging | {} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| extensions | {
"io.modelcontextprotocol/ui": {}
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| quick_plotB | Build an interactive Plotly figure from tabular data and return it as JSON. Pass data as a list of records and choose a chart kind. The server constructs and validates the figure and returns it as a JSON string (the output of fig.to_json()). A frontend can parse the string and render it directly with plotly.js. Returning a string keeps the response a single text content block, which is robust across MCP clients and transports. |
| create_figureA | Construct and validate a Plotly figure from a full figure spec. Use this when you want full control over traces and layout. The server builds the figure, which surfaces schema errors, and returns it as a JSON string. |
| render_figure_htmlA | Render a Plotly figure spec to a standalone HTML document string. The returned HTML can be saved as a .html file or embedded directly. Use this when a consumer wants a portable, viewable artifact rather than the raw figure JSON. |
| describe_plotA | Build a Plotly figure from data and a natural-language description. An AI agent (Gemini, driven by opencode running on the server) writes and runs Python plotting code against the provided data to satisfy the description, then returns the resulting figure as JSON, the same shape quick_plot and create_figure return. Slower than the other tools because it runs a full code-generation loop, but it handles open-ended chart requests. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 4 tools
Each tool targets a distinct workflow: creating from full spec, from natural language, from quick template, and rendering to HTML. No overlap in purpose.
All tool names follow a consistent verb_noun pattern with lowercase and underscores: create_figure, describe_plot, quick_plot, render_figure_html.
Four tools cover the core workflows of figure creation (three input methods) and output rendering, which is well-scoped for a plotting server.
The set covers all main entry points for creating figures and provides HTML export. Minor gap: no direct export to static images, but the HTML output is versatile.