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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

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/firebase/firebase-data-connect/download
  2. 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:

  1. Review GraphQL Schema: Both user-defined and generated extensions (in .dataconnect/schema/main/).

  2. 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.

StrategyWhen to useImplementation
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:


Feature Capability Map

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

FeatureReference FileKey Concepts
Data Modelingreference/schema.md@table, @unique, @index, Relations
Vector Searchreference/search.mdVector, @col(dataType: "vector"), embeddings
Full-Text Searchreference/search.md@searchable, movies_search
Upserting Datareference/operations.md_upsert mutations
Complex Filtersreference/operations.md_or, _and, _not, eq, contains
Transactionsreference/operations.md@transaction, response binding
Environment Configreference/config.mddataconnect.yaml, connector.yaml
Realtime Subscriptionsreference/realtime.md@refresh, subscribe(), auto-refresh
Cloud Functions Integrationreference/cloud_functions.mdonMutationExecuted, triggering events
Data Seeding & Migrationsreference/data_seeding.mdseed_data.gql, _insertMany, Admin SDK bulk
Starter Templatestemplates.mdCRUD, 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
  1. Understand the app idea. Ask clarification questions if unclear.

  2. Run npx -y firebase-tools@latest init dataconnect.

  3. Validate that the app template and generated SDK are setup.

How to build apps using SQL Connect locally
  1. Start the emulator: npx -y firebase-tools@latest emulators:start --only dataconnect.

  2. Write schema and operations.

  3. Seed local test data into seed_data.gql. Read reference/data_seeding.md.

  4. Run npx -y firebase-tools@latest dataconnect:compile or npx -y firebase-tools@latest dataconnect:sdk:generate to validate them.

  5. Use the operations in your app and build it.

How to deploy SQL Connect to Cloud SQL
  1. 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

reference/cloud_functions.md

Cloud Functions Integration Reference

Use this reference to handle database events in SQL Connect by triggering Cloud Functions in response to mutation executions.


Core Trigger Configuration

To handle a mutation execution, define the onMutationExecuted event handler.

🚨 Critical Infinite Loop Constraint

Unlike document-based database triggers (like Firestore or Realtime Database), SQL Connect event triggers do not provide a "before" snapshot of the data. Because SQL Connect proxies requests directly to PostgreSQL, "before" states cannot be resolved transactionally.

  • Warning: If onMutationExecuted executes a SQL Connect mutation, it can trigger another onMutationExecuted trigger in a cascading loop. Make sure that onMutationExecuted has a filter on operation to reduce the chance of infinite loops.

  • Rule: Ensure that no mutation executed inside the function can ever trigger the handler itself, even indirectly.

Location & Region Matching Rule

The Cloud Function region option must match your SQL Connect service location. You must explicitly configure the region parameter (e.g., 'us-central1') in the trigger options to match the location specified in dataconnect.yaml.

import { onMutationExecuted } from "firebase-functions/dataconnect";
import { logger } from "firebase-functions";

export const logMutation = onMutationExecuted(
  {
    region: "europe-west1" // Must match the SQL Connect service location
  },
  (event) => {
    logger.info("A mutation was executed!", {
      eventId: event.id,
      type: event.type
    });
  }
);

Event Filtering

To prevent unnecessary function invocations and infinite execution loops, always specify narrow filters using service and operation attributes.

  • service & operation (Recommended): Always specify these to restrict the trigger to a specific mutation in your project.

  • connector (Optional): Can be omitted if you want to trigger on the same operation name across multiple connectors. Specify it only if you need to restrict the trigger to a specific connector.

Comprehensive Example
import { onMutationExecuted } from "firebase-functions/dataconnect";
import { logger } from "firebase-functions";

// Triggers for "CreateUser" mutation in "myAppService" service.
// 'connector' is omitted (optional), meaning it matches "CreateUser" in any connector.
export const onUserCreate = onMutationExecuted(
  {
    service: "myAppService",
    operation: "CreateUser",
    // region: "us-central1" // Optional: defaults to us-central1, change if database is elsewhere
  },
  (event) => {
    logger.info("A new user was created!");
  }
);

// Advanced: Trigger using wildcards or capture variables
export const onMutationCaptures = onMutationExecuted(
  {
    service: "myAppService",
    operation: "{operation}", // Captures matching operation name dynamically
  },
  (event) => {
    const triggeredOp = event.params.operation;
    logger.info(`Captured operation execution: ${triggeredOp}`);
  }
);

Accessing User Authentication Context

Extract security credentials about the caller who executed the mutation using event.authType and event.authId.

Auth Context Mappings
Triggered Principalevent.authTypeevent.authId
Authenticated end user"app_user"Firebase Auth token UID
Unauthenticated end user"unauthenticated"Empty
Admin SDK (Impersonating User)"app_user"Firebase Auth token UID of the impersonated user
Admin SDK (Impersonating Unauth)"unauthenticated"Empty
Admin SDK (Full privileges)"admin"Empty
Auth Extraction Example
export const processSensitiveMutation = onMutationExecuted(
  { operation: "UpdateFinancials" },
  (event) => {
    if (event.authType === "admin") {
      console.log("Elevated admin mutation execution.");
    } else {
      console.log(`Mutation initiated by user: ${event.authId}`);
    }
  }
);

Parsing Event Data Payloads

The trigger payload provides inputs passed to the mutation (payload.variables) and return values generated from the execution (payload.data).

Event Payload Structure
{
  "authType": "app_user",
  "authId": "user-123",
  "data": {
    "payload": {
      "variables": {
        "movieId": "m-1",
        "rating": 5
      },
      "data": {
        "review_insert": {
          "id": "r-99"
        }
      },
      "errors": []
    }
  }
}
  • event.data.payload.variables: Inputs passed to the mutation.

  • event.data.payload.data: Fields returned by the mutation execution.

  • event.data.payload.errors: Array of execution errors. Empty if successful.

Payload Extraction Example
import { onMutationExecuted } from "firebase-functions/dataconnect";
import { logger } from "firebase-functions";

export const onNewReview = onMutationExecuted(
  {
    service: "myAppService",
    connector: "reviews",
    operation: "CreateReview",
  },
  (event) => {
    // Extract input variables passed to the mutation
    const inputVariables = event.data.payload.variables;

    // Extract returned fields from the database write
    const returnedFields = event.data.payload.data;

    logger.info(`Processed review ${returnedFields.review_insert.id} for movie ${inputVariables.movieId}`);
  }
);

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

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