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feat(mcp): MCP service implementation (PRs 3-9 consolidated) (#35877)
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Amin Ghadersohi
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superset/mcp_service/chart/prompts/create_chart_guided.py
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195
superset/mcp_service/chart/prompts/create_chart_guided.py
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# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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"""
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Chart prompts for visualization guidance
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"""
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import logging
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from superset.mcp_service.app import mcp
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from superset.mcp_service.auth import mcp_auth_hook
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logger = logging.getLogger(__name__)
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@mcp.prompt("create_chart_guided")
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@mcp_auth_hook
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async def create_chart_guided_prompt(
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chart_type: str = "auto", business_goal: str = "exploration"
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) -> str:
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"""
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AI-powered chart creation guide following Anthropic's agent design principles.
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This prompt implements:
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- Transparency: Clear reasoning at each step
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- Proactive Intelligence: Suggests insights before being asked
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- Context Awareness: Maintains conversational flow
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- Business Focus: Translates data into actionable insights
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- Validation: Verifies choices before proceeding
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- Natural Interaction: Conversational, not configuration-driven
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Args:
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chart_type: Preferred chart type (auto, line, bar, pie, table, scatter, area)
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business_goal: Purpose (exploration, reporting, monitoring, presentation)
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"""
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# Enhanced chart intelligence with business context
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chart_intelligence = {
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"line": {
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"description": "Time series visualization for trend analysis",
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"best_for": "Tracking performance over time, identifying patterns",
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"business_value": "Reveals growth trends, seasonality, and patterns",
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"data_requirements": "Temporal column + continuous metrics",
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},
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"bar": {
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"description": "Category comparison visualization",
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"best_for": "Ranking, comparisons, and performance by category",
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"business_value": "Identifies top performers, bottlenecks, and gaps",
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"data_requirements": "Categorical dimensions + aggregatable metrics",
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},
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"scatter": {
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"description": "Correlation and relationship analysis",
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"best_for": "Finding relationships, outlier detection, clustering",
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"business_value": "Uncovers hidden correlations and identifies anomalies",
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"data_requirements": "Two continuous variables, optional grouping",
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},
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"table": {
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"description": "Detailed data exploration and exact values",
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"best_for": "Detailed analysis, data validation, precise values",
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"business_value": "Provides granular insights and detailed reporting",
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"data_requirements": "Any combination of dimensions and metrics",
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},
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"area": {
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"description": "Volume and composition over time",
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"best_for": "Showing cumulative effects, stacked comparisons",
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"business_value": "Visualizes contribution and total volume trends",
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"data_requirements": "Temporal dimension + stackable metrics",
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},
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"auto": {
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"description": "AI-powered visualization recommendation",
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"best_for": "When you're not sure what chart type to use",
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"business_value": "Optimizes chart choice based on data characteristics",
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"data_requirements": "I'll analyze your data and recommend the best type",
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},
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}
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# Business context intelligence
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goal_intelligence = {
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"exploration": {
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"approach": "Interactive discovery and pattern finding",
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"features": "Filters, drill-downs, multiple perspectives",
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"outcome": "Uncover hidden insights and generate hypotheses",
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},
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"reporting": {
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"approach": "Clear, professional, and consistent presentation",
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"features": "Clean design, appropriate aggregation, clear labels",
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"outcome": "Reliable, repeatable business reporting",
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},
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"monitoring": {
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"approach": "Real-time tracking with clear thresholds",
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"features": "Alert conditions, trend indicators, key metrics",
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"outcome": "Proactive issue detection and performance tracking",
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},
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"presentation": {
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"approach": "Compelling visual storytelling",
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"features": "Engaging colors, clear messaging, audience-appropriate detail",
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"outcome": "Persuasive data-driven presentations for stakeholders",
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},
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}
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selected_chart = chart_intelligence.get(chart_type, chart_intelligence["auto"])
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selected_goal = goal_intelligence.get(
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business_goal, goal_intelligence["exploration"]
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)
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return f"""🎯 **AI-Powered Chart Creation Assistant**
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I'm your intelligent data visualization partner! Let me help you create charts.
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**Your Visualization Goal:**
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📊 **Chart Focus**: {chart_type.title()} - {selected_chart["description"]}
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🎯 **Business Purpose**: {business_goal.title()} - {selected_goal["approach"]}
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💡 **Expected Value**: {selected_chart["business_value"]}
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---
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## 🚀 My Intelligent Approach
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### **Phase 1: Data Intelligence** 📊
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I'll automatically analyze your dataset to understand:
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- **Data characteristics** (types, distributions, quality)
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- **Business relationships** (correlations, hierarchies, trends)
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- **Visualization opportunities** (what stories your data can tell)
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- **Performance considerations** (size, complexity, aggregation needs)
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*Why this matters: The right chart depends on your data's unique characteristics*
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### **Phase 2: Smart Recommendations** 🧠
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Based on your data analysis, I'll:
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- **Recommend optimal chart types** with confidence scores and reasoning
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- **Suggest meaningful metrics** that align with your business goal
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- **Identify interesting patterns** you might want to highlight
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- **Propose filters** to focus on what matters most
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*Why this matters: I'll spot opportunities you might miss and save you time*
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### **Phase 3: Intelligent Configuration** ⚙️
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I'll configure your chart with:
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- **Business-appropriate aggregations** (daily, weekly, monthly for time series)
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- **Meaningful labels and formatting** (currency, percentages, readable names)
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- **Performance optimizations** (appropriate limits, caching strategies)
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- **Visual best practices** (colors, scales, legends that enhance understanding)
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*Why this matters: Proper configuration makes charts both beautiful and actionable*
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### **Phase 4: Validation & Refinement** 🎯
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Before finalizing, I'll:
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- **Verify the chart answers your business question**
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- **Check data quality and completeness**
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- **Suggest improvements** based on visualization best practices
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- **Provide preview** so you can see exactly what you're getting
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*Why this matters: Great charts require iteration and validation*
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---
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## 🎬 Let's Begin Your Data Story
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I'm ready to be your proactive data exploration partner. Here's how we can start:
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**Option 1: Quick Start** ⚡
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Tell me: *"What business question are you trying to answer?"*
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(e.g., "How are our sales trending?" or "Which products perform best?")
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**Option 2: Dataset Exploration** 🔍
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I can show you available datasets: `list_datasets`
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Or explore a specific one: `get_dataset_info [dataset_id]`
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**Option 3: Visual Inspiration** 🎨
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Browse pre-built chart configurations: `superset://chart/configs` resource
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Perfect for when you want to see examples of great charts!
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**Option 4: Autonomous Discovery** 🤖
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Just point me to a dataset and say *"Find something interesting"*
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I'll explore autonomously and surface the most compelling insights!
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---
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💡 **Pro Tip**: Great charts combine business intuition with data analysis!
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**What's your data challenge today?** 🚀"""
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