快速入门：将数据 API 生成器与 SQL 配合使用

在本快速入门中，你将使用数据 API 生成器（DAB）为本地 SQL 数据库创建 REST 和 GraphQL 终结点。 选择数据库引擎以开始。

先决条件

安装数据 API 生成器 CLI

将 NuGet 中的 Microsoft.DataApiBuilder 包安装为 .NET 工具。

  1. 使用dotnet tool install来安装带有Microsoft.DataApiBuilder参数的--global的最新版本。

    dotnet tool install --global Microsoft.DataApiBuilder

    注释

    如果包已安装，请改用 dotnet tool update更新包。

    dotnet tool update --global Microsoft.DataApiBuilder

  2. 使用dotnet tool list参数验证是否已安装--global工具。

    dotnet tool list --global

拉取数据库镜像

小窍门

已有数据库？ 跳到 创建和初始化数据库，运行引擎的 SQL 脚本，然后使用自己的连接字符串跳转到 配置 Data API 构建器。

下载数据库引擎的 Docker 映像。 此步骤可能需要几分钟时间，具体取决于连接速度。

docker pull mcr.microsoft.com/mssql/server:2025-latest

启动数据库

在 Docker 中运行本地数据库实例。

docker run --name dab-mssql --env "ACCEPT_EULA=Y" --env "MSSQL_SA_PASSWORD=P@ssw0rd1" --publish 1433:1433 --detach mcr.microsoft.com/mssql/server:2025-latest

小窍门

如果端口1433已在使用（例如，由本地 SQL Server 安装），请将--publish更改为其他主机端口，例如1434:1433，并在后续步骤中将Server=localhost,1433更新为Server=localhost,1434。

运行下一个命令之前，请验证数据库引擎是否已准备就绪。

docker exec dab-mssql /opt/mssql-tools18/bin/sqlcmd -S localhost -U sa -P "P@ssw0rd1" -C -Q "SELECT 1"

如果返回错误，请等待几秒钟，然后重试。

创建并初始化数据库

创建数据库 todos 和表，然后添加示例数据。 如果使用 Docker，则不需要 SQL 客户端 -docker exec 直接在容器中运行命令。 如果使用自己的数据库，请在首选工具中运行 SQL 脚本。

  1. 创建数据库。

    docker exec dab-mssql /opt/mssql-tools18/bin/sqlcmd -S localhost -U sa -P "P@ssw0rd1" -C -Q "CREATE DATABASE todos;"

  2. 创建表并添加示例数据。

    docker exec dab-mssql /opt/mssql-tools18/bin/sqlcmd -S localhost -U sa -P "P@ssw0rd1" -C -d todos -Q "CREATE TABLE dbo.todos (id int PRIMARY KEY, title nvarchar(100) NOT NULL, completed bit NOT NULL DEFAULT 0); INSERT INTO dbo.todos VALUES (1, 'Walk the dog', 0), (2, 'Feed the fish', 0), (3, 'Comb the cat', 1);"

小窍门

使用自己的 SQL Server？ 直接运行此脚本：

CREATE DATABASE todos;
GO
USE todos;
GO
CREATE TABLE dbo.todos (id int PRIMARY KEY, title nvarchar(100) NOT NULL, completed bit NOT NULL DEFAULT 0);
INSERT INTO dbo.todos VALUES (1, 'Walk the dog', 0), (2, 'Feed the fish', 0), (3, 'Comb the cat', 1);

配置数据 API 生成器

创建 DAB 配置文件并添加 Todo 实体。

小窍门

使用自己的数据库？ 将 dab init 中的连接字符串替换为你自己的：

  • Sqlserver：Server=<host>,<port>;Database=todos;User Id=<user>;Password=<password>;TrustServerCertificate=true;Encrypt=true;
  • PostgreSQL：Host=<host>;Port=5432;Database=todos;User ID=<user>;Password=<password>;
  • Mysql：Server=<host>;Port=3306;Database=todos;User=<user>;Password=<password>;

  1. 初始化配置。

    dab init --database-type "mssql" --host-mode "Development" --connection-string "Server=localhost,1433;Database=todos;User Id=sa;Password=P@ssw0rd1;TrustServerCertificate=true;Encrypt=true;"

  2. 添加 Todo 实体。

    dab add Todo --source "dbo.todos" --permissions "anonymous:*"

