postgresql-docker
PostgreSQL in containers - Docker, Kubernetes, production configs
PostgreSQL in containers - Docker, Kubernetes, production configs
Optimize PostgreSQL performance - EXPLAIN ANALYZE, indexing, query tuning
Generate production-ready Row Level Security (RLS) policies for Supabase tables with is_super_admin() bypass, proper USING/WITH CHECK, and common relationship patterns; use when creating RLS policies, securing tables, implementing data access controls, or securing storage buckets
数据库管理统一接口,支持 Supabase (PostgreSQL)、PlanetScale (MySQL)、Turso (SQLite) 等主流数据库服务。 提供连接管理、CRUD 操作、迁移、RLS 策略配置等功能。用于快速集成数据库到 Agent 系统。
Manages Firestore collections, document schemas, security rules, and NoSQL queries for the 32Gamers portal app catalog. Use when: performing CRUD operations on the apps collection, writing security rules, querying documents, handling Firestore errors, or designing document schemas.
Explore a MongoDB collection to learn its schema, field types, value distributions, and relationships
Ingests repository files into the ChromaDB vector store. Builds or updates the vector index from a manifest or directory scan using ingest.py. Use when new files need to be indexed or the vector store is out of date. <example> user: "Index these new plugin files into the vector database" assistant: "I'll use vector-db-ingest to add them to the vector store." </example> <example> user: "The vector store is missing recent files -- update it" assistant: "I'll use vector-db-ingest to re-index the changes." </example>
Memory management with AgentDB unification, HNSW indexing, vector search, and hybrid SQLite+AgentDB backend. Use when storing, searching, or managing agent memory, configuring memory backends, or performing semantic search across knowledge bases.
Aggregated search aggregator using Google CSE, GNews RSS, Wikipedia, Reddit, and Scrapling.
Unified search tool for Google, Wikipedia, Reddit, and RSS feeds with Redis caching. Use when user asks "search for X", "who is Y", "latest news on Z".
Serverless Redis-compatible key-value store via Upstash REST API -- edge-compatible, automatic JSON serialization, TTL-based caching
MongoDB with Mongoose ODM - schemas, models, queries, aggregation, indexes, TypeScript typing, connection management
Redis in-memory data store patterns with ioredis and node-redis -- caching, sessions, rate limiting, pub/sub, streams, queues, transactions, cluster
Serverless Redis-compatible key-value store via Upstash REST API -- edge-compatible, automatic JSON serialization, TTL-based caching
Elasticsearch patterns -- client setup, index management, search DSL, aggregations, vector search, bulk operations, deep pagination
MongoDB with Mongoose ODM - schemas, models, queries, aggregation, indexes, TypeScript typing, connection management
Redis in-memory data store patterns with ioredis and node-redis -- caching, sessions, rate limiting, pub/sub, streams, queues, transactions, cluster
Serverless Redis-compatible key-value store via Upstash REST API -- edge-compatible, automatic JSON serialization, TTL-based caching
Elasticsearch patterns -- client setup, index management, search DSL, aggregations, vector search, bulk operations, deep pagination
AIMS 데이터베이스 가이드. MongoDB, 컬렉션, 쿼리, DB, 스키마 작업 시 자동 사용
Performance patterns for Apollo caching, Redis, and CloudFront optimization