mongodb
hoodini/ai-agents-skills
Work with MongoDB databases using best practices for schemas, queries, and aggregation pipelines.
What is mongodb?
MongoDB & Mongoose skill provides tools for building and querying MongoDB databases with best practices. Use it when designing schemas, writing queries, building aggregation pipelines, or optimizing database performance.
- Connect to MongoDB using native driver or Mongoose ODM
- Design schemas with validation, indexes, and embedded/referenced documents
- Execute CRUD operations with query builders and operators
- Build aggregation pipelines for data analysis and transformation
- Implement virtuals, text search, and complex filtering
- Handle connection pooling and graceful shutdown
How to install mongodb
npx skills add https://github.com/hoodini/ai-agents-skills --skill mongodb- Node.js runtime environment
- MongoDB instance or MongoDB Atlas cluster
- Environment variable MONGODB_URI configured
- npm packages: mongodb and/or mongoose installed
How to use mongodb
- 1.Install mongodb and/or mongoose packages via npm
- 2.Set MONGODB_URI environment variable with your connection string
- 3.Connect to MongoDB using MongoClient or mongoose.connect()
- 4.Define schemas with validation rules, indexes, and field types
- 5.Execute queries using find, updateOne, or aggregation pipelines
- 6.Use populate() for references or virtuals for computed fields
- 7.Close connections gracefully on application shutdown
Use cases
- Designing normalized vs denormalized document structures for different data patterns
- Writing complex queries with filters, sorting, pagination, and text search
- Building aggregation pipelines to analyze orders, user activity, or metrics
- Setting up indexes and optimizing query performance
- Implementing upserts and bulk updates for data synchronization
- Backend developers building Node.js applications
- Full-stack developers working with MongoDB databases
- Data engineers designing document schemas and pipelines
- DevOps engineers optimizing database connections and performance
mongodb FAQ
Embed when data is read together and doesn't grow unbounded (e.g., order items). Use references when data is large, shared, or changes independently (e.g., post author).
Create a text index on fields using userSchema.index({ name: 'text', 'bio': 'text' }), then query with { $text: { $search: 'query' } }.
lean() returns plain JavaScript objects instead of Mongoose documents, making queries faster when you don't need document methods.
Use nested populate syntax: .populate({ path: 'comments', populate: { path: 'author' } }) to populate references within populated documents.
Use $push to add elements, $pull to remove, $addToSet to add only if unique, and $all to match arrays containing all specified values.
Full instructions (SKILL.md)
Source of truth, from hoodini/ai-agents-skills.
name: mongodb description: Work with MongoDB databases using best practices. Use when designing schemas, writing queries, building aggregation pipelines, or optimizing performance. Triggers on MongoDB, Mongoose, NoSQL, aggregation pipeline, document database, MongoDB Atlas.
MongoDB & Mongoose
Build and query MongoDB databases with best practices.