文件 dab-config.json 现在应类似于以下示例：

{
  "$schema": "https://github.com/Azure/data-api-builder/releases/download/vmajor.minor.patch/dab.draft.schema.json",
  "data-source": {
    "database-type": "mssql",
    "connection-string": "Server=localhost,1433;Database=todos;User Id=sa;Password=P@ssw0rd1;TrustServerCertificate=true;Encrypt=true;"
  },
  "runtime": {
    "rest": {
      "enabled": true
    },
    "graphql": {
      "enabled": true
    },
    "host": {
      "mode": "development",
      "cors": {
        "origins": ["*"]
      }
    }
  },
  "entities": {
    "Todo": {
      "source": "dbo.todos",
      "permissions": [
        {
          "role": "anonymous",
          "actions": [
            "*"
          ]
        }
      ]
    }
  }
}

小窍门

可以跳过 dab init 和 dab add 命令，直接使用此处显示的内容创建 dab-config.json 文件。

启动 API

使用 dab start 来运行该工具并为您的实体创建 API 终结点。

dab start

输出应包括正在运行的 API 的地址。

      Successfully completed runtime initialization.
info: Microsoft.Hosting.Lifetime[14]
      Now listening on: <http://localhost:5000>

小窍门

在此示例中，应用程序在端口 localhost 上运行。 正在运行的应用程序可能有不同的地址和端口。

测试 API

  1. 打开浏览器并导航到 Todo 实体的 REST 终结点。

    http://localhost:5000/api/Todo

  2. JSON 响应应包含所有三个待办事项。

    {
  "value": [
    { "id": 1, "title": "Walk the dog", "completed": false },
    { "id": 2, "title": "Feed the fish", "completed": false },
    { "id": 3, "title": "Comb the cat", "completed": true }
  ]
}

  3. 导航到 Swagger 文档页面。/swagger

    http://localhost:5000/swagger

生成 Web 应用

使用一个简单的 HTML 文件在浏览器中显示您的待办事项。 使用 REST 或 GraphQL 终结点创建一个名为 todo.html 的文件。

<!DOCTYPE html>
<html lang="en">
<head>
  <meta charset="UTF-8">
  <title>Todo App</title>
  <style>
    body { font-family: sans-serif; max-width: 400px; margin: 2rem auto; }
    li.done { text-decoration: line-through; color: gray; }
    #error { color: red; }
  </style>
</head>
<body>
  <h1>Todos</h1>
  <ul id="list"></ul>
  <p id="error"></p>
  <script>
    fetch('http://localhost:5000/api/Todo')
      .then(r => r.json())
      .then(data => {
        const ul = document.getElementById('list');
        data.value.forEach(todo => {
          const li = document.createElement('li');
          li.textContent = todo.title;
          if (todo.completed) li.className = 'done';
          ul.appendChild(li);
        });
      })
      .catch(() => {
        document.getElementById('error').textContent =
          'Could not reach the API. Make sure DAB is running on http://localhost:5000.';
      });
  </script>
</body>
</html>

在浏览器中打开 todo.html 。 该页提取所有待办事项并将其呈现为列表，其中已完成的项目显示在删除线中。

重要

配置 cors 中的设置允许从本地文件系统打开此 HTML 文件来调用 API。 如果没有它，浏览器将阻止请求。

清理

完成后停止并删除 Docker 容器。

docker stop dab-mssql && docker rm dab-mssql

使用GitHub Copilot重新创建本快速入门

打开要在Visual Studio Code中创建示例的工作区，将GitHub Copilot切换到代理模式，然后粘贴此提示。

You are GitHub Copilot running in agent mode. Recreate the Data API builder basic SQL quickstart as a complete, runnable local project in the current VS Code workspace under `quickstart-00-basic-sql`. Build a local Docker-based sample that starts one database engine, creates and seeds a `todos` database, configures Data API builder (DAB), exposes REST, GraphQL, and MCP endpoints, adds MCP Inspector for DAB MCP testing, and creates a small static web app that calls DAB. Keep the implementation minimal, but make the web interface neat and approachable: responsive layout, accessible labels, clear loading and error states, and simple styling that is polished rather than austere.

