20 MongoDB Search & AI alternatives
MongoDB Search & AI: MongoDB's official skill for choosing between Atlas Search, Vector Search and Hybrid Search, then building the right indexes and queries for the use case. 20 agent skills do similar work, most sharing RAG, Search and Vector Search, ranked by how much they have in common with MongoDB Search & AI.
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by OpenSearch Project
Take an OpenSearch search application from requirements to a running cluster — BM25, dense and sparse vectors, hybrid retrieval, agentic search and RAG, with relevance evaluation built in.
Also: RAG, Search, Vector Search
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by Redis, Inc.
Redis' own guidance for FT.CREATE schema design, FT.SEARCH / FT.AGGREGATE / FT.HYBRID, HNSW vector similarity and RAG retrieval pipelines.
Also: RAG, Search, Vector Search
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by MongoDB
MongoDB's official data-modelling skill — embed-vs-reference decisions, relationship patterns and the anti-patterns that quietly wreck performance and cost.
Also: MongoDB, MongoDB Atlas
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by Brave
Brave's official search skill: one CLI that searches, scrapes and extracts in a single call, returning token-budgeted web content instead of a list of links.
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by MongoDB
MongoDB's official skill for connection pools and timeouts — it refuses to hand you numbers until it knows your deployment, workload and concurrency.
Also: MongoDB
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by Hugging Face
Train bi-encoders, rerankers, SPLADE sparse encoders and ColBERT multi-vector models with the loss, evaluator and template each type actually needs.
Also: Vector Search
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by Brave
Brave's official skill for the Brave Search API — ranked web results with snippets and thumbnails, freshness and SafeSearch filters, search operators, pagination, and Goggles for custom ranking.
Also: Search
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by Weaviate
Weaviate's official skill for searching and managing vector collections — hybrid, semantic and keyword search, schema inspection, filtered fetches and bulk imports.
Also: RAG
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by Qdrant
Qdrant's meta-skill: instead of shipping static docs, it loads the current official Qdrant skill tree live from skills.qdrant.tech and diagnoses from that.
Also: RAG
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by docling-project (IBM)
Parse, convert, chunk, and structurally analyze PDFs, DOCX, PPTX, HTML, and images with IBM's open-source Docling toolkit.
Also: RAG
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by NVIDIA
Deploy, configure and troubleshoot the NVIDIA RAG Blueprint from your agent — Docker Compose, Helm or library, with feature toggles for VLM, guardrails and agentic RAG.
Also: RAG
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by Oldcircle
Find where a photo was taken: EXIF, OCR, OpenStreetMap, skyline and satellite matching, with coordinates, error radius and evidence images.
Also in Development
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by AMD
AMD's official meta-skill: permanently reroutes an agent's image generation, text-to-speech and speech-to-text to a local Lemonade Server instead of a paid cloud API.
Also in Development
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by Microsoft
Microsoft's official Playwright skill — drives a real browser from the command line using accessibility snapshots and element refs, and plans, generates and heals Playwright tests.
Also in Development
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by Google Maps Platform
Google's official agent skill for writing production Maps Platform code — grounded in freshly fetched docs, with a demo key path that needs no billing account.
Also in Development
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by NVIDIA
Diagnoses wrong gradients in differentiable NVIDIA Warp programs by measuring first — comparing autodiff against finite differences on a shrunk reproduction before proposing any fix.
Also in Development
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by Google Workspace
Google's official skill for the gws CLI — drive Gmail, Drive, Calendar, Sheets, Docs, Chat and Admin APIs from an agent, with Model Armor screening.
Also in Development
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by Netlify
Netlify's official skill for zero-config managed Postgres — querying from Functions, Drizzle setup, migrations and per-preview database branches.
Also in Development, Data & Analytics
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by WordPress
Official WordPress skill for Gutenberg block work: block.json, attributes and serialization, dynamic rendering, and the deprecation path that keeps existing content valid.
Also in Development
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by thedotmack
Persistent cross-session memory for coding agents: hooks capture each session, a local SQLite + vector store compresses it, and a mem-search skill reads it back.
Also in Development
