MongoDB

Build apps from MongoDB.
Just describe what you need.

Connect your MongoDB Atlas cluster. Describe the app you need. camelAI reads your collections, understands nested documents, and builds it.

users
{
"_id": ObjectId("64f1a2b3c8e9d1f2a3b4c5d6"),
"name": "Amara Chen",
"email": "amara@acme.io",
"role": "admin",
"profile": {
"avatar": "https://cdn.acme.io/avatars/amara.jpg",
"timezone": "US/Pacific",
"preferences": {
"theme": "dark",
"notifications": true
}
},
"teams": ["engineering", "platform"],
"loginHistory": [
{ "ts": "2026-03-12T09:14:00Z", "ip": "192.168.1.42" },
{ "ts": "2026-03-10T14:33:00Z", "ip": "10.0.0.7" }
],
"createdAt": ISODate("2025-08-14T00:00:00Z")
}

Your data is already flexible. Your tools should be too.

companies
idnameaddresstags
1Acme CorpNULLNULL
2Globex Inc123 Main StNULL
3Initech456 Oak Avesaas
NULLs everywhere
No nested data
Arrays? Add another table and JOIN
companies
{
"name": "Acme Corp",
"address": {
"street": "123 Main St",
"city": "San Francisco",
"state": "CA"
},
"tags": ["saas", "enterprise"],
"contacts": [
{ "name": "Jordan", "role": "CTO" },
{ "name": "Riley", "role": "VP Eng" }
]
}
Nested objects — address is structured, not a flat string
Optional fields — no NULLs, no wasted columns
Arrays inline — no extra tables, no JOINs

How it works

1

Connect your cluster

users
orders
products
mongodb+srv://admin:****@cluster0.abc12.mongodb.net
Connected
2

Ask in plain English

{
  "status": "premium",
  "plan": "pro",
  "signupDate": {
    "$gte": "2026-03-01"
  },
  "active": true
}

Show me all premium users who signed up this month

Building query...

No aggregation pipelines. No query syntax. Just describe what you want to see.

3

See rich results

NameEmailPlan
Amara C.amara@acme.ioPremium
Jordan K.jordan@globex.coPremium
Riley M.riley@initech.ioFree
Sam T.sam@startup.devPremium
Premium users
247
Plans
Pro
Free
Build app

What you can build from your collections.

Customer CRM

Search, filter, and manage customer records with nested contact history, notes, and activity timelines. Edit deeply nested profile fields inline.

db.users
Product Catalog

Browse products with faceted search across variant attributes — sizes, colors, pricing tiers. Detail pages with nested specs and inventory data.

db.products
Support Dashboard

Track open tickets by priority, monitor average resolution time, and let agents update ticket status. Threaded message history built in.

db.tickets

camelAI speaks your aggregation language.

Source
orders
42,817 documents
Stage 1
$match
status: "paid" and date >= 2025-01
Stage 2
$group
by month — SUM(total), AVG(value), COUNT
Stage 3
$sort
by total, descending
Result
Monthly revenue by category

Describe an aggregation in plain English. camelAI builds the pipeline, runs it, and visualizes the output.

What teams build with MongoDB + camelAI

users12.4K
orders8.2K
products1.3K
+ New Document

Admin panels for Atlas collections

Build admin panels that let your team browse, search, edit, and manage MongoDB collections — without writing CRUD boilerplate or deploying a Retool instance.

AC
Amara ChenProActive
amara@acme.io
P1Login failing on mobile2m ago
P2Can't export CSV reports1h ago
P3Feature request: dark mode3h ago

Customer support dashboards

Give your support team a dashboard that queries user records and tickets in real time. Search by email, filter by plan, and see the full customer picture — all from your MongoDB data.

{
"order": {
"items": [...],
"total": 529
}
}
docordermetaitemstotal

Visualize documents without aggregation pipelines

MongoDB's aggregation framework is powerful but complex. Skip the $match, $group, $unwind pipeline and just describe what you want to see — camelAI builds the visualizations.

Labeluser.name
Jordan Kim
Roleuser.role
Admin
Activeuser.active
Enabled
Save to collection

Internal tools for ops teams

Build internal tools that read from and write to your MongoDB collections. Forms, dashboards, approval workflows — describe what your ops team needs and ship it in an afternoon.

Frequently asked questions

What will you build from your documents?

Connect to our MongoDB Atlas cluster and build an admin panel for the users collection. I need search, filters by role and status, and the ability to edit nested profile fields.

Try this prompt

Our products collection has deeply nested variant data — sizes, colors, prices. Build a product catalog app with faceted search and a detail page for each product.

Try this prompt

Run an aggregation pipeline on our orders collection: group by month and category, calculate average order value, and visualize the trends as a line chart.

Try this prompt

Build a support dashboard from our tickets collection. Show open tickets by priority, average resolution time, and let agents update ticket status from the dashboard.

Try this prompt

Your documents are ready.

Start building.