DBX：25MB 跨平台数据库客户端，支持 100+ 数据库与 AI Agent 集成

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🪶 25 MB，无运行时臃肿

无需 Java JRE，无需 Python venv，也不捆绑 Chromium。DBX 以单个小型二进制文件交付——下载、安装、连接。DBeaver 需要 Java；TablePlus 采用 Freemium 模式。DBX 可在各处运行，无需额外依赖。|

🤖 原生驻留在编辑器中的 AI

高亮选中一张表，描述你的需求，即可获得 SQL——无需在工具之间复制粘贴。支持通过 Claude、OpenAI 或 Ollama 接入本地模型。内置安全检查会在 AI 生成的 SQL 执行前进行审查。 ---|---

🔌 MCP：让你的数据库具备 AI 就绪能力

DBX 支持 Model Context Protocol。Claude Code、Cursor、Windsurf 及其他 AI 编程 Agent 可通过你已配置的连接查询数据库。一份配置，处处可用。| 原生应用覆盖 macOS、Windows 和 Linux。可通过 Docker 自托管以供团队使用；也提供面向仅浏览器环境的 Web 版本。功能集相同，连接相同。 消息队列和中间件拥有一等控制台支持：Kafka、RocketMQ、RabbitMQ、Pulsar 和 MQTT，以及 Nacos、Consul、ZooKeeper 和 etcd。可在数据库旁查看主题与消息——无需额外工具。| 通过内置商店中的已签名、沙箱化插件扩展 DBX，支持 S3、Kubernetes、LDAP 等。还可使用 Go / TypeScript SDK 构建自己的插件。

MySQL、PostgreSQL、SQLite、Cloudflare D1、Redis、MongoDB、DuckDB、ClickHouse、SQL Server、Oracle、Elasticsearch、Easysearch、Meilisearch、Qdrant、Milvus、Weaviate、MariaDB、TiDB、OceanBase、openGauss、GaussDB、KWDB、KingbaseES、Vastbase、GoldenDB、Doris、SelectDB、StarRocks、Manticore Search、Redshift、DM、TDengine、XuguDB、CockroachDB、Access、HighGo、UXDB、Dolt 等。基于 Agent 的配置文件可将 DBX 扩展至 H2、Snowflake、Trino、PrestoSQL、Hive、DB2、Informix、Neo4j、Cassandra、BigQuery、Cloud Spanner、Kylin、SunDB、JDBCX 及自定义 JDBC 连接。新增的原生和 Agent 驱动程序还覆盖 Databricks、SAP HANA、Teradata、Vertica、Firebird、Exasol、YashanDB、GBase 8a/8s、Databend、RQLite、Turso、InfluxDB、QuestDB、IoTDB、etcd、ZooKeeper、Nacos、Consul KV、IRIS 等。全部集成于一个约 25 MB 的应用中，不捆绑 Chromium。

基于 CodeMirror 6，提供 SQL 语法高亮、感知元数据的自动补全、Cmd+Enter 执行、选中 SQL 执行、SQL 格式化、诊断和 9 套编辑器主题。持久化查询历史、保存的 SQL 片段、标签页恢复及 SQL 文件执行功能，让重复工作触手可及。

用自然语言描述你的需求，即可获得 SQL。DBX 可解释查询、优化 SQL、修复错误，并通过内置安全检查执行 AI 生成的 SQL。支持 Claude、OpenAI、本地模型或任意 OpenAI 兼容端点。

采用虚拟滚动的数据表可处理大型结果集。支持内联编辑、保存前 SQL 预览、WHERE / ORDER BY 控制、DataGrip 风格过滤器、LIKE / NOT LIKE 上下文筛选、排序、全文搜索、分页、列宽调整、自动适配、行号、斑马纹及完整单元格详情。可导出或复制为 CSV、JSON、Markdown、XLSX 或 INSERT 语句。

• Schema 浏览器 —— 数据库、Schema、表、列、索引、外键、触发器，支持侧栏搜索和固定

• 对象浏览器 —— 按组查看存储过程、函数、视图，并在支持时编辑源代码

• 表结构编辑器 —— 对支持的数据库引擎审查列和索引变更

• ER 图 —— 可视化表关系

• Schema 差异对比 —— 比较不同连接之间的结构

• 执行计划 —— 可视化查询执行计划

• 字段血缘 —— 列级血缘分析

• 数据库搜索 —— 在大型 Schema 中查找对象

• 表导入 —— CSV、Excel

• 数据传输 —— 在数据库之间迁移

• 数据库导出 —— 完整数据库转储

• 数据对比 —— 比较表数据并审查同步输出

• SQL 文件执行 —— 直接运行 .sql 文件

• 文件预览 —— 拖放 Parquet、CSV、JSON 文件即可即时预览（由 DuckDB 驱动）

• 连接导入 —— 从 DBeaver 或 Navicat 导入连接配置

• Redis —— 键模式搜索、批量键操作、命令执行器、TTL 编辑及所有数据类型（String、Hash、List、Set、ZSet、Stream）

• MongoDB —— 支持分页的文档 CRUD，以及 Atlas 和副本集 URL 连接

消息队列与中间件控制台

• Kafka / RocketMQ / RabbitMQ / Pulsar —— 主题、消费者组、消息浏览、查询与追踪、Broker 监控、权限和策略

• MQTT —— 主题树导航、订阅与发布

• Nacos / Consul / ZooKeeper / etcd —— 服务发现、KV / 配置浏览、健康状态和 ACL

• 可扩展设计 —— 新连接类型和工具以插件形式提供：可从内置商店获取 S3 浏览、Kubernetes、LDAP 等功能

• 签名与沙箱化 —— 每个插件包安装前均会验证签名；插件 UI 在拥有独立 Sidecar 进程的沙箱中运行

• 构建自己的插件 —— 使用 Go / TypeScript SDK 和 npx @dbx-app/plugin-cli 脚手架；通过 t8y2/dbx-store 发布到 Marketplace

SSH 隧道（密钥和密码）· 数据库与 AI 代理设置 · 连接中断自动重连 · 破坏性操作确认对话框 · 加密配置导出/导入 · 连接颜色标记 · 驱动商店及可选 JDBC 插件

深色模式与原生标题栏同步 · 9 套编辑器主题 · 英语、简体中文和西班牙语 · 布局偏好设置 · 内置自动更新

AI Agent 集成（MCP）

DBX 提供独立的由 Rust 驱动的 MCP Server，让 AI 编程 Agent 可使用 DBX 中配置的连接查询数据库。MCP Server 与桌面应用独立分发，因此安装 DBX 不会自动安装 MCP 可执行文件。

将以下内容添加至你的 .mcp.json：

{
  "mcpServers": {
    "dbx": { "command": "npx", "args": ["-y", "@dbx-app/mcp-server"] }
  }
}

在 DBX 设置 → MCP 中管理连接允许列表，以及 只读、数据读/写 和 完全访问 模式。机器可读的值仍分别为 read_only、safe_write 和 high_risk_write；客户端配置无需设置权限或连接范围环境变量。

为保持升级兼容性，已有的 DBX_MCP_ALLOW_WRITES=0（或 false）仅会维持只读限制，直至首次保存中央 MCP 策略；它绝不会启用写入权限，也无法覆盖已保存的策略。

Windows 便携版需要在 MCP 配置中设置 DBX_DATA_DIR，指向 DBX.exe 同级的 data 目录（即包含 dbx.db 的文件夹）。

对于 DBX Web 或 Docker 部署，请让 MCP Server 指向 Web 后端 API。若 Web 登录页面需要密码，请将 DBX_WEB_PASSWORD 设置为同一个密码：

{
  "mcpServers": {
    "dbx": {
      "command": "npx",
      "args": ["-y", "@dbx-app/mcp-server"],
      "env": {
        "DBX_WEB_URL": "http://localhost:4224",
        "DBX_WEB_PASSWORD": "your-web-login-password"
      }
    }
  }
}

支持 Claude Code、Cursor、Windsurf 及任意兼容 MCP 的 Agent。支持列出连接、浏览表、执行 SQL，以及直接在 DBX UI 中打开表。

macOS、Linux 和 Windows 的预编译原生二进制文件也发布在软件包发行版中。它们无需 Node.js 即可运行，适用于离线或服务器环境。npm 安装方式则通过一个小型 Node.js 启动器使用相同的 Rust 二进制文件。

DBX 还提供专用 CLI 包，用于终端、脚本和 Codex 工作流：

npm install -g @dbx-app/cli
# or via Homebrew
brew tap t8y2/tap && brew install dbx-cli
dbx agent setup
dbx connections list --json
dbx query local "select 1" --json

CLI 包含官方 DBX Agent Skill。dbx agent setup 会在 ~/.agents/skills/dbx 下离线安装或更新该 Skill，使具备 Shell 能力的 AI Agent 知道如何安全使用 DBX CLI。

详见 MCP Server README 和 CLI README。

可从 Releases 页面下载最新版本。

Homebrew（macOS）：

Scoop（Windows）：

scoop bucket add dbx https://github.com/t8y2/scoop-bucket
scoop install dbx

WinGet（Windows）：

Flatpak（Linux）：

flatpak remote-add --if-not-exists flatpark https://dl.flatpark.org/flatpark.flatpakrepo
flatpak install flatpark com.dbxio.dbx

后续更新可通过常规的 flatpak update 获取。详情参见 FlatPark 上的 DBX 页面。

如需在关闭桌面应用或浏览器后执行计划备份，请参阅后台数据库备份，其中包括 Windows/macOS/Linux 启动配置和持久化容器备份卷说明。

DBX 提供可通过 Docker 部署的 Web 版本。以下示例使用 latest 标签拉取当前发行版本。

# The default keeps the key in the persistent /app/data volume.
docker run -d --pull=always --name dbx -p 4224:4224 \
  -v dbx-data:/app/data \
  t8y2/dbx:latest

这会使用跨平台的 dbx-data 命名卷。中国用户可使用 CNB 镜像 docker.cnb.cool/dbxio.com/dbx:latest 以获得更快的拉取速度。

对于 Docker Compose，deploy/docker-compose.yml 仍是从源码构建时使用的配置。若要部署已发布镜像，请使用 deploy/docker-compose.release.yml：

docker compose -f deploy/docker-compose.release.yml up -d

services:
  dbx:
    image: t8y2/dbx:latest
    # For faster pulls in China, use the CNB image instead:
    # image: docker.cnb.cool/dbxio.com/dbx:latest
    pull_policy: always
    ports:
      - "4224:4224"
    volumes:
      - dbx-data:/app/data
    restart: unless-stopped

volumes:
  dbx-data:

在浏览器中打开 http://localhost:4224。提供多架构镜像（amd64 / arm64）。

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	Special thanks to AICodeMirror for sponsoring this project! AICodeMirror provides a high-stability official relay service for Claude Code / Codex / Gemini CLI, with enterprise-grade concurrency, fast invoicing, and 7×24 dedicated support. Official-channel pricing for Claude Code / Codex / Gemini is as low as 38% / 2% / 9% of list price, with extra discounts on top-ups! AICodeMirror offers a special benefit for DBX users: register through this link to enjoy 20% off your first top-up, and enterprise customers up to 25% off. Visit AICodeMirror
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🪶 25 MB, zero runtime bloat

No Java JRE. No Python venv. No bundled Chromium. DBX ships as a single small binary — download, install, connect. DBeaver needs Java; TablePlus is Freemium. DBX runs everywhere with nothing extra. |

🤖 AI that lives in your editor

Highlight a table, describe what you want, get SQL back — no copy-paste between tools. Works with Claude, OpenAI, or local models via Ollama. Built-in safety checks review AI-generated SQL before it runs.
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🔌 MCP: your databases, AI-ready

DBX speaks the Model Context Protocol. Claude Code, Cursor, Windsurf, and other AI coding agents can query your databases through connections you already set up. One config, everywhere. | Native app on macOS, Windows, and Linux. Self-host via Docker for team access. Web version for browser-only environments. Same feature set. Same connections.
Message queues and middleware get first-class consoles: Kafka, RocketMQ, RabbitMQ, Pulsar, and MQTT, plus Nacos, Consul, ZooKeeper, and etcd. Inspect topics and messages next to your databases — no extra tool. | Extend DBX with signed, sandboxed plugins from the built-in store — S3, Kubernetes, LDAP, and more. Build your own with the Go / TypeScript SDK.

MySQL, PostgreSQL, SQLite, Cloudflare D1, Redis, MongoDB, DuckDB, ClickHouse, SQL Server, Oracle, