sktime-mcp

The Semantic Engine for Time-Series Forecasting with LLMs.

Getting Started

• sktime-mcp
  • 👋 Who is this for?
  • 🔥 Key Features
  • ⚡ Quick Start
  • 📚 Documentation Map
  • 🚀 Get Started
• 🎯 Use Cases & Personas
  • 👤 User Personas
  • 📂 Loading Data
  • 📝 What You Can Get Out
  • 🔗 See Also
• 📘 User Guide
  • 🚀 Getting Started
  • How It Works
  • 🛠️ Core Capabilities
  • ⚡ Workflows
  • 💾 Data Management
  • 💡 Best Practices
  • ⚠️ Known Limitations
  • ❓ Troubleshooting

Features

• Usage Examples
  • 🔄 End-to-End Examples
  • 🛠️ Individual Tasks
  • 📋 MCP Tool Reference
• Data Source Support
  • Supported Data Sources
  • Quick Start
  • MCP Tools
  • Configuration Options
  • Data Validation
  • Installation
  • Examples
  • Architecture
  • Metadata
  • Error Handling
  • 💡 LLM Guidelines & Best Practices
  • Troubleshooting
• Background Job Management
  • Overview
  • Architecture
  • How It Works
  • Available Tools
  • Complete Workflow Example
  • Technical Details
  • Benefits
  • Comparison: Blocking vs Non-Blocking
  • When to Use Each
  • Future Enhancements
  • Troubleshooting

Development

• Architecture Diagram
  • New Data Flow
  • Component Interaction
  • Data Adapter Pattern
  • Data Validation Flow
  • Handle Management
  • Complete Workflow Example
• Complete Code Explanation: sktime-mcp
  • 📋 Table of Contents
  • Project Overview
  • Architecture
  • File-by-File Breakdown
  • How It All Works Together
  • Key Concepts
  • Summary
• Developer Guide
  • Development Prerequisites
  • Setup
  • Running The Server Locally
  • Running Tests
  • Standard Local Checks
  • Project Layout
  • Architecture Overview
  • Adding A New MCP Tool
  • Adding A New Data Source Adapter
  • Adding A Demo Dataset
  • Documentation Build
• API Reference
  • EstimatorNode
  • RegistryInterface
  • TagResolver
  • CompositionValidator
  • Executor
  • HandleManager
  • Server
  • Tools
  • Registry
  • Runtime
  • Composition

Indices and tables

• Index

• Module Index

• Search Page