Source repository guidance: no dedicated Azure-Samples repository currently appears for this basic SQL quickstart. However, https://github.com/Azure-Samples/dab-2.0-quickstart-web_anon-api_anon-db_sql_auth is very close and features such as the database and the web site can be reused. If internet access is available, review that site and reuse shared file patterns when they match this local Docker quickstart. Otherwise, implement from this article and the current Data API builder docs. Do not invent a different architecture or add extra services beyond this prompt.

Minimize user interaction. Use the defaults in this prompt and make reasonable best guesses for noncritical choices. Do not ask for a root folder or project folder name; use the current VS Code workspace and the default subfolder. Ask only when you need approval for resource changes, secrets, permissions, materially higher cost, external account choices, or an ambiguous requirement that affects the architecture.

Start with a short plan and proceed with safe defaults before you create files or run commands. Use SQL Server, the default `todos` schema and seed data, SQL Commander, the listed non-default host ports, and local Docker only unless the user explicitly asks for a different database engine or an Azure extension. Ask only these questions if the values aren't already available from the environment or prior context:

- If you want an Azure extension, which Azure subscription, primary region, fallback region, and resource group should it use? Default fallback region: `westus2`.

Show a short checklist before implementation. Include phases for project scaffold, Docker Compose, database initialization, DAB configuration, web app, MCP Inspector, validation, and cleanup. Proceed with local files and local Docker validation without asking for extra confirmation. Do not create Azure resources for this quickstart unless the user explicitly asks for an Azure extension and approves the exact Azure command set.

After you start, continue working without asking status-check questions. If a command, build, container, endpoint, or validation step fails, inspect the error, adjust the project, rerun the step, and continue. Keep iterating until the sample runs end-to-end or you hit a blocker that requires user action.

Use cost-first defaults. The default solution is local Docker only with no Azure cost. If the user asks for an Azure extension, choose the cheapest option that satisfies the selected database engine: use a free Azure SQL database offer when SQL Server is selected and the subscription and region support it; otherwise choose the lowest-cost Azure database option that supports the selected SQL Server, PostgreSQL, or MySQL scenario. Use Azure Container Apps consumption, minimal CPU and memory, Basic Azure Container Registry, minimal Log Analytics retention, and no always-on or dedicated plans unless required. Prioritize finishing the project. Treat regional provisioning limits as expected adjustment points, not failures: if the primary region can't provision a required service or free SQL option, use the approved fallback region such as `westus2`, and continue the deployment. Ask the user only when both the primary and fallback regions can't satisfy the requirements, when a change would materially increase cost, when a new permission is required, or when you need approval for Azure commands that create or change resources beyond the already-approved plan.

Verify prerequisites and report only missing items: Docker Desktop running, .NET SDK, DAB CLI, and a shell that can run Docker Compose. Use the DAB CLI docs while building: https://learn.microsoft.com/azure/data-api-builder/command-line/.

Use these docs during implementation:

- DAB CLI reference: https://learn.microsoft.com/azure/data-api-builder/command-line/
- `dab init`: https://learn.microsoft.com/azure/data-api-builder/command-line/dab-init
- `dab add`: https://learn.microsoft.com/azure/data-api-builder/command-line/dab-add
- `dab validate`: https://learn.microsoft.com/azure/data-api-builder/command-line/dab-validate
- `dab start`: https://learn.microsoft.com/azure/data-api-builder/command-line/dab-start
- DAB MCP overview: https://learn.microsoft.com/azure/data-api-builder/mcp/overview
- DAB configuration: https://learn.microsoft.com/azure/data-api-builder/configuration/

Create this structure under the sample folder:

- `docker-compose.yml` for the selected database, DAB, MCP Inspector, and the web app.
- `.env` for local passwords and connection strings.
- `.gitignore` with `.env`, `**/bin`, and `**/obj`.
- `database/` for selected-engine initialization scripts.
- `data-api/dab-config.json` for DAB configuration.
- `web-app/` for static HTML, CSS, and JavaScript.
- `mcp-inspector/README.md` with the auto-connect URL.
- `README.md` with run, validation, troubleshooting, and cleanup steps.

Handle secrets first. Add `.env` to `.gitignore` before writing passwords. Use `DATABASE_PASSWORD` and `DATABASE_CONNECTION_STRING`. Never print secret values. Use `@env('DATABASE_CONNECTION_STRING')` in `dab-config.json`. Avoid `$` in Docker Compose passwords because Compose treats `$` as variable interpolation.

