Firebase Data Connect

Firebase (Google)OfficialCreated by Google LLCDistributed by Firebase (Google)

Skill
Tool integration
Software development
Apache-2.0
Low risk

From the author

Builds and deploys Firebase SQL Connect (aka Firebase Data Connect) backends with PostgreSQL securely. Use when designing schemas with tables and relations, writing authorized queries and mutations, configuring real-time data updates, or generating type-safe SDKs. Use when you need a relational database with Firebase, or when the user mentions SQL Connect or Data Connect.

— the description by Google LLC

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

Firebase SQL Connect (formerly Firebase Data Connect) provides a managed relational database service built on Cloud SQL for PostgreSQL. It enables developers to define data models using GraphQL schemas, automatically generating type-safe SDKs for various platforms. The service emphasizes a secure-by-default approach, offering built-in authorization, real-time data updates, and support for complex operations through both GraphQL and native SQL.

What it does

Defines relational data models using GraphQL schema syntax.
Generates type-safe SDKs for TypeScript, Kotlin, Swift, Dart, and Node.js.
Manages database operations including queries, mutations, and transactions.
Configures real-time data subscriptions and event-driven updates.
Supports advanced PostgreSQL features via native SQL when necessary.
Provides local emulation for development, testing, and data seeding.

When to use it

When building a new application that requires a relational database integrated with Firebase.
When you need to generate type-safe client SDKs from a defined database schema.
When implementing row-level security and authorized data access.
When your application requires real-time data synchronization.
When you need to perform complex database operations like vector search or window functions.

Advantages

Strong type safety across the full stack via auto-generated SDKs.
Secure-by-default architecture with built-in authorization directives.
Seamless integration with the Firebase ecosystem and Cloud SQL.
Flexible operation strategies allowing for both standard GraphQL and advanced native SQL.
Robust local development tooling including emulators and schema validation.

Usage examples

“How do I define a new table for my user profiles in Firebase SQL Connect?”: The agent will guide you to define a GraphQL type in schema.gql using the @table directive, specifying columns and relationships.
“Generate a TypeScript SDK for my current Firebase SQL Connect project.”: The agent will show you how to configure the generate block in connector.yaml and run the SDK generation command.
“How can I perform a complex PostgreSQL window function in my query?”: The agent will explain how to use Native SQL operations with _select or _execute to bypass standard GraphQL limitations.
“Set up a real-time subscription for my movie list.”: The agent will demonstrate using the @refresh directive in your query to enable event-driven updates.

Install

Download the skill as a ZIP:
https://autogineer.com/agent-skills/firebase/firebase-data-connect/download

Unzip it into the cross-client skills folder of your project:

mkdir -p .agents/skills && unzip firebase-data-connect.zip -d .agents/skills

Documentation by Google LLC

Firebase SQL Connect

Firebase SQL Connect is a relational database service using Cloud SQL for PostgreSQL with GraphQL schema, auto-generated queries/mutations, and type-safe SDKs.

[!NOTE] Product Rename: Firebase Data Connect was renamed to Firebase SQL Connect. All instructions, references, and examples in this skill repository referring to "Data Connect" or "Firebase Data Connect" apply to "SQL Connect" and "Firebase SQL Connect" as well.

Project Structure

dataconnect/
├── dataconnect.yaml      # Service configuration
├── seed_data.gql         # LOCAL ONLY — prototype/test data
├── schema/
│   └── schema.gql        # Data model (types with @table)
└── connector/
    ├── connector.yaml    # Connector config + SDK generation
    ├── queries.gql       # Queries
    └── mutations.gql     # Mutations

Key Tools for Validation

Rely on these two mechanisms to ensure project correctness:

Review GraphQL Schema: Both user-defined and generated extensions (in .dataconnect/schema/main/).
Validate Operations: Run npx -y firebase-tools@latest dataconnect:compile against the schema.

Operation Strategies: GraphQL vs. Native SQL

Always default to Native GraphQL. Native SQL lacks type safety and bypasses schema-enforced structures. Only use Native SQL when the user explicitly requests it or when the task requires advanced database features.