Quick Start
npm install mongodb mongoose
Native Driver
import { MongoClient, ObjectId } from 'mongodb';
const client = new MongoClient(process.env.MONGODB_URI!);
const db = client.db('myapp');
const users = db.collection('users');
// Connect
await client.connect();
// CRUD Operations
await users.insertOne({ name: 'Alice', email: 'alice@example.com' });
const user = await users.findOne({ email: 'alice@example.com' });
await users.updateOne({ _id: user._id }, { $set: { name: 'Alice Smith' } });
await users.deleteOne({ _id: user._id });
Mongoose Setup
import mongoose from 'mongoose';
await mongoose.connect(process.env.MONGODB_URI!, {
maxPoolSize: 10,
serverSelectionTimeoutMS: 5000,
socketTimeoutMS: 45000,
});
// Connection events
mongoose.connection.on('connected', () => console.log('MongoDB connected'));
mongoose.connection.on('error', (err) => console.error('MongoDB error:', err));
mongoose.connection.on('disconnected', () => console.log('MongoDB disconnected'));
// Graceful shutdown
process.on('SIGINT', async () => {
await mongoose.connection.close();
process.exit(0);
});
Schema Design
Basic Schema
import mongoose, { Schema, Document, Model } from 'mongoose';
interface IUser extends Document {
email: string;
name: string;
password: string;
role: 'user' | 'admin';
profile: {
avatar?: string;
bio?: string;
};
createdAt: Date;
updatedAt: Date;
}
const userSchema = new Schema<IUser>({
email: {
type: String,
required: [true, 'Email is required'],
unique: true,
lowercase: true,
trim: true,
match: [/^\S+@\S+\.\S+$/, 'Invalid email format'],
},
name: {
type: String,
required: true,
trim: true,
minlength: 2,
maxlength: 100,
},
password: {
type: String,
required: true,
select: false, // Never return password by default
},
role: {
type: String,
enum: ['user', 'admin'],
default: 'user',
},
profile: {
avatar: String,
bio: { type: String, maxlength: 500 },
},
}, {
timestamps: true, // Adds createdAt, updatedAt
toJSON: {
transform(doc, ret) {
delete ret.password;
delete ret.__v;
return ret;
},
},
});
// Indexes
userSchema.index({ email: 1 });
userSchema.index({ createdAt: -1 });
userSchema.index({ name: 'text', 'profile.bio': 'text' }); // Text search
const User: Model<IUser> = mongoose.model('User', userSchema);
Embedded Documents vs References
// ✅ Embed when: Data is read together, doesn't grow unbounded
const orderSchema = new Schema({
customer: {
name: String,
email: String,
address: {
street: String,
city: String,
country: String,
},
},
items: [{
product: String,
quantity: Number,
price: Number,
}],
total: Number,
});
// ✅ Reference when: Data is large, shared, or changes independently
const postSchema = new Schema({
title: String,
content: String,
author: {
type: Schema.Types.ObjectId,
ref: 'User',
required: true,
},
comments: [{
type: Schema.Types.ObjectId,
ref: 'Comment',
}],
});
// Populate references
const post = await Post.findById(id)
.populate('author', 'name email') // Select specific fields
.populate({
path: 'comments',
populate: { path: 'author', select: 'name' }, // Nested populate
});
Virtuals
const userSchema = new Schema({
firstName: String,
lastName: String,
});
// Virtual field (not stored in DB)
userSchema.virtual('fullName').get(function() {
return `${this.firstName} ${this.lastName}`;
});
// Virtual populate (for reverse references)
userSchema.virtual('posts', {
ref: 'Post',
localField: '_id',
foreignField: 'author',
});
// Enable virtuals in JSON
userSchema.set('toJSON', { virtuals: true });
userSchema.set('toObject', { virtuals: true });
Query Operations
Find Operations
// Find with filters
const users = await User.find({
role: 'user',
createdAt: { $gte: new Date('2024-01-01') },
});
// Query builder
const results = await User.find()
.where('role').equals('user')
.where('createdAt').gte(new Date('2024-01-01'))
.select('name email')
.sort({ createdAt: -1 })
.limit(10)
.skip(20)
.lean(); // Return plain objects (faster)
// Find one
const user = await User.findOne({ email: 'alice@example.com' });