Use Docker Compose, not raw `docker run`, for the generated project. Containers must talk by service name, not `localhost`. Mount `data-api/dab-config.json` into DAB read-only at `/App/dab-config.json`. Use health checks and `depends_on` so DAB starts after the selected database is healthy.

Implement database initialization explicitly. For PostgreSQL and MySQL, mount selected-engine scripts into `/docker-entrypoint-initdb.d` for first-run initialization. For SQL Server, add a one-shot init service or setup script that waits for the `db` service to become healthy and then runs `sqlcmd` to create the `todos` database, table, and seed rows. Do not assume the database health check creates the database or schema.

Use one of these selected-engine configurations.

SQL Server:

```yaml
services:
  db:
    image: mcr.microsoft.com/mssql/server:2025-latest
    environment:
      ACCEPT_EULA: "Y"
      MSSQL_SA_PASSWORD: ${DATABASE_PASSWORD}
    ports:
      - "14330:1433"
    healthcheck:
      test: /opt/mssql-tools18/bin/sqlcmd -S localhost -U sa -P "${DATABASE_PASSWORD}" -C -Q "SELECT 1" || exit 1
      interval: 10s
      timeout: 5s
      retries: 10
```

PostgreSQL:

```yaml
services:
  db:
    image: postgres:16
    environment:
      POSTGRES_PASSWORD: ${DATABASE_PASSWORD}
    ports:
      - "54320:5432"
    healthcheck:
      test: ["CMD-SHELL", "pg_isready -U postgres"]
      interval: 10s
      timeout: 5s
      retries: 10
```

MySQL:

```yaml
services:
  db:
    image: mysql:8
    environment:
      MYSQL_ROOT_PASSWORD: ${DATABASE_PASSWORD}
    ports:
      - "33060:3306"
    healthcheck:
      test: ["CMD", "mysqladmin", "ping", "-h", "localhost"]
      interval: 10s
      timeout: 5s
      retries: 10
```

Use the selected database engine only. Do not scaffold all three engines unless the user asks for a matrix sample.

Use the matching schema and connection details.

SQL Server:

```sql
CREATE DATABASE todos;
GO
USE todos;
GO
CREATE TABLE dbo.todos (id int PRIMARY KEY, title nvarchar(100) NOT NULL, completed bit NOT NULL DEFAULT 0);
INSERT INTO dbo.todos VALUES (1, 'Walk the dog', 0), (2, 'Feed the fish', 0), (3, 'Comb the cat', 1);
```

```text
DATABASE_CONNECTION_STRING=Server=db;Database=todos;User Id=sa;Password=<password>;TrustServerCertificate=true;Encrypt=true;
```

PostgreSQL:

```sql
CREATE DATABASE todos;
\c todos
CREATE TABLE todos (id int PRIMARY KEY, title varchar(100) NOT NULL, completed boolean NOT NULL DEFAULT false);
INSERT INTO todos VALUES (1, 'Walk the dog', false), (2, 'Feed the fish', false), (3, 'Comb the cat', true);
```

```text
DATABASE_CONNECTION_STRING=Host=db;Port=5432;Database=todos;User ID=postgres;Password=<password>;
```

MySQL:

```sql
CREATE DATABASE todos;
USE todos;
CREATE TABLE todos (id int PRIMARY KEY, title varchar(100) NOT NULL, completed bool NOT NULL DEFAULT false);
INSERT INTO todos VALUES (1, 'Walk the dog', false), (2, 'Feed the fish', false), (3, 'Comb the cat', true);
```

```text
DATABASE_CONNECTION_STRING=Server=db;Port=3306;Database=todos;User=root;Password=<password>;
```

Use the DAB CLI workflow for the selected engine and validate after each config change.

