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This skill should be used when user asks to "query MongoDB", "show database collections", "get collection schema", "list MongoDB databases", "search records in MongoDB", or "check database indexes".

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SKILL.md

name mongodb-usage
description This skill should be used when user asks to "query MongoDB", "show database collections", "get collection schema", "list MongoDB databases", "search records in MongoDB", or "check database indexes".

MongoDB Best Practices

MCP Limitation

This MCP operates in READ-ONLY mode. No write, update, or delete operations are possible.

Schema Design Patterns

Embedding vs Referencing

Embed when:

  • Data is accessed together frequently
  • Child documents are bounded (won't grow unbounded)
  • One-to-few relationships
  • Data doesn't change frequently

Reference when:

  • Data is accessed independently
  • Many-to-many relationships
  • Documents would exceed 16MB limit
  • Frequent updates to referenced data

Common Patterns

Subset pattern: Store frequently accessed subset in parent, full data in separate collection.

Bucket pattern: Group time-series data into buckets (e.g., hourly readings in one document).

Computed pattern: Store pre-computed values for expensive calculations.

Index Strategies

Index Guidelines

  • Index fields used in queries, sorts, and aggregation $match stages
  • Compound indexes support queries on prefix fields
  • Covered queries (all fields in index) are fastest
  • Too many indexes slow writes

Index Types

  • Single field: Basic index on one field
  • Compound: Multiple fields, order matters for queries
  • Multikey: Automatically created for array fields
  • Text: Full-text search on string content
  • TTL: Auto-expire documents after time period

ESR Rule

For compound indexes, order fields by:

  1. Equality (exact match fields)
  2. Sort (sort order fields)
  3. Range (range query fields like $gt, $lt)

Aggregation Pipeline

Performance Tips

  • Put $match and $project early to reduce documents
  • Use $limit early when possible
  • Avoid $lookup on large collections without indexes
  • Use $facet for multiple aggregations in one query

Common Stages

// Filter documents
{ $match: { status: "active" } }

// Reshape documents
{ $project: { name: 1, total: { $sum: "$items.price" } } }

// Group and aggregate
{ $group: { _id: "$category", count: { $sum: 1 } } }

// Sort results
{ $sort: { count: -1 } }

// Join collections
{ $lookup: { from: "orders", localField: "_id", foreignField: "userId", as: "orders" } }

Connection Best Practices

Connection String Formats

  • Atlas: mongodb+srv://user:pass@cluster.mongodb.net/database
  • Local: mongodb://localhost:27017/database
  • Replica set: mongodb://host1,host2,host3/database?replicaSet=rs0

Connection Pooling

  • Use connection pooling in applications (default in drivers)
  • Set appropriate pool size for your workload
  • Don't create new connections per request

Anti-Patterns to Avoid

  • Unbounded arrays: Arrays that grow without limit
  • Massive documents: Documents approaching 16MB
  • Too many collections: Use embedding instead
  • Missing indexes: Queries doing collection scans
  • $where operator: Use aggregation instead for security
  • Storing files in documents: Use GridFS for large files