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By vanman2024
Build a managed RAG pipeline using Google File Search API for document processing, chunking, and semantic search with Gemini AI
npx claudepluginhub vanman2024/ai-dev-marketplace --plugin rag-pipelineMulti-format document parsing and preparation for Google File Search - handles PDF, DOCX, HTML, Markdown with text extraction and metadata preparation
Google File Search API specialist for Python - creates stores, uploads documents, implements search and RAG using the official google-genai SDK
Google File Search API specialist for TypeScript/JavaScript - creates stores, uploads documents, implements search and RAG using the official @google/genai SDK
Document chunking implementations and benchmarking tools for RAG pipelines including fixed-size, semantic, recursive, and sentence-based strategies. Use when implementing document processing, optimizing chunk sizes, comparing chunking approaches, benchmarking retrieval performance, or when user mentions chunking, text splitting, document segmentation, RAG optimization, or chunk evaluation.
Multi-format document parsing tools for PDF, DOCX, HTML, and Markdown with support for LlamaParse, Unstructured.io, PyPDF2, PDFPlumber, and python-docx. Use when parsing documents, extracting text from PDFs, processing Word documents, converting HTML to text, extracting tables from documents, building RAG pipelines, chunking documents, or when user mentions document parsing, PDF extraction, DOCX processing, table extraction, OCR, LlamaParse, Unstructured.io, or document ingestion.
Google File Search API patterns for managed RAG with Gemini. Covers both TypeScript (@google/genai) and Python (google-genai) SDKs. Use when building File Search integrations, implementing RAG with Google AI, or when user mentions Google File Search, Gemini RAG, document indexing, or semantic search.
Uses power tools
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Build Retrieval-Augmented Generation pipelines
OpenRAG agent skills: guided installation and SDK integration helpers.
Google Gemini File Search for managed RAG with 100+ file formats. Use for document Q&A, knowledge bases, or encountering immutability errors, quota issues, polling failures. Supports Gemini 3 Pro/Flash (Gemini 2.5 legacy).
Local RAG system with embedded Multi-Agent Framework for Claude Code plugin
Universal documentation loading system with intelligent link extraction and parallel WebFetch for all plugins
LLM application development with LangGraph, RAG systems, vector search, and AI agent architectures for Claude 4.6 and GPT-5.4
Production-ready Celery distributed task queue with worker management, beat scheduling, monitoring (Flower), and framework integrations (Django, Flask, FastAPI)
OpenRouter SDK plugin - unified interface for 500+ LLM models with intelligent routing, cost optimization, and framework integrations (Vercel AI SDK, LangChain, OpenAI SDK, PydanticAI)
Comprehensive ElevenLabs AI audio integration for voice-enabled applications with TTS, STT, voice cloning, and Vercel AI SDK support
Comprehensive Supabase integration for AI applications with database, auth, storage, realtime, and vector search capabilities
Modular Vercel AI SDK development plugin with 13 specialized agents, parallel orchestration, and AI SDK v6 support. Features AI Elements (54 components), 107+ providers, Tools Registry, MCP integration, and full-stack app builder.
Central repository of 21 Claude Code plugins for AI-powered development - agents, SDKs, frontends, backends, and infrastructure.
Note: The
domain-plugin-builderhas been moved to its own standalone repository: https://github.com/vanman2024/domain-plugin-builder
The ai-dev-marketplace is a collection of Claude Code plugins that provide slash commands, specialized agents, and skills for building AI applications. Each plugin targets a specific technology and can be used independently or combined into full-stack solutions.
| Plugin | Description |
|---|---|
claude-agent-sdk | Build AI agents with Claude's Agent SDK (TypeScript/Python) |
google-adk | Google Agent Development Kit - Python, TypeScript, Go, Java |
a2a-protocol | Agent-to-Agent Protocol for multi-agent interoperability |
| Plugin | Description |
|---|---|
vercel-ai-sdk | Modular Vercel AI SDK with streaming, tool-calling, and multi-provider support |
openrouter | Unified interface for 500+ LLM models with intelligent routing and cost optimization |
elevenlabs | AI audio - TTS, STT, voice cloning, and Vercel AI SDK integration |
| Plugin | Description |
|---|---|
mem0 | AI memory management - Platform (hosted), Open Source (Supabase), MCP (OpenMemory) |
rag-pipeline | RAG toolkit with LlamaIndex, LangChain, pgvector, Pinecone, Chroma |
| Plugin | Description |
|---|---|
ml-training | ML training/inference on cloud GPUs (Modal, Lambda Labs, RunPod) with HuggingFace |
| Plugin | Description |
|---|---|
nextjs-frontend | Next.js 15 App Router with AI SDK, Supabase, shadcn/ui, SEO, marketing tools |
sveltekit-frontend | SvelteKit with Tailwind CSS v4, shadcn-svelte, Bun, HTML-to-Svelte migration |
mobile | React Native/Expo, PWA, responsive design, EAS Build, app store deployment |
website-builder | AI-powered sites with Astro, MDX, content-image-generation MCP, Supabase CMS |
| Plugin | Description |
|---|---|
fastapi-backend | Production FastAPI with async/await, Mem0, SQLAlchemy, PostgreSQL |
celery | Distributed task queue - workers, beat scheduling, Flower monitoring |
| Plugin | Description |
|---|---|
supabase | Database, auth, storage, realtime, pgvector for AI apps |
redis | Caching, sessions, rate limiting, pub/sub, AI embedding cache |
| Plugin | Description |
|---|---|
clerk | Authentication with OAuth, organizations, and billing |
payments | Stripe integration - checkout, subscriptions, webhooks with FastAPI/Next.js/Supabase |
| Plugin | Description |
|---|---|
resend | Email API - transactional, contacts, broadcasts, templates, webhooks |
| Plugin | Description |
|---|---|
plugin-docs-loader | Universal documentation loading with link extraction and parallel WebFetch |
git clone https://github.com/vanman2024/ai-dev-marketplace.git
cd ai-dev-marketplace
# From local clone
claude plugin install vercel-ai-sdk --project
# From GitHub directly
claude plugin install vercel-ai-sdk \
--source github:vanman2024/ai-dev-marketplace/plugins/vercel-ai-sdk
claude marketplace add ai-dev-marketplace \
--source github:vanman2024/ai-dev-marketplace
claude marketplace list ai-dev-marketplace
Each plugin follows a consistent structure:
plugins/{name}/
├── .claude-plugin/
│ └── plugin.json # Manifest (name, version, description)
├── commands/ # Slash commands (/plugin:command)
├── agents/ # Specialized AI agents
├── skills/ # Reusable knowledge/templates
├── docs/ # Static documentation
└── README.md
Combine plugins for complete solutions:
AI Chatbot:
vercel-ai-sdk + mem0 + supabase + nextjs-frontend + clerk
SaaS Platform:
nextjs-frontend + supabase + clerk + payments + redis + resend
Multi-Agent System:
claude-agent-sdk + a2a-protocol + celery + redis + supabase
Mobile App:
mobile + supabase + clerk + fastapi-backend
ML Pipeline:
ml-training + rag-pipeline + redis + fastapi-backend + supabase
Use the domain-plugin-builder:
/domain-plugin-builder:build-plugin my-plugin
This creates the full plugin structure with commands, agents, and skills.