| name | bkend-data |
| classification | C |
| description | bkend.ai database expert skill.
Covers table creation, CRUD operations, 7 column types, constraints,
filtering (AND/OR, 10 operators), sorting, pagination, relations, joins,
indexing, and schema management via MCP and REST API.
Triggers: table, column, CRUD, schema, index, filter, query, data model,
테이블, 컬럼, 스키마, 인덱스, 필터, 쿼리, 데이터 모델,
テーブル, カラム, スキーマ, インデックス, フィルター,
数据表, 列, 模式, 索引, 过滤, 查询,
tabla, columna, esquema, indice, filtro, consulta,
tableau, colonne, schema, index, filtre, requete,
Tabelle, Spalte, Schema, Index, Filter, Abfrage,
tabella, colonna, schema, indice, filtro, query
Do NOT use for: authentication (use bkend-auth), file storage (use bkend-storage),
MCP setup (use bkend-mcp), security policies (use bkend-security)
|
| user-invocable | true |
| argument-hint | |
| allowed-tools | ["read_file","write_file","replace","glob","grep_search","run_shell_command","web_fetch"] |
| imports | [] |
| agents | {"backend":"bkend-expert"} |
| context | session |
| memory | project |
| pdca-phase | all |
bkend-data: Database Expert Skill
Complete database management for bkend.ai projects using MongoDB Atlas
1. Overview
bkend.ai provides a fully managed database layer built on MongoDB Atlas. Each project operates in complete data isolation, with built-in schema validation and Row-Level Security (RLS) policies.
Key characteristics:
- MongoDB Atlas backend with project-level isolation
- Schema validation enforced at the database level
- Row-Level Security (RLS) for fine-grained access control
- Automatic system fields on every record
- REST API and MCP tools for full database management
2. Data Model
2.1 Column Types (7 Types)
bkend.ai supports exactly 7 column types. There is no generic "number" type.
| Type | Description | Example |
|---|
string | Text data, UTF-8 encoded | "Hello World" |
int | Integer numbers (no decimals) | 42 |
double | Floating-point numbers | 3.14 |
bool | Boolean true/false | true |
date | ISO 8601 date-time string | "2025-01-15T09:30:00Z" |
object | Nested JSON object | { "city": "Seoul", "zip": "06000" } |
array | Array of values | ["tag1", "tag2", "tag3"] |
IMPORTANT: Do NOT use "number" as a column type. Use int for integers or double for decimals.
2.2 System Fields (Auto-Generated)
Every record automatically includes these system fields. Do NOT define them manually.
| Field | Type | Description |
|---|
id | string | Unique record identifier (auto-generated) |
createdBy | string | User ID of the creator (auto-set) |
createdAt | date | Creation timestamp (auto-set) |
updatedAt | date | Last update timestamp (auto-set) |
2.3 Constraints
Apply constraints to columns for data integrity:
| Constraint | Description | Example |
|---|
required | Field must have a value | required: true |
unique | Value must be unique across all records | unique: true |
default | Default value when not provided | default: "active" |
min | Minimum value (int/double) or length (string) | min: 0 |
max | Maximum value (int/double) or length (string) | max: 100 |
enum | Restrict to a set of allowed values | enum: ["active", "inactive", "pending"] |
2.4 Default Indexes
Every table is created with these indexes by default:
| Index Name | Fields | Purpose |
|---|
_id_ | id | Primary key lookup |
idx_createdAt_desc | createdAt descending | Sort by creation date |
idx_updatedAt_desc | updatedAt descending | Sort by update date |
idx_createdBy | createdBy | Filter by owner |
3. CRUD REST API
All data endpoints require authentication via the Authorization: Bearer <token> header and the x-project-id header.
