How does this skill improve vector search performance?

It provides specific rules for tuning the 'numCandidates' parameter, implementing vector quantization to reduce RAM usage, and utilizing dedicated Search Nodes.

Why is this skill necessary if Claude already knows MongoDB?

AI models often have outdated knowledge of Atlas Vector Search's evolving syntax. This skill provides the most current, verified rules to prevent errors and inefficient query patterns.

Does it support hybrid search patterns?

Yes, it includes patterns for combining vector and text search using MongoDB 8.0+ features like $rankFusion and $scoreFusion.

What version of MongoDB is required for this skill?

This skill is designed for MongoDB 7.0.2 and later, which introduced the $vectorSearch aggregation stage and dedicated vector search capabilities.

MongoDB Vector Search & AI

Name: MongoDB Vector Search & AI
Author: romiluz13

byromiluz13

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Database Management

Integrates MongoDB Atlas Vector Search and RAG patterns with Claude for building high-performance, AI-driven applications.

The MongoDB AI skill provides 33 expert-curated rules to bridge the gap between Claude's general knowledge and the rapidly evolving MongoDB Atlas Vector Search ecosystem. It offers precise guidance on implementing semantic search, Retrieval-Augmented Generation (RAG), and hybrid search patterns while avoiding common pitfalls related to outdated syntax. Whether you are defining complex vector indexes with quantization, tuning query performance via the '20x rule', or designing persistent memory for AI agents, this skill ensures your code follows current MongoDB best practices for production-grade AI features.

Key Features

018 GitHub stars

02Advanced $vectorSearch query optimization and parameter tuning

03Precise vector index definitions for HNSW and scalar/binary quantization

04Hybrid search implementation using $rankFusion and $scoreFusion

05AI agent memory schema design for short-term and long-term storage

06Standardized RAG patterns for context retrieval and metadata filtering

Use Cases

01Building semantic search engines with Atlas Vector Search

02Implementing robust RAG pipelines for LLM-powered applications

03Optimizing vector query latency and memory usage in production

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add romiluz13/mongodb-agent-skills mongodb-ai

For use in Claude.ai and ChatGPT

Download Skill