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"""Tool definitions for the Datawrapper MCP server."""
from mcp.types import Tool
from .config import CHART_CLASSES
async def list_tools() -> list[Tool]:
"""List available tools."""
return [
Tool(
name="create_chart",
description=(
"⚠️ THIS IS THE DATAWRAPPER INTEGRATION ⚠️\n"
"Use this MCP tool for ALL Datawrapper chart creation.\n\n"
"DO NOT:\n"
"❌ Install the 'datawrapper' Python package\n"
"❌ Use the Datawrapper API directly\n"
"❌ Import 'from datawrapper import ...'\n"
"❌ Run pip install datawrapper\n\n"
"This MCP server IS the complete Datawrapper integration. All Datawrapper operations "
"should use the MCP tools provided by this server.\n\n"
"---\n\n"
"Create a Datawrapper chart with full control using Pydantic models. "
"This allows you to specify all chart properties including title, description, "
"visualization settings, axes, colors, and more. The chart_config should "
"be a complete Pydantic model dict matching the schema for the chosen chart type.\n\n"
"STYLING WORKFLOW:\n"
"1. Use get_chart_schema to explore all available options for your chart type\n"
"2. Refer to https://datawrapper.readthedocs.io/en/latest/ for detailed examples\n"
"3. Build your chart_config with the desired styling properties\n\n"
"Common styling patterns:\n"
'- Colors: {"color_category": {"sales": "#1d81a2", "profit": "#15607a"}}\n'
'- Line styling: {"lines": [{"column": "sales", "width": "style1", "interpolation": "curved"}]}\n'
'- Axis ranges: {"custom_range_y": [0, 100], "custom_range_x": [2020, 2024]}\n'
'- Grid formatting: {"y_grid_format": "0", "x_grid": "on", "y_grid": "on"}\n'
'- Tooltips: {"tooltip_number_format": "00.00", "tooltip_x_format": "YYYY"}\n'
'- Annotations: {"text_annotations": [{"x": "2023", "y": 50, "text": "Peak"}]}\n\n'
"See the documentation for chart-type specific examples and advanced patterns.\n\n"
'Example data format: [{"date": "2024-01", "value": 100}, {"date": "2024-02", "value": 150}]'
),
inputSchema={
"type": "object",
"properties": {
"data": {
"type": ["string", "array", "object"],
"description": (
"Chart data. RECOMMENDED: Pass data inline as a list or dict.\n\n"
"PREFERRED FORMATS (use these first):\n\n"
"1. List of records (RECOMMENDED):\n"
' [{"year": 2020, "sales": 100}, {"year": 2021, "sales": 150}]\n\n'
"2. Dict of arrays:\n"
' {"year": [2020, 2021], "sales": [100, 150]}\n\n'
"3. JSON string of format 1 or 2:\n"
' \'[{"year": 2020, "sales": 100}]\'\n\n'
"ALTERNATIVE (only for extremely large datasets where inline data is impractical):\n\n"
"4. File path to CSV or JSON:\n"
' "/path/to/data.csv" or "/path/to/data.json"\n'
" - Use only when inline data would be too large to pass directly\n"
" - CSV files are read directly\n"
" - JSON files must contain list of dicts or dict of arrays"
),
},
"chart_type": {
"type": "string",
"enum": list(CHART_CLASSES.keys()),
"description": "Type of chart to create",
},
"chart_config": {
"type": "object",
"description": (
"Complete chart configuration as a Pydantic model dict. "
"Must match the schema for the chosen chart_type. "
"Use get_chart_schema to see the full schema."
),
},
},
"required": ["data", "chart_type", "chart_config"],
},
),
Tool(
name="get_chart_schema",
description=(
"⚠️ DATAWRAPPER MCP TOOL ⚠️\n"
"This is part of the Datawrapper MCP server integration.\n\n"
"---\n\n"
"Get the Pydantic JSON schema for a specific chart type. This is your primary tool "
"for discovering styling and configuration options.\n\n"
"The schema shows:\n"
"- All available properties and their types\n"
"- Enum values (e.g., line widths, interpolation methods)\n"
"- Default values\n"
"- Detailed descriptions for each property\n\n"
"WORKFLOW: Use this tool first to explore options, then refer to "
"https://datawrapper.readthedocs.io/en/latest/ for detailed examples and patterns "
"showing how to use these properties in practice."
),
inputSchema={
"type": "object",
"properties": {
"chart_type": {
"type": "string",
"enum": list(CHART_CLASSES.keys()),
"description": "Chart type to get schema for",
},
},
"required": ["chart_type"],
},
),
Tool(
name="publish_chart",
description=(
"⚠️ DATAWRAPPER MCP TOOL ⚠️\n"
"This is part of the Datawrapper MCP server integration.\n\n"
"---\n\n"
"Publish a Datawrapper chart to make it publicly accessible. "
"Returns the public URL of the published chart. "
"IMPORTANT: Only use this tool when the user explicitly requests to publish the chart. "
"Do not automatically publish charts after creation unless specifically asked."
