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Build applications with Google's Gemini models, supporting multimodal content, function calling, and structured outputs across Python, JavaScript, Go, and Java. \n \n Access current Gemini 3 models (Pro, Flash, Pro Image) with 1M token context; legacy Gemini 2.x and 1.5 models are deprecated \n Supports text generation, image/audio/video understanding, function calling, structured JSON output, code execution, context caching, and embeddings \n Official SDKs available: google-genai (Python), @goo

RESTful CRUD operations for TypeSpec API plugins with routing, parameters, and adaptive cards. \n \n Supports GET, POST, PATCH, and DELETE operations with path, query, and body parameters for filtering, creation, and updates \n Includes adaptive card visualization for GET responses and confirmation dialogs for destructive operations (POST, PATCH, DELETE) \n Provides complete CRUD example with models, error handling, and multiple query parameter patterns \n Built-in testing prompts and best pract

Multi-platform market research data extraction via Apify Actors across Google Maps, Facebook, Instagram, Booking.com, and TripAdvisor. \n \n Supports 16+ specialized Actors covering location density, pricing, consumer behavior, hashtag trends, hospitality data, and review analysis \n Workflow guides users through Actor selection, schema fetching, preference configuration, and result export in CSV or JSON formats \n Requires Apify token authentication and Node.js 20.6+; includes error handling fo

Pythonic idioms, PEP 8 standards, type hints, and best practices for building robust Python applications. \n \n Covers core principles including readability, explicit code, EAFP exception handling, and modern type hints with generics and protocols \n Includes practical patterns for error handling, context managers, comprehensions, generators, dataclasses, and decorators with runnable examples \n Addresses concurrency patterns for I/O-bound (threading, async/await) and CPU-bound (multiprocessing)

Generate production-ready Kotlin MCP server projects with Gradle, official SDK, and typed tools. \n \n Scaffolds complete project structure with build.gradle.kts, package layout, and MCP server configuration using io.modelcontextprotocol:kotlin-sdk \n Includes 2–3 sample tools with JSON schema definitions, typed inputs/outputs, and error handling patterns \n Provides coroutine-based server setup with stdio transport, environment variable configuration, and kotlin-logging integration \n Includes

Production-ready FastAPI patterns with Pydantic v2, SQLAlchemy 2.0 async, and JWT authentication. \n \n Domain-based project structure, async database setup with SQLAlchemy 2.0, and dependency injection patterns for maintainable APIs \n Comprehensive JWT authentication with password hashing, token generation, and protected routes using OAuth2 \n Prevents 7 documented issues including form data validation bugs, background task overwrites, Pydantic v2 migration breaking changes, and async event lo

Generate production-ready MCP servers in Java with the official SDK, Maven or Gradle, and reactive streams. \n \n Scaffolds complete project structure with tools, resources, and prompts organized into separate handler classes \n Includes Maven and Gradle templates with MCP SDK, SLF4J logging, Project Reactor, and JUnit 5 dependencies \n Provides ready-to-use handler templates for tools, resources, and prompts with error handling and async Mono-based responses \n Generates test suite examples and

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Generate complete, production-ready MCP server projects in Swift with the official SDK. \n \n Scaffolds full project structure with Package.swift, source files organized by capability (Tools, Resources, Prompts), and unit tests \n Includes templates for main.swift with ServiceLifecycle integration, Server.swift configuration, and handler implementations for tools, resources, and prompts \n Provides example tool definitions (greet, calculate) and resource/prompt handlers with proper error handlin