3.1 Create Record
Single record:
POST /v1/data/:tableName
Content-Type: application/json
{
"name": "John Doe",
"email": "john@example.com",
"age": 30,
"role": "user"
}
Batch create (multiple records):
POST /v1/data/:tableName
Content-Type: application/json
{
"records": [
{ "name": "Alice", "email": "alice@example.com", "age": 25 },
{ "name": "Bob", "email": "bob@example.com", "age": 28 }
]
}
Response:
{
"success": true,
"data": {
"id": "rec_abc123",
"name": "John Doe",
"email": "john@example.com",
"age": 30,
"role": "user",
"createdBy": "usr_xyz",
"createdAt": "2025-01-15T09:30:00Z",
"updatedAt": "2025-01-15T09:30:00Z"
}
}
3.2 Read One Record
GET /v1/data/:tableName/:id
Response:
{
"success": true,
"data": {
"id": "rec_abc123",
"name": "John Doe",
"email": "john@example.com",
"age": 30,
"role": "user",
"createdBy": "usr_xyz",
"createdAt": "2025-01-15T09:30:00Z",
"updatedAt": "2025-01-15T09:30:00Z"
}
}
3.3 List Records
GET /v1/data/:tableName?filter={...}&sort={...}&limit=20&cursor=last_id&search=keyword&searchType=partial
Query Parameters:
| Parameter | Type | Description |
|---|
filter | JSON | Filter conditions (see Section 4) |
sort | JSON | Sort order (see Section 5) |
limit | int | Number of records to return (max 100, default 20) |
cursor | string | Cursor for pagination (last record ID) |
search | string | Full-text or partial search keyword |
searchType | string | Search mode: "exact" or "partial" |
Response:
{
"success": true,
"data": [
{ "id": "rec_abc123", "name": "John Doe", "age": 30 },
{ "id": "rec_def456", "name": "Jane Smith", "age": 25 }
],
"meta": {
"total": 150,
"limit": 20,
"nextCursor": "rec_def456"
}
}
3.4 Update Record
PUT /v1/data/:tableName/:id
Content-Type: application/json
{
"name": "John Updated",
"age": 31
}
Response:
{
"success": true,
"data": {
"id": "rec_abc123",
"name": "John Updated",
"age": 31,
"updatedAt": "2025-01-16T10:00:00Z"
}
}
3.5 Delete Record
DELETE /v1/data/:tableName/:id
Response:
{
"success": true,
"data": {
"id": "rec_abc123",
"deleted": true
}
}
3.6 Table Specification
Retrieve the full schema definition for a table:
GET /v1/data/:tableName/spec
Response:
{
"success": true,
"data": {
"tableName": "users",
"fields": [
{ "name": "name", "type": "string", "required": true },
{ "name": "email", "type": "string", "required": true, "unique": true },
{ "name": "age", "type": "int", "min": 0, "max": 150 },
{ "name": "role", "type": "string", "enum": ["user", "admin"], "default": "user" }
],
"indexes": [
{ "name": "_id_", "fields": ["id"] },
{ "name": "idx_createdAt_desc", "fields": [{ "createdAt": -1 }] }
]
}
}
4. Filtering
4.1 AND Filtering (Default)
Multiple conditions in the same filter object are combined with AND logic:
{
"filter": {
"status": { "$eq": "active" },
"age": { "$gte": 18 }
}
}
This returns records where status equals "active" AND age is greater than or equal to 18.
4.2 OR Filtering
Use the $or operator to combine conditions with OR logic:
{
"filter": {
"$or": [
{ "status": "active" },
{ "role": "admin" }
]
}
}
This returns records where status equals "active" OR role equals "admin".
