1.1 KiB
1.1 KiB
Phase 1: Discovery & Language Selection
Purpose: Understand what the user wants to build and choose the right SDK
Questions to Ask
1. Server Purpose
- "What data source, tools, or workflows do you want to expose to AI?"
- Examples: "Access PostgreSQL database", "Search Jira tickets", "Format code"
2. Target AI Application
- Claude Desktop (most common)
- Custom AI application
- Multiple clients
3. Programming Language Preference
- TypeScript/Node.js (recommended for web APIs, JavaScript ecosystem)
- Python (recommended for data processing, ML workflows)
- Java/Spring AI (enterprise Java applications)
- Kotlin (Android/JVM applications)
- C#/.NET (Windows/Azure applications)
4. Capability Types Needed
- Tools: Functions AI can call (e.g., "get_weather", "search_database")
- Resources: Data AI can read (e.g., file contents, API responses)
- Prompts: Specialized templates for common tasks
Output
Clear understanding of:
- Server purpose
- Language choice
- Capabilities needed (tools/resources/prompts)
Transition
Proceed to Phase 2 (Project Structure Generation)