Strategy	When to use	Implementation
Native GraphQL (Default)	Almost all use cases. Standard CRUD, basic filtering/sorting, simple relational joins. Requires full type safety.	Auto-generated fields (`movie_insert`, `movies`). Strong typing and schema enforcement.
Native SQL (Advanced)	PostgreSQL extensions (e.g., PostGIS), window functions (`RANK()`), complex aggregations, or highly tuned sub-queries.	Raw SQL string literals via `_select`, `_execute`, etc. Requires strict positional parameters (`$1`). No type safety.

Development Workflow

Follow this strict workflow to build your application. You must read the linked reference files for each step to understand the syntax and available features.

1. Define Data Model (`schema/schema.gql`)

Define your GraphQL types, tables, and relationships (which map to a Postgres schema).

Read reference/schema.md for:
@table, @col, @default
Relationships (@ref, one-to-many, many-to-many)
Data types (UUID, Vector, JSON, etc.)

2. Define Authorized Operations (`connector/queries.gql`, `connector/mutations.gql`)

Write the queries and mutations your client will use, including authorization logic. SQL Connect is secure by default.

Read reference/operations.md for:
Queries: Filtering (where), Ordering (orderBy), Pagination (limit/offset).
Mutations: Create (_insert), Update (_update), Delete (_delete).
Upserts: Use _upsert to "insert or update" records (CRITICAL for user profiles).
Transactions: Use @transaction for multi-step atomic operations. Use _expr: "response.<prevStep>" to pass data between steps.
Read reference/security.md for authorization:
@auth(level: ...) for PUBLIC, USER, or NO_ACCESS.
@check and @redact for row-level security and validation.
Read reference/realtime.md for real-time subscriptions:
@refresh directive for time-based polling and event-driven updates.
CEL conditions to scope refresh triggers precisely.
Read reference/native_sql.md for Native SQL operations:
Embedding raw SQL with _select, _selectFirst, _execute
Strict rules for positional parameters ($1, $2), quoting, and CTEs
Advanced PostgreSQL features (PostGIS, Window Functions)

3. Use type-safe SDK in your apps

Generate type-safe code for your client platform.

Configure SDK generation in connector.yaml:

connectorId: my-connector
generate:
  javascriptSdk:
    outputDir: "../web-app/src/lib/dataconnect"
    package: "@movie-app/dataconnect"
  kotlinSdk:
    outputDir: "../android-app/app/src/main/kotlin/com/example/dataconnect"
    package: "com.example.dataconnect"
  swiftSdk:
    outputDir: "../ios-app/DataConnect"
    package: "DataConnectGenerated"

Generate SDKs:

npx -y firebase-tools@latest dataconnect:sdk:generate

For platform-specific instructions on how to use the generated SDKs, read:

Web (TypeScript): reference/sdk_web.md
Android (Kotlin): reference/sdk_android.md
iOS (Swift): reference/sdk_ios.md
Admin (Node.js): reference/sdk_admin_node.md
Flutter (Dart): reference/sdk_flutter.md

Feature Capability Map

If you need to implement a specific feature, consult the mapped reference file:

Feature	Reference File	Key Concepts
Data Modeling	reference/schema.md	`@table`, `@unique`, `@index`, Relations
Vector Search	reference/search.md	`Vector`, `@col(dataType: "vector")`, embeddings
Full-Text Search	reference/search.md	`@searchable`, `movies_search`
Upserting Data	reference/operations.md	`_upsert` mutations
Complex Filters	reference/operations.md	`_or`, `_and`, `_not`, `eq`, `contains`
Transactions	reference/operations.md	`@transaction`, `response` binding
Environment Config	reference/config.md	`dataconnect.yaml`, `connector.yaml`
Realtime Subscriptions	reference/realtime.md	`@refresh`, `subscribe()`, auto-refresh
Cloud Functions Integration	reference/cloud_functions.md	`onMutationExecuted`, triggering events
Data Seeding & Migrations	reference/data_seeding.md	`seed_data.gql`, `_insertMany`, Admin SDK bulk
Starter Templates	templates.md	CRUD, user-owned resources, many-to-many, SDK init

Deployment & CLI

Read reference/config.md for deep dive on configuration.

