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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://mp-staging.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/native_sql.md

Native SQL Operations

Always default to Native GraphQL. Use Native SQL only when you need database-specific features not available in GraphQL (e.g., PostGIS, Window Functions, Complex Aggregations, or specific DML CTEs).

Core Agent Constraints

When generating Native SQL operations, you are bypassing GraphQL and talking directly to PostgreSQL. You MUST adhere to these strict constraints:

  1. Operation Syntax Isolation: Never mix Native SQL positional parameters ($1) with standard GraphQL named variables ($id). The sql: argument MUST be a hardcoded string literal block ("""SELECT..."""), not a GraphQL variable.

  2. Table & Column Mapping (Case Sensitivity):

    • Default snake_case Conversion: By default, SQL Connect converts PascalCase types and camelCase fields to snake_case in the database.

      • Schema: type UserProfile { releaseYear: Int } -> Native SQL: SELECT release_year FROM user_profile

    • Explicit Overrides (Requires Double Quotes): If the schema uses @table(name: "ExactName") or @col(name: "ExactCol"), you MUST wrap the identifier in double quotes if it contains capital letters (e.g., SELECT * FROM "ExactName"). Without quotes, Postgres folds it to lowercase and fails validation.

Syntax rules & limitations

Native SQL enforces strict parsing rules to ensure security and prevent SQL injection:

  • String Literals Only: The sql argument must be a hardcoded string literal block ("""SELECT...""") directly in the .gql file. It cannot be a GraphQL variable.

  • Validation: Do NOT use DDL in any operations (modify the schema.gql file instead for table/column changes). Furthermore, query operations cannot contain DML and must start with SELECT, TABLE, or WITH.

  • Parameters: Use strict positional parameters ($1, $2) that match the params array order. Named parameters ($id, :name) are forbidden.

  • Comments: Use block comments (/* ... */). Line comments (--) are forbidden because they can truncate subsequent clauses during query compilation. If you comment out a line containing a parameter (e.g., /* WHERE id = $1 */), you must also remove that parameter from the params list, or it will fail with unused parameter: $1.

  • Strings: Extended string literals (E'...') and dollar-quoted strings ($$...$$) are supported.

  • Context Maps (_expr): Variables cannot be used inside _expr fields; to ensure security, _expr must be a static string (e.g., {_expr: "auth.uid"}, not {_expr: $uidVar}).

Native SQL Root Fields

Operations are executed using the permissions granted to the SQL Connect service account. You can alias the root field (e.g., movies: _select) to make the client response cleaner (data.movies instead of data._select).

Note on Any Return Types: Because Native SQL completely bypasses GraphQL's strong typing, queries like _select and _executeReturning return the generic Any scalar type. The generated client SDKs (TypeScript, Swift, Kotlin, Dart) will type this as any (or equivalent). AGENT INSTRUCTION: When you generate client-side code that consumes these operations, you MUST manually cast or validate the shape of the data, as the typical type safety of SQL Connect will not be present.

Use these root fields in query or mutation operations:

Query Fields (Read-Only)
  • _select: Executes a SQL query returning zero or more rows. Returns [Any].

    query GetMovies($genre: String!) @auth(level: PUBLIC) {
      movies: _select(
        sql: "SELECT id, title FROM movie WHERE genre = $1",
        params: [$genre]
      )
    }
  • _selectFirst: Executes a SQL query expected to return zero or one row. Returns Any or null.

    query GetTotalReviews @auth(level: PUBLIC) {
      stats: _selectFirst(
        sql: "SELECT COUNT(*) as total_reviews FROM review"
      ) # params can be omitted if empty
    }
Mutation Fields (DML)
  • _execute: Executes DML (INSERT, UPDATE, DELETE). Returns Int (number of rows affected).

    • Note 1: RETURNING clauses are ignored in the result.

    • Note 2: Only _execute supports Data-Modifying Common Table Expressions (e.g., WITH new_row AS (INSERT...)).

    mutation UpdateRating($id: UUID!, $rating: Float!) @auth(level: USER) {
      _execute(
        sql: "UPDATE movie SET rating = $2 WHERE id = $1",
        params: [$id, $rating]
      )
    }
  • _executeReturning: Executes DML with a RETURNING clause. Returns [Any]. Data-Modifying CTEs are not supported.

    mutation DeleteUserReviews($uid: String!) @auth(level: USER) {
      deletedReviews: _executeReturning(
        sql: "DELETE FROM review WHERE user_id = $1 RETURNING id, rating",
        params: [{_expr: "auth.uid"}]
      )
    }
  • _executeReturningFirst: Executes DML with RETURNING, expecting zero or one row. Returns Any or null. Data-Modifying CTEs are not supported.

    mutation UpdateMyReview($movieId: UUID!, $text: String!) @auth(level: USER) {
      updatedReview: _executeReturningFirst(
        sql: """
          UPDATE review SET text = $2 
          WHERE movie_id = $1 AND user_id = $3 
          RETURNING id, text
        """,
        params: [$movieId, $text, {_expr: "auth.uid"}]
      )
    }
PostgreSQL Extensions

Native SQL allows you to directly query and utilize PostgreSQL extensions, such as PostGIS, without needing to map complex geometry types into your GraphQL schema or alter your underlying tables (e.g., using JSON operators to extract values and pass them into ST_MakePoint).

Note: You must enable the extension on your underlying Cloud SQL instance by connecting as the postgres user and running CREATE EXTENSION IF NOT EXISTS ...;

(See examples.md for a full GetNearbyActiveRestaurants implementation).

⚠️ Security: Stored Procedures & Dynamic SQL

SQL Connect parameterizes inputs at the GraphQL boundary automatically. However, if your Native SQL calls custom PL/pgSQL stored procedures, you must manually prevent 2nd-order SQL injection:

  • NEVER concatenate user input into an EXECUTE string (EXECUTE 'UPDATE ' || table || ' SET x=' || val;).

  • DO use the USING clause to bind data values safely.

  • DO use format('%I') for safe database identifier injection.

  • DO validate dynamic table/column names against a strict hardcoded allowlist.

Secure PL/pgSQL Pattern:

CREATE OR REPLACE PROCEDURE secure_update(target_table TEXT, new_value TEXT, row_id INT)
LANGUAGE plpgsql AS $$
BEGIN
    -- 1. Strict Allowlist for Identifiers
    IF target_table NOT IN ('orders', 'users', 'inventory') THEN
        RAISE EXCEPTION 'Invalid table name';
    END IF;

    -- 2. format(%I) for Identifiers, USING for Data
    EXECUTE format('UPDATE %I SET status = $1 WHERE id = $2', target_table)
    USING new_value, row_id;
END;
$$;

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).

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