Skip to main content
Glama
Fervoyush
by Fervoyush

import_plot_config

Load saved plot configurations to recreate visualizations quickly. Modify specific parameters like data sources while preserving the original design structure for consistent plotting.

Instructions

Import and use a saved plot configuration.

Load a previously exported plot configuration and create a plot from it. You can optionally override specific parameters (like data_source) while keeping the rest of the configuration intact.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
config_pathYesPath to the saved configuration JSON file
overridesNoOptional overrides for config parameters (e.g., new data_source)

Implementation Reference

  • Implements the core logic for the import_plot_config tool: loads JSON config from file, applies optional overrides, and creates the plot by calling create_plot_handler.
    async def import_plot_config_handler(arguments: dict[str, Any]) -> list[TextContent]: """Handle import_plot_config tool calls.""" try: from pathlib import Path config_path = Path(arguments["config_path"]) overrides = arguments.get("overrides", {}) # Check if file exists if not config_path.exists(): return [ TextContent( type="text", text=f"Configuration file not found: {config_path}\n\nPlease check the path and try again.", ) ] # Load config from file with open(config_path, "r") as f: config = json.load(f) # Apply overrides if provided if overrides: config.update(overrides) # Create plot using the loaded config result = await create_plot_handler(config) # Prepend info about the config source original_message = result[0].text if result else "" new_message = f"""Plot created from imported configuration! Config file: {config_path} Overrides applied: {len(overrides)} parameter(s) {original_message}""" return [TextContent(type="text", text=new_message)] except json.JSONDecodeError as e: return [ TextContent( type="text", text=f"Invalid JSON in config file: {str(e)}\n\nPlease check that the file contains valid JSON.", ) ] except Exception as e: return [ TextContent( type="text", text=f"Error importing config: {str(e)}\n\nPlease check:\n- Config file is valid\n- All required fields are present", ) ]
  • Registers the import_plot_config tool in the MCP server with its description and input schema definition.
    Tool( name="import_plot_config", description="""Import and use a saved plot configuration. Load a previously exported plot configuration and create a plot from it. You can optionally override specific parameters (like data_source) while keeping the rest of the configuration intact.""", inputSchema={ "type": "object", "properties": { "config_path": { "type": "string", "description": "Path to the saved configuration JSON file", }, "overrides": { "type": "object", "description": "Optional overrides for config parameters (e.g., new data_source)", }, }, "required": ["config_path"], }, ),
  • Defines the input schema for the import_plot_config tool, specifying config_path as required and overrides as optional.
    inputSchema={ "type": "object", "properties": { "config_path": { "type": "string", "description": "Path to the saved configuration JSON file", }, "overrides": { "type": "object", "description": "Optional overrides for config parameters (e.g., new data_source)", }, }, "required": ["config_path"], },

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Fervoyush/plotnine-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server