281 个 ・ 集成工具: MongoDB · 按人气排序
Projete esquemas de banco de dados robustos e escaláveis para SQL e NoSQL. Fornece diretrizes de normalização, estratégias de indexação, padrões de migração, design de restrições e otimização de desempenho. Garante integridade de dados, desempenho de consultas e modelos de dados mantíveis.
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Padrões abrangentes para criar, manter e gerenciar Registros de Decisões de Arquitetura (ADRs) que capturam o contexto e a lógica por trás de decisões técnicas significativas.
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Otimizador de banco de dados especializado em tuning de desempenho moderno, otimização de queries e arquiteturas escaláveis.
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Arquiteto de banco de dados especializado em design de camada de dados do zero, seleção de tecnologia, modelagem de schemas e arquiteturas de bancos de dados escaláveis.
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Write and maintain Architecture Decision Records (ADRs) following best practices for technical decision documentation. Use when documenting significant technical decisions, reviewing past architectural choices, or establishing decision processes.
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Use when designing, reviewing, modifying, migrating, optimizing, securing, operating, troubleshooting, or decommissioning data architectures across data model exploration, SQL, ISO SQL conformance, NoSQL, vector, graph, document, time-series, NewSQL, search, in-memory, SQLite, CDC/Debezium, DBMS storage/query/recovery internals, database incident prevention, hardware acceleration, cache, big-data, lakehouse, and warehouse systems.
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54 real design systems (Stripe, Linear, Vercel) as HTML/CSS.
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Comprehensive patterns for creating, maintaining, and managing Architecture Decision Records (ADRs) that capture the context and rationale behind significant technical decisions.
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Comprehensive patterns for creating, maintaining, and managing Architecture Decision Records (ADRs) that capture the context and rationale behind significant technical decisions.
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Expert database architect specializing in data layer design from scratch, technology selection, schema modeling, and scalable database architectures.
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MongoDB, Redis, Cassandra, DynamoDB, and distributed database patterns for scalable applications
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Expert database optimizer specializing in modern performance tuning, query optimization, and scalable architectures.
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Create a MongoDB CDC capture using flowctl. Use when setting up real-time streaming from MongoDB Atlas, DocumentDB, or self-hosted MongoDB. Use when user says "capture MongoDB", "stream from Mongo", "MongoDB CDC", or "connect MongoDB to Estuary".
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在授权渗透测试中挖掘 SQL/NoSQL 注入（SQLi、NoSQLi，含 WAF 绕过、盲注、堆叠查询、类型混淆注入）。当用户输入拼进 SQL/NoSQL 查询时使用——典型场景：id/搜索/排序/过滤参数、数组键当 SQL 片段、PHP 类型混淆、MongoDB `$where`/`$regex`、堆叠查询到 xp_cmdshell。适用目标类型 Web / REST API。触发场景包括用户说"测下 SQL 注入""这个参数能不能注入""盲注/时间注入试试""NoSQL/MongoDB 注入看一下"。输出：注入点 + 类型 + 证据的 finding（含 killed 记录）。
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Express/Fastifyを使用した本番環境対応のNode.jsバックエンドサービスを構築し、ミドルウェアパターン、エラーハンドリング、認証、データベース統合、APIデザインのベストプラクティスを実装します。Node.jsサーバー、REST API、GraphQLバックエンド、マイクロサービスアーキテクチャの作成時に使用してください。
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Build production-ready Node.js backend services with Express/Fastify, implementing middleware patterns, error handling, authentication, database integration, and API design best practices. Use when creating Node.js servers, REST APIs, GraphQL backends, or microservices architectures.
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Manage MongoDB Atlas Organizations as Azure ARM resources using Azure.ResourceManager.MongoDBAtlas SDK. Use when creating, updating, listing, or deleting MongoDB Atlas organizations through Azure M...
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Write and maintain Architecture Decision Records (ADRs) following best practices for technical decision documentation. Use when documenting significant technical decisions, reviewing past architect...
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Use when working with Mongodb — mongoDB database analysis, performance tuning, query optimization, and health monitoring. Covers collection analysis, index recommendations, aggregation pipelines, replica set health, Atlas cluster management, and slow query investigation.
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Write and maintain Architecture Decision Records (ADRs) following best practices for technical decision documentation. Use when documenting significant technical decisions, reviewing past architectural choices, or establishing decision processes.
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Trigger when the user asks for explanations of web development concepts, code breakdowns, or learning guidance.
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Serena MCP for project memory and code navigation. Use when managing Serena memories, navigating symbols, performing intelligent refactoring, or maintaining context/continuity across AI agent sessions.
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Guides MongoDB users through implementing and optimizing Atlas Search (full-text), Vector Search (semantic), and Hybrid Search solutions. Use this skill when users need to build search functionality for text-based queries (autocomplete, fuzzy matching, faceted search), semantic similarity (embeddings, RAG applications), or combined approaches. Also use when users need text containment, substring matching ('contains', 'includes', 'appears in'), case-insensitive or multi-field text search, or filtering across many fields with variable combinations. Provides workflows for selecting the right search type, creating indexes, constructing queries, and optimizing performance using the MongoDB MCP server.
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Generate read-only MongoDB queries (find) or aggregation pipelines using natural language, with collection schema context and sample documents. Use this skill whenever the user asks to write, create, or generate MongoDB queries, wants to filter/query/aggregate data in MongoDB, asks "how do I query...", needs help with query syntax, or discusses finding/filtering/grouping MongoDB documents. Also use for translating SQL-like requests to MongoDB syntax. Does NOT handle Atlas Search ($search operator), vector/semantic search ($vectorSearch operator), fuzzy matching, autocomplete indexes, or relevance scoring - use search-and-ai for those. Does NOT analyze or optimize existing queries - use mongodb-query-optimizer for that. Does NOT handle aggregation pipelines that involve write operations. Requires MongoDB MCP server.
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