4.3 Filter Operators (10 Operators)
| Operator | Description | Example |
|---|
$eq | Equal to | { "status": { "$eq": "active" } } |
$ne | Not equal to | { "status": { "$ne": "deleted" } } |
$gt | Greater than | { "age": { "$gt": 18 } } |
$gte | Greater than or equal | { "age": { "$gte": 18 } } |
$lt | Less than | { "price": { "$lt": 100 } } |
$lte | Less than or equal | { "price": { "$lte": 99.99 } } |
$in | In array of values | { "role": { "$in": ["admin", "editor"] } } |
$nin | Not in array | { "status": { "$nin": ["deleted", "banned"] } } |
$regex | Regular expression match | { "name": { "$regex": "^John" } } |
$exists | Field exists or not | { "profileImage": { "$exists": true } } |
4.4 Search
Use query parameters for text search:
GET /v1/data/users?search=john&searchType=partial
search: The keyword to search for
searchType: "exact" for exact match, "partial" for contains match
5. Sorting & Pagination
5.1 Sorting
Specify sort order with field name and direction (1 for ascending, -1 for descending):
{
"sort": { "createdAt": -1 }
}
Multiple sort fields:
{
"sort": { "role": 1, "createdAt": -1 }
}
5.2 Pagination
bkend.ai uses cursor-based pagination for optimal performance:
GET /v1/data/users?limit=20&cursor=rec_last_id_value
limit: Number of records per page (max 100, default 20)
cursor: The id of the last record from the previous page
The response includes meta.nextCursor for fetching the next page. When nextCursor is null, there are no more pages.
Example pagination flow:
# First page
GET /v1/data/users?limit=20
# Next page (use nextCursor from previous response)
GET /v1/data/users?limit=20&cursor=rec_def456
# Continue until nextCursor is null
6. Relations
6.1 One-to-Many (1:N)
Store a reference ID in the child table:
Table: users
- id (system)
- name (string)
- email (string)
Table: posts
- id (system)
- title (string)
- content (string)
- authorId (string) ← references users.id
Join query to include related data:
GET /v1/data/posts?join=authorId
Response with joined data:
{
"success": true,
"data": [
{
"id": "post_001",
"title": "My First Post",
"content": "Hello world",
"authorId": "usr_abc",
"author": {
"id": "usr_abc",
"name": "John Doe",
"email": "john@example.com"
}
}
]
}
6.2 Many-to-Many (N:M)
Use a junction table to model many-to-many relationships:
Table: posts
- id (system)
- title (string)
Table: tags
- id (system)
- name (string)
Table: post_tags (junction)
- id (system)
- postId (string) ← references posts.id
- tagId (string) ← references tags.id
Query posts with their tags:
GET /v1/data/post_tags?filter={"postId":{"$eq":"post_001"}}&join=tagId
7. MCP Table Management Tools
Use these MCP tools for schema and table management operations:
7.1 Table Operations
| Tool | Description |
|---|
backend_table_create | Create a new table with field definitions |
backend_table_list | List all tables in the project |
backend_table_get | Get table schema and metadata |
backend_table_update | Update table settings |
backend_table_delete | Delete a table and all its data |
Example: Create a table
Tool: backend_table_create
Arguments:
tableName: "users"
fields:
- name: "name"
type: "string"
required: true
- name: "email"
type: "string"
required: true
unique: true
- name: "age"
type: "int"
min: 0
max: 150
- name: "role"
type: "string"
enum: ["user", "admin"]
default: "user"
- name: "isActive"
type: "bool"
default: true
7.2 Field Management
| Tool | Description |
|---|
backend_field_manage | Add, update, or remove fields from a table |
Example: Add a field
Tool: backend_field_manage
Arguments:
tableName: "users"
action: "add"
field:
name: "bio"
type: "string"
max: 500
7.3 Index Management
| Tool | Description |
|---|
backend_index_manage | Create, list, or delete custom indexes |
Example: Create a compound index
Tool: backend_index_manage
Arguments:
tableName: "users"
action: "create"
index:
name: "idx_role_active"
fields:
- field: "role"
direction: 1
- field: "isActive"
