MongoDB and Mongoose schema design, querying, aggregation pipelines, and performance optimization.
Works with
Covers both native MongoDB driver and Mongoose ODM with connection setup, CRUD operations, and graceful shutdown patterns
Schema design guidance including embedded vs. referenced documents, virtuals, validation, indexes, and text search configuration
Query operations with 20+ operators (comparison, logical, array, regex) plus find, update, and upsert patterns with query builders
Aggr
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionmongodbExecute the skills CLI command in your project's root directory to begin installation:
Fetches mongodb from hoodini/ai-agents-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate mongodb. Access via /mongodb in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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Build and query MongoDB databases with best practices.
npm install mongodb mongoose
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: '[email protected]' });
const user = await users.findOne({ email: '[email protected]' });
await users.updateOne({ _id: user._id }, { $set: { name: 'Alice Smith' } });
await users.deleteOne({ _id: user._id });
import mongoose from 'mongoose';
await mongoose.connect(process.env.MONGODB_URI!, {
maxPoolSize: 10,
serverSelectionTimeoutMS: 5000,
socketTimeoutMS: 45000,
});
// Connection events
mongoose.connection.on('connected', () => console.log('MongoDB connected'));
mongoose.connection.on('error', (err) => console.error('MongoDB error:', err));
mongoose.connection.on('disconnected', () => console.log('MongoDB disconnected'));
// Graceful shutdown
process.on('SIGINT', async () => {
await mongoose.connection.close();
process.exit(0);
});
import mongoose, { Schema, Document, Model } from 'mongoose';
interface IUser extends Document {
email: string;
name: string;
password: string;
role: 'user' | 'admin';
profile: {
avatar?: string;
bio?: string;
};
createdAt: Date;
updatedAt: Date;
}
const userSchema = new Schema<IUser>({
email: {
type: String,
required: [true, 'Email is required'],
unique: true,
lowercase: true,
trim: true,
match: [/^\S+@\S+\.\S+$/, '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);
// ✅ 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: [Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
jwynia/agent-skills
mindrally/skills
github/awesome-copilot
kostja94/marketing-skills
wispbit-ai/skills
mrgoonie/claudekit-skills
We added mongodb from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
mongodb has been reliable in day-to-day use. Documentation quality is above average for community skills.
Useful defaults in mongodb — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend mongodb for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Keeps context tight: mongodb is the kind of skill you can hand to a new teammate without a long onboarding doc.
I recommend mongodb for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
mongodb fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
mongodb has been reliable in day-to-day use. Documentation quality is above average for community skills.
Keeps context tight: mongodb is the kind of skill you can hand to a new teammate without a long onboarding doc.
Registry listing for mongodb matched our evaluation — installs cleanly and behaves as described in the markdown.
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