Follow these patterns based on your current task:

How to initialize SQL Connect in a Firebase project

Understand the app idea. Ask clarification questions if unclear.
Run npx -y firebase-tools@latest init dataconnect.
Validate that the app template and generated SDK are setup.

How to build apps using SQL Connect locally

Start the emulator: npx -y firebase-tools@latest emulators:start --only dataconnect.
Write schema and operations.
Seed local test data into seed_data.gql. Read reference/data_seeding.md.
Run npx -y firebase-tools@latest dataconnect:compile or npx -y firebase-tools@latest dataconnect:sdk:generate to validate them.
Use the operations in your app and build it.

How to deploy SQL Connect to Cloud SQL

Run npx -y firebase-tools@latest deploy --only dataconnect.

Examples

For complete, working code examples of schemas and operations, see examples.md.

For ready-to-use starter templates (CRUD, user-owned resources, many-to-many, YAML configs, SDK init), see templates.md.

Files

ATTRIBUTION.mdAdded by AutoGineer989 B
LICENSELicence file added by AutoGineer11.1 KiB
SKILL.md9.3 KiB
examples.md14.7 KiB
reference/cloud_functions.md6.0 KiB
reference/config.md7.1 KiB
reference/data_seeding.md5.8 KiB
reference/native_sql.md6.9 KiB
reference/operations.md11.0 KiB
reference/realtime.md7.7 KiB
reference/schema.md7.4 KiB
reference/sdk_admin_node.md4.1 KiB
reference/sdk_android.md5.9 KiB
reference/sdk_flutter.md3.4 KiB
reference/sdk_ios.md4.2 KiB
reference/sdk_web.md4.8 KiB
reference/search.md8.7 KiB
reference/security.md8.9 KiB
templates.md7.1 KiB

reference/realtime.md

Realtime Reference

When to Use What
The @refresh Directive
CEL Bindings in Conditions
Implicit Entity Refresh signals

When to Use What

SQL Connect provides three mechanisms for live data updates. Pick the right one based on what you're querying:

Scenario	Mechanism	Directive Needed?
Single-entity lookup by ID (e.g., `movie(id: $id)`)	Automatic refresh	No — SQL Connect handles it
List query that should update when a specific mutation runs	Event-driven refresh	`@refresh(onMutationExecuted: ...)`
Any query that should poll at a fixed interval	Time-based polling	`@refresh(every: ...)`

List queries require explicit @refresh to tell SQL Connect which mutations affect the result set.

Clients consume all three using subscribe() instead of execute(). See sdk_web.md, sdk_android.md, sdk_ios.md, and sdk_flutter.md for per-platform subscribe patterns.

The @refresh Directive

@refresh is a repeatable directive applied to queries. It defines when connected subscribers should receive updated data.

Time-Based Polling (`every`)

Keep the query fresh with a recommended refresh interval. Note that every and mutation signals can be used together; whichever signal arrives first will trigger the refresh.

query MovieLeaderboard
  @auth(level: PUBLIC)
  @refresh(every: { seconds: 30 }) {
  movies(orderBy: [{ rating: DESC }], limit: 10) {
    id title rating
  }
}

Constraints:

The every argument takes a duration object: { seconds: Int }
Minimum: { seconds: 10 } — protects against excessive server load
Maximum: { hours: 1 } (3600 seconds)
Values outside this range fail validation at deploy time

Use time-based polling when freshness matters but you don't have a specific mutation to listen for (e.g., dashboards aggregating external data, stock tickers, activity feeds).

Explicit Mutation Signals (`onMutationExecuted`)

Trigger a query refresh when a specific mutation executes. This is the most common pattern for keeping lists in sync.

# Example with condition (refreshes only when the condition is met)
query ChatRoom($roomId: UUID!) @auth(level: PUBLIC)
  @refresh(onMutationExecuted: {
    operation: "SendMessage",
    condition: "mutation.variables.roomId == request.variables.roomId"
  }) {
  messages(where: {roomId: {eq: $roomId}}, orderBy: [{createTime: DESC}], limit: 50) {
    author content createTime
  }
}

# Example without condition (refreshes on any execution of the named mutation)
query ListAllMessages
  @auth(level: PUBLIC)
  @refresh(onMutationExecuted: {
    operation: "SendMessage"
  }) {
  messages { id content }
}

Arguments:

operation (required): The name of the mutation operation to listen for. Must match the mutation's operation name exactly.
condition (optional): A CEL expression that must evaluate to true for the refresh to fire. Without a condition, every execution of the named mutation triggers a refresh.

