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mongodb/mongodb-search-and-ai

引導 MongoDB 使用者實作與優化 Atlas Search(全文檢索)、Vector Search(語意搜尋)及 Hybrid Search(混合搜尋)解決方案。

mongodb-search-and-ai 是什麼?

此技能專為 MongoDB 使用者設計,協助其建立與優化進階搜尋功能。它涵蓋三種核心搜尋類型:Atlas Search(全文檢索,適用於自動完成、模糊比對、多面向搜尋)、Vector Search(語意搜尋,適用於嵌入向量與 RAG 應用程式)以及 Hybrid Search(結合前兩者的混合方法)。此外,此技能也適用於文字包含、子字串比對(如 'contains'、'includes'、'appears in')、不區分大小寫或多欄位文字搜尋,以及需要根據多種欄位組合進行過濾的場景。此技能提供完整的工作流程,引導使用者選擇合適的搜尋類型、建立索引、建構查詢,並透過 MongoDB MCP 伺服器進行效能調校,最終實現高效能、可擴展的搜尋解決方案。

相容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/mongodb/agent-skills/tree/main/skills/mongodb-search-and-ai

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說明文件

mongodb-search-and-ai 是做什麼的?

引導 MongoDB 使用者實作與優化 Atlas Search(全文檢索)、Vector Search(語意搜尋)及 Hybrid Search(混合搜尋)解決方案。當使用者需要為文字查詢(自動完成、模糊比對、多面向搜尋)建立搜尋功能、語意相似度(嵌入向量、RAG 應用程式)或結合兩者的方法時,請使用此技能。此技能也適用於文字包含、子字串比對('contains'、'includes'、'appears in')、不區分大小寫或多欄位文字搜尋,以及需要根據多種欄位組合進行過濾的場景。提供選擇正確搜尋類型、建立索引、建構查詢,並透過 MongoDB MCP 伺服器最佳化效能的工作流程。

Individual skills in this repo

This repo contains 5 individual skills — each has its own dedicated page.

mongodb/mongodb-connection

Optimize MongoDB client connection configuration (pools, timeouts, patterns) for any supported driver language. Use this skill when working/updating/reviewing on functions that instantiate or configure a MongoDB client (eg, when calling `connect()`), configuring connection pools, troubleshooting connection errors (ECONNREFUSED, timeouts, pool exhaustion), optimizing performance issues related to connections. This includes scenarios like building serverless functions with MongoDB, creating API endpoints that use MongoDB, optimizing high-traffic MongoDB applications, creating long-running tasks and concurrency, or debugging connection-related failures.

mongodb/mongodb-mcp-setup

Guide users through configuring key MongoDB MCP server options. Use this skill when a user has the MongoDB MCP server installed but hasn't configured the required environment variables, or when they ask about connecting to MongoDB/Atlas and don't have the credentials set up.

mongodb/mongodb-natural-language-querying

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.

mongodb/mongodb-query-optimizer

Help with MongoDB query optimization and indexing. Use only when the user asks for optimization or performance: "How do I optimize this query?", "How do I index this?", "Why is this query slow?", "Can you fix my slow queries?", "What are the slow queries on my cluster?", etc. Do not invoke for general MongoDB query writing unless user asks for performance or index help. Prefer indexing as optimization strategy. Use MongoDB MCP when available.

mongodb/mongodb-schema-design

MongoDB schema design patterns and anti-patterns. Use when designing data models, reviewing schemas, migrating from SQL, or troubleshooting performance issues caused by schema problems. Triggers on "design schema", "embed vs reference", "MongoDB data model", "schema review", "unbounded arrays", "one-to-many", "tree structure", "16MB limit", "schema validation", "JSON Schema", "time series", "schema migration", "polymorphic", "TTL", "data lifecycle", "archive", "index explosion", "unnecessary indexes", "approximation pattern", "document versioning".

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