),
inputSchema={
"type": "object",
"properties": {
"chart_id": {
"type": "string",
"description": "ID of the chart to publish",
},
},
"required": ["chart_id"],
},
),
Tool(
name="get_chart",
description=(
"⚠️ DATAWRAPPER MCP TOOL ⚠️\n"
"This is part of the Datawrapper MCP server integration.\n\n"
"---\n\n"
"Get information about an existing Datawrapper chart, "
"including its metadata, data, and public URL if published."
),
inputSchema={
"type": "object",
"properties": {
"chart_id": {
"type": "string",
"description": "ID of the chart to retrieve",
},
},
"required": ["chart_id"],
},
),
Tool(
name="update_chart",
description=(
"⚠️ DATAWRAPPER MCP TOOL ⚠️\n"
"This is part of the Datawrapper MCP server integration.\n\n"
"---\n\n"
"Update an existing Datawrapper chart's data or configuration using Pydantic models. "
"IMPORTANT: The chart_config must use high-level Pydantic fields only (title, intro, "
"byline, source_name, source_url, etc.). Do NOT use low-level serialized structures "
"like 'metadata', 'visualize', or other internal API fields.\n\n"
"STYLING UPDATES:\n"
"Use get_chart_schema to see available fields, then apply styling changes:\n"
'- Colors: {"color_category": {"sales": "#ff0000"}}\n'
'- Line properties: {"lines": [{"column": "sales", "width": "style2"}]}\n'
'- Axis settings: {"custom_range_y": [0, 200], "y_grid_format": "0,0"}\n'
'- Tooltips: {"tooltip_number_format": "0.0"}\n\n'
"See https://datawrapper.readthedocs.io/en/latest/ for detailed examples. "
"The provided config will be validated through Pydantic and merged with the existing "
"chart configuration."
),
inputSchema={
"type": "object",
"properties": {
"chart_id": {
"type": "string",
"description": "ID of the chart to update",
},
"data": {
"type": ["string", "array", "object"],
"description": (
"Chart data. RECOMMENDED: Pass data inline as a list or dict.\n\n"
"PREFERRED FORMATS (use these first):\n\n"
"1. List of records (RECOMMENDED):\n"
' [{"year": 2020, "sales": 100}, {"year": 2021, "sales": 150}]\n\n'
"2. Dict of arrays:\n"
' {"year": [2020, 2021], "sales": [100, 150]}\n\n'
"3. JSON string of format 1 or 2:\n"
' \'[{"year": 2020, "sales": 100}]\'\n\n'
"ALTERNATIVE (only for extremely large datasets where inline data is impractical):\n\n"
"4. File path to CSV or JSON:\n"
' "/path/to/data.csv" or "/path/to/data.json"\n'
" - Use only when inline data would be too large to pass directly\n"
" - CSV files are read directly\n"
" - JSON files must contain list of dicts or dict of arrays"
),
},
"chart_config": {
"type": "object",
"description": (
"Updated chart configuration using high-level Pydantic fields (optional). "
"Must use Pydantic model fields like 'title', 'intro', 'byline', etc. "
"Do NOT use raw API structures like 'metadata' or 'visualize'. "
"Use get_chart_schema to see valid fields. Will be validated and merged "
"with existing config."
),
},
},
"required": ["chart_id"],
},
),
Tool(
name="delete_chart",
description=(
"⚠️ DATAWRAPPER MCP TOOL ⚠️\n"
"This is part of the Datawrapper MCP server integration.\n\n"
"---\n\n"
"Delete a Datawrapper chart permanently."
),
inputSchema={
"type": "object",
"properties": {
"chart_id": {
"type": "string",
"description": "ID of the chart to delete",
},
},
"required": ["chart_id"],
},
),
Tool(
name="export_chart_png",
description=(
"⚠️ DATAWRAPPER MCP TOOL ⚠️\n"
"This is part of the Datawrapper MCP server integration.\n\n"
"---\n\n"
"Export a Datawrapper chart as PNG and display it inline. "
"The chart must be created first using create_chart. "
"Supports high-resolution output via the zoom parameter. "
"IMPORTANT: Only use this tool when the user explicitly requests to see the chart image "
"or export it as PNG. Do not automatically export charts after creation unless specifically asked."
),
inputSchema={
"type": "object",
"properties": {
"chart_id": {
"type": "string",
"description": "ID of the chart to export",
},
"width": {
"type": "integer",
"description": "Width of the image in pixels (optional, uses chart width if not specified)",
},
"height": {
"type": "integer",
"description": "Height of the image in pixels (optional, uses chart height if not specified)",
},
"plain": {
"type": "boolean",
"description": "If true, exports only the visualization without header/footer (default: false)",
"default": False,
},
"zoom": {
"type": "integer",
"description": "Scale multiplier for resolution, e.g., 2 = 2x resolution (default: 2)",
"default": 2,
},
"transparent": {
"type": "boolean",
"description": "If true, exports with transparent background (default: false)",
"default": False,
},
"border_width": {
"type": "integer",
"description": "Margin around visualization in pixels (default: 0)",
"default": 0,
},
"border_color": {
"type": "string",
"description": "Color of the border, e.g., '#FFFFFF' (optional, uses chart background if not specified)",
},
},
"required": ["chart_id"],
},
),
]
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