It's highly recommended to define fine granular conditions. Inaccurate refresh policies could consume Postgres resources and make your app slower.

Use conditions to scope refreshes precisely — a review list should only refresh when the mutation targets the same movie, not every review across the entire app.

Combining Multiple @refresh Directives

Since @refresh is repeatable, you can combine strategies on a single query:

query ActiveOrders($userId: UUID!)
  @auth(level: USER)
  @refresh(onMutationExecuted: {
    operation: "UpdateOrderStatus",
    condition: "request.variables.userId == mutation.variables.userId"
  })
  @refresh(every: { seconds: 60 }) {
  orders(where: { user: { id: { eq: $userId }}, status: { ne: DELIVERED }}) {
    id status total updatedAt
  }
}

This query refreshes whenever an order status changes for this user, and polls every 60 seconds as a fallback to catch any updates that might not have a direct mutation trigger.

CEL Bindings in Conditions

The condition expression in onMutationExecuted has access to two contexts:

`request` — The Query Subscription

The state of the query being subscribed to.

Binding	Description
`request.variables`	Variables passed to the query (e.g., `request.variables.id`)
`request.auth.uid`	UID of the user who subscribed
`request.auth.token`	Full auth token claims of the subscriber

`mutation` — The Triggering Event

The mutation that just executed.

Binding	Description
`mutation.variables`	Variables passed to the mutation (e.g., `mutation.variables.movieId`)
`mutation.auth.uid`	UID of the user who executed the mutation
`mutation.auth.token`	Full auth token claims of the mutation executor

Common Patterns

# Refresh only when the mutation targets the same entity
"request.variables.id == mutation.variables.id"

# Refresh only when the same user who subscribed makes a change
"request.auth.uid == mutation.auth.uid"

# Refresh when a specific field value matches a condition
"request.auth.uid == mutation.auth.uid && mutation.variables.status == 'PUBLISHED'"

# Refresh when a specific flag is set in the mutation
"mutation.variables.isPublic == true"

Implicit Entity Refresh signals

For single-entity lookups by unique identifier, SQL Connect handles refreshes automatically — no @refresh directive needed.

What qualifies:

Queries fetching one entity by its primary key: movie(id: $id), user(key: { uid: $uid })
If a single-entity mutation modifies that specific entity, all active subscribers automatically receive the update. Supported operations include:
- _insert(data) or _insertMany(data)
- _upsert(data) or _upsertMany(data)
- _update(id) or _update(key)
- _delete(id) or _delete(key)
Note: Bulk operations like _updateMany and _deleteMany do not trigger automatic entity refreshes.

What does NOT qualify:

List queries: movies(where: {...}), users { id name } — these require explicit @refresh
Nested query with JOINs
Aggregation
Native SQL
Customized Resolver (if supported)

# When subscribed to, this query auto-refreshes when movie data changes — no @refresh needed
query GetMovie($id: UUID!) @auth(level: PUBLIC) {
  movie(id: $id) {
    id title rating description
    reviews_on_movie { rating text user { displayName } }
  }
}

To consume automatic refreshes on the client, use subscribe() instead of execute() — the same client pattern works regardless of whether the refresh is automatic or directive-driven.

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs Node.js

Security

What our scanner noticed· Low risk

Instructions that use the network

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by

Google LLC

Publisher

Firebase (Google) (Official)

Distributed by

Firebase (Google)

Source

firebase/agent-skills · skills/firebase-data-connect-basics · commit b76be96

Licence

Apache License 2.0 (redistribution allowed)

LICENSE (added by AutoGineer from LICENSE)
ATTRIBUTION.md (written by AutoGineer)

Synced

2026-11-09

AutoGineer is not affiliated with or endorsed by Google LLC or Firebase (Google).

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download firebase-data-connect.zip