Mongodb Search And Ai

作者 mongodb1e72df255e54Apache-2.0收錄於 2026年10月8日更新於 2026年10月8日

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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路徑大小類型
references/automated-embedding.md15.5 KBtext/markdown
references/hybrid-search.md23.1 KBtext/markdown
references/lexical-search-indexing.md19.5 KBtext/markdown
references/lexical-search-querying.md17.5 KBtext/markdown
references/vector-search.md18.7 KBtext/markdown
SKILL.md6.8 KBtext/markdown

來源與署名

來源:mongodb/agent-skills位於plugins/mongodb-atlas/skills/mongodb-search-and-ai提交1e72df2

授權條款: Apache-2.0

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