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Skills/hoodini/ai-agents-skills/mongodb
mongodb logo

mongodb

hoodini/ai-agents-skills
1K installs227 stars
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Installation

npx skills add https://github.com/hoodini/ai-agents-skills --skill mongodb

Summary

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.

SKILL.md

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/

Score

0–100
63/ 100

Grade

C

Popularity15/30

1,407 installs — growing adoption.

Completeness27/30

Documented: full SKILL.md body, description, one-line install. Missing: category/license metadata.

Trust15/25

Community skill with a public GitHub source repository you can review.

Freshness6/15

No update timestamp is tracked for this skill in our catalog.

Scored automatically from popularity, completeness, trust, and freshness — computed only from data in our catalog, never fabricated.

Proud of your score? Add this badge to your README.

Paste a snippet into your GitHub README. The badge updates automatically and links back to this page.

Mongodb skill score badge previewScore badge

Markdown

[![Mongodb skill](https://www.remoteopenclaw.com/skills/hoodini/ai-agents-skills/mongodb/badges/score.svg)](https://www.remoteopenclaw.com/skills/hoodini/ai-agents-skills/mongodb)

HTML

<a href="https://www.remoteopenclaw.com/skills/hoodini/ai-agents-skills/mongodb"><img src="https://www.remoteopenclaw.com/skills/hoodini/ai-agents-skills/mongodb/badges/score.svg" alt="Mongodb skill"/></a>

Mongodb FAQ

How do I install the Mongodb skill?

Run “npx skills add https://github.com/hoodini/ai-agents-skills --skill mongodb” in your terminal. The skill is added to your agent's skills directory and picked up automatically on the next run — no restart or extra configuration needed.

What does the Mongodb skill do?

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. The full SKILL.md on this page shows the exact instructions the skill gives your agent.

Is the Mongodb skill free?

Yes. Mongodb is a free, open-source skill published from hoodini/ai-agents-skills. As with any third-party skill, review the source repository before installing it into an agent with sensitive access.

Does Mongodb work with Claude Code and OpenClaw?

Yes. Skills use the portable SKILL.md format, so Mongodb works with Claude Code, OpenClaw, Codex, Hermes, and any other agent that reads SKILL.md skills.

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