SQL Server:

```dotnetcli
dab init --config data-api/dab-config.json --database-type mssql --host-mode Development --connection-string "@env('DATABASE_CONNECTION_STRING')" --rest.enabled true --graphql.enabled true --mcp.enabled true
dab add Todo --config data-api/dab-config.json --source dbo.todos --source.type table --permissions "anonymous:*" --mcp.dml-tools true
dab validate --config data-api/dab-config.json
```

PostgreSQL:

```dotnetcli
dab init --config data-api/dab-config.json --database-type postgresql --host-mode Development --connection-string "@env('DATABASE_CONNECTION_STRING')" --rest.enabled true --graphql.enabled true --mcp.enabled true
dab add Todo --config data-api/dab-config.json --source public.todos --source.type table --permissions "anonymous:*" --mcp.dml-tools true
dab validate --config data-api/dab-config.json
```

MySQL:

```dotnetcli
dab init --config data-api/dab-config.json --database-type mysql --host-mode Development --connection-string "@env('DATABASE_CONNECTION_STRING')" --rest.enabled true --graphql.enabled true --mcp.enabled true
dab add Todo --config data-api/dab-config.json --source todos --source.type table --permissions "anonymous:*" --mcp.dml-tools true
dab validate --config data-api/dab-config.json
```

Use this DAB container pattern in Compose:

```yaml
  data-api:
    image: mcr.microsoft.com/azure-databases/data-api-builder:latest
    environment:
      DATABASE_CONNECTION_STRING: ${DATABASE_CONNECTION_STRING}
    ports:
      - "5000:5000"
    volumes:
      - ./data-api/dab-config.json:/App/dab-config.json:ro
    depends_on:
      db:
        condition: service_healthy
```

Configure DAB CORS before you start the browser-based web app. Do not leave `runtime.host.cors.origins` as `[]`. Set it to include the exact web app origin, including scheme and port, such as `http://localhost:8000` for this Docker Compose web app. Keep `allow-credentials` set to `false` unless the sample explicitly uses browser credentials or cookies. Direct REST, GraphQL, or Swagger requests can succeed even when the browser blocks JavaScript fetch calls, so browser-origin CORS must be configured and validated separately.

Add MCP Inspector with the auto-connect URL. Use Streamable HTTP and omit auth only for local development.

```yaml
  mcp-inspector:
    image: ghcr.io/modelcontextprotocol/inspector:latest
    environment:
      HOST: 0.0.0.0
      MCP_AUTO_OPEN_ENABLED: "false"
      DANGEROUSLY_OMIT_AUTH: "true"
    ports:
      - "6274:6274"
      - "6277:6277"
    depends_on:
      - data-api
```

```text
http://localhost:6274/?transport=streamable-http&serverUrl=http%3A%2F%2Fdata-api%3A5000%2Fmcp
```

Use the Compose service name `data-api` in the MCP Inspector auto-connect URL because MCP Inspector runs in the Compose network. Also document a host-side MCP URL for VS Code or direct browser testing:

```text
http://localhost:5000/mcp
```

For SQL Server only, include SQL Commander if the user wants a database browser. Use env var `ConnectionStrings__db` and include `TrustServerCertificate=true`.

```yaml
  sql-commander:
    image: jerrynixon/sql-commander:latest
    environment:
      ConnectionStrings__db: ${DATABASE_CONNECTION_STRING}
    ports:
      - "8080:8080"
    depends_on:
      db:
        condition: service_healthy
```

Build the static web app with minimal code and a polished UI. It should show the todo list, loading state, empty state, error state, API base URL, and quick links to REST, GraphQL, Swagger, and MCP Inspector. Keep dependencies minimal; use plain HTML, CSS, and JavaScript unless the user asks for a framework.

Validate before reporting success:

- `docker compose up -d` starts the selected database, DAB, MCP Inspector, and web app.
- The selected database health check passes.
- The `todos` database and table exist with three seeded rows.
- A direct database query returns the three seeded todo rows.
- `dab validate --config data-api/dab-config.json` exits with code 0.
- DAB `/health` returns a 2xx response.
- REST returns the three todo rows at `http://localhost:5000/api/Todo`.
- GraphQL returns the three todo rows.
- Swagger opens at `http://localhost:5000/swagger`.
- A browser-origin request from the web app origin, for example `http://localhost:8000`, receives an `Access-Control-Allow-Origin` response header that matches that origin.
- MCP Inspector opens with the auto-connect URL and can list DAB tools.
- The web site returns a successful HTTP response.
- The web app displays the todo rows and looks neat, not austere.
- `README.md` includes run, validation, troubleshooting, and cleanup steps.

Do not report final URLs, asset locations, or a success summary until you directly verify database connectivity and query results, a 2xx DAB health response, and a successful web site response. This validation ensures the sample works without requiring the developer to check.

后续步骤

REST 终结点

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