const userById = await User.findById(id);
// Exists check
const exists = await User.exists({ email: 'alice@example.com' });
// Count
const count = await User.countDocuments({ role: 'admin' });
Query Operators
// Comparison
await User.find({ age: { $eq: 25 } }); // Equal
await User.find({ age: { $ne: 25 } }); // Not equal
await User.find({ age: { $gt: 25 } }); // Greater than
await User.find({ age: { $gte: 25 } }); // Greater or equal
await User.find({ age: { $lt: 25 } }); // Less than
await User.find({ age: { $lte: 25 } }); // Less or equal
await User.find({ age: { $in: [20, 25, 30] } }); // In array
await User.find({ age: { $nin: [20, 25] } }); // Not in array
// Logical
await User.find({
$and: [{ age: { $gte: 18 } }, { role: 'user' }],
});
await User.find({
$or: [{ role: 'admin' }, { isVerified: true }],
});
await User.find({ age: { $not: { $lt: 18 } } });
// Element
await User.find({ avatar: { $exists: true } });
await User.find({ score: { $type: 'number' } });
// Array
await User.find({ tags: 'nodejs' }); // Array contains value
await User.find({ tags: { $all: ['nodejs', 'mongodb'] } }); // Contains all
await User.find({ tags: { $size: 3 } }); // Array length
await User.find({ 'items.0.price': { $gt: 100 } }); // Array index
// Text search
await User.find({ $text: { $search: 'mongodb developer' } });
// Regex
await User.find({ name: { $regex: /^john/i } });
Update Operations
// Update one
await User.updateOne(
{ _id: userId },
{ $set: { name: 'New Name' } }
);
// Update many
await User.updateMany(
{ role: 'user' },
{ $set: { isVerified: true } }
);
// Find and update (returns document)
const updated = await User.findByIdAndUpdate(
userId,
{ $set: { name: 'New Name' } },
{ new: true, runValidators: true } // Return updated doc, run validators
);
// Update operators
await User.updateOne({ _id: userId }, {
$set: { name: 'New Name' }, // Set field
$unset: { tempField: '' }, // Remove field
$inc: { loginCount: 1 }, // Increment
$mul: { score: 1.5 }, // Multiply
$min: { lowScore: 50 }, // Set if less than
$max: { highScore: 100 }, // Set if greater than
$push: { tags: 'new-tag' }, // Add to array
$pull: { tags: 'old-tag' }, // Remove from array
$addToSet: { tags: 'unique-tag' }, // Add if not exists
});
// Upsert (insert if not exists)
await User.updateOne(
{ email: 'new@example.com' },
{ $set: { name: 'New User' } },
{ upsert: true }
);
Aggregation Pipeline
Basic Aggregation
const results = await Order.aggregate([
// Stage 1: Match
{ $match: { status: 'completed' } },
// Stage 2: Group
{ $group: {
_id: '$customerId',
totalOrders: { $sum: 1 },
totalSpent: { $sum: '$total' },
avgOrder: { $avg: '$total' },
}},
// Stage 3: Sort
{ $sort: { totalSpent: -1 } },
// Stage 4: Limit
{ $limit: 10 },
]);
Pipeline Stages
const pipeline = [
// $match - Filter documents
{ $match: { createdAt: { $gte: new Date('2024-01-01') } } },
// $project - Shape output
{ $project: {
name: 1,
email: 1,
yearJoined: { $year: '$createdAt' },
fullName: { $concat: ['$firstName', ' ', '$lastName'] },
}},
// $lookup - Join collections
{ $lookup: {
from: 'orders',
localField: '_id',
foreignField: 'userId',
as: 'orders',
}},
// $unwind - Flatten arrays
{ $unwind: { path: '$orders', preserveNullAndEmptyArrays: true } },
// $group - Aggregate
{ $group: {
_id: '$_id',
name: { $first: '$name' },
orderCount: { $sum: 1 },
orders: { $push: '$orders' },
}},
// $addFields - Add computed fields
{ $addFields: {
hasOrders: { $gt: ['$orderCount', 0] },
}},
// $facet - Multiple pipelines
{ $facet: {
topCustomers: [{ $sort: { orderCount: -1 } }, { $limit: 5 }],
stats: [{ $group: { _id: null, avgOrders: { $avg: '$orderCount' } } }],
}},
];
Analytics Examples
// Sales by month
const salesByMonth = await Order.aggregate([
{ $match: { status: 'completed' } },
{ $group: {
_id: {
year: { $year: '$createdAt' },
month: { $month: '$createdAt' },
},
totalSales: { $sum: '$total' },
orderCount: { $sum: 1 },
}},
{ $sort: { '_id.year': -1, '_id.month': -1 } },
]);
// Top products
const topProducts = await Order.aggregate([
{ $unwind: '$items' },
{ $group: {
_id: '$items.productId',
totalQuantity: { $sum: '$items.quantity' },
totalRevenue: { $sum: { $multiply: ['$items.price', '$items.quantity'] } },
}},
{ $lookup: {
from: 'products',
localField: '_id',
foreignField: '_id',
as: 'product',
}},
{ $unwind: '$product' },
{ $project: {
name: '$product.name',
totalQuantity: 1,
totalRevenue: 1,
}},
{ $sort: { totalRevenue: -1 } },
{ $limit: 10 },
]);
Middleware (Hooks)
// Pre-save middleware
userSchema.pre('save', async function(next) {
if (this.isModified('password')) {
this.password = await bcrypt.hash(this.password, 12);
}
next();
});
// Post-save middleware
userSchema.post('save', function(doc) {
console.log('User saved:', doc._id);
});
// Pre-find middleware
userSchema.pre(/^find/, function(next) {
// Exclude deleted users by default
this.find({ isDeleted: { $ne: true } });
next();
});
// Pre-aggregate middleware
userSchema.pre('aggregate', function(next) {
// Add match stage to all aggregations
this.pipeline().unshift({ $match: { isDeleted: { $ne: true } } });
next();
});
Transactions
const session = await mongoose.startSession();
try {
session.startTransaction();
// All operations in the transaction
const user = await User.create([{ name: 'Alice' }], { session });
await Account.create([{ userId: user[0]._id, balance: 0 }], { session });
await Order.updateOne({ _id: orderId }, { $set: { status: 'paid' } }, { session });
await session.commitTransaction();
} catch (error) {
await session.abortTransaction();
throw error;
} finally {
session.endSession();
}
// With callback
await mongoose.connection.transaction(async (session) => {
await User.create([{ name: 'Alice' }], { session });
await Account.create([{ userId: user._id }], { session });
});
Indexing
// Single field index
userSchema.index({ email: 1 });
// Compound index
userSchema.index({ role: 1, createdAt: -1 });
// Unique index
userSchema.index({ email: 1 }, { unique: true });
// Partial index
userSchema.index(
{ email: 1 },
{ partialFilterExpression: { isActive: true } }
);
// TTL index (auto-delete after time)
sessionSchema.index({ createdAt: 1 }, { expireAfterSeconds: 3600 });
// Text index for search
postSchema.index({ title: 'text', content: 'text' });
// Geospatial index
locationSchema.index({ coordinates: '2dsphere' });
// Check indexes
const indexes = await User.collection.getIndexes();
Performance Tips
// Use lean() for read-only queries
const users = await User.find().lean();
// Select only needed fields
const users = await User.find().select('name email');
// Use cursor for large datasets
const cursor = User.find().cursor();
for await (const user of cursor) {
// Process one at a time
}
// Bulk operations
const bulkOps = [
{ insertOne: { document: { name: 'User 1' } } },
{ updateOne: { filter: { _id: id1 }, update: { $set: { name: 'Updated' } } } },
{ deleteOne: { filter: { _id: id2 } } },
];
await User.bulkWrite(bulkOps);
// Explain query
const explanation = await User.find({ role: 'admin' }).explain('executionStats');
MongoDB Atlas
// Atlas connection string
const uri = 'mongodb+srv://user:password@cluster.mongodb.net/dbname?retryWrites=true&w=majority';
// Atlas Search (full-text search)
const results = await Product.aggregate([
{ $search: {
index: 'default',
text: {
query: 'wireless headphones',
path: ['name', 'description'],
fuzzy: { maxEdits: 1 },
},
}},
{ $project: {
name: 1,
score: { $meta: 'searchScore' },
}},
]);
// Atlas Vector Search
const results = await Product.aggregate([
{ $vectorSearch: {
index: 'vector_index',
path: 'embedding',
queryVector: [0.1, 0.2, ...],
numCandidates: 100,
limit: 10,
}},
]);
Resources
- MongoDB Docs: https://www.mongodb.com/docs/
- Mongoose Docs: https://mongoosejs.com/docs/
- MongoDB University: https://learn.mongodb.com/
- Atlas Docs: https://www.mongodb.com/docs/atlas/
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