direction: 1
7.4 Schema Versioning
| Tool | Description |
|---|
backend_schema_version_list | List all schema versions for a table |
backend_schema_version_get | Get a specific schema version |
8. Frontend CRUD Pattern (TanStack Query)
Use the Query Key Factory pattern for consistent cache management:
import { useQuery, useMutation, useQueryClient } from '@tanstack/react-query';
import { bkendFetch } from '@/lib/bkend';
export const userKeys = {
all: ['users'] as const,
lists: () => [...userKeys.all, 'list'] as const,
list: (filters: Record<string, unknown>) =>
[...userKeys.lists(), filters] as const,
details: () => [...userKeys.all, 'detail'] as const,
detail: (id: string) => [...userKeys.details(), id] as const,
};
export function useUsers(filters: Record<string, unknown> = {}) {
return useQuery({
queryKey: userKeys.list(filters),
queryFn: async () => {
const params = new URLSearchParams();
if (filters.filter) params.set('filter', JSON.stringify(filters.filter));
if (filters.sort) params.set('sort', JSON.stringify(filters.sort));
if (filters.limit) params.set('limit', String(filters.limit));
if (filters.cursor) params.set('cursor', String(filters.cursor));
const res = await bkendFetch(`/v1/data/users?${params.toString()}`);
return res.json();
},
});
}
export function useUser(id: string) {
return useQuery({
queryKey: userKeys.detail(id),
queryFn: async () => {
const res = await bkendFetch(`/v1/data/users/${id}`);
return res.json();
},
enabled: !!id,
});
}
export function useCreateUser() {
const queryClient = useQueryClient();
return useMutation({
mutationFn: async (data: Record<string, unknown>) => {
const res = await bkendFetch('/v1/data/users', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify(data),
});
return res.json();
},
onSuccess: () => {
queryClient.invalidateQueries({ queryKey: userKeys.lists() });
},
});
}
export function useUpdateUser() {
const queryClient = useQueryClient();
return useMutation({
mutationFn: async ({ id, data }: { id: string; data: Record<string, unknown> }) => {
const res = await bkendFetch(`/v1/data/users/${id}`, {
method: 'PUT',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify(data),
});
return res.json();
},
onSuccess: (_, variables) => {
queryClient.invalidateQueries({ queryKey: userKeys.detail(variables.id) });
queryClient.invalidateQueries({ queryKey: userKeys.lists() });
},
});
}
export function useDeleteUser() {
const queryClient = useQueryClient();
return useMutation({
mutationFn: async (id: string) => {
const res = await bkendFetch(`/v1/data/users/${id}`, {
method: 'DELETE',
});
return res.json();
},
onSuccess: () => {
queryClient.invalidateQueries({ queryKey: userKeys.lists() });
},
});
}
9. Error Codes
| Error Code | HTTP Status | Description |
|---|
TABLE_NOT_FOUND | 404 | The specified table does not exist |
VALIDATION_ERROR | 400 | Request data fails schema validation |
DUPLICATE_KEY | 400 | A unique constraint violation occurred |
PERMISSION_DENIED | 403 | User lacks permission for this operation |
INVALID_FILTER | 400 | The filter syntax is malformed or invalid |
RECORD_NOT_FOUND | 404 | The specified record ID does not exist |
LIMIT_EXCEEDED | 400 | The requested limit exceeds the maximum (100) |
Error response format:
{
"success": false,
"error": {
"code": "VALIDATION_ERROR",
"message": "Field 'email' is required",
"details": [
{ "field": "email", "message": "This field is required" }
]
}
}
Quick Reference
Common Workflows
- Create a table -> Use
backend_table_create MCP tool
- Add fields later -> Use
backend_field_manage MCP tool
- Insert data ->
POST /v1/data/:tableName
- Query with filters ->
GET /v1/data/:tableName?filter={...}&sort={...}&limit=20
- Join related data ->
GET /v1/data/:tableName?join=fieldName
- Paginate results -> Use
cursor from meta.nextCursor
- Search records ->
GET /v1/data/:tableName?search=keyword&searchType=partial
- Manage indexes -> Use
backend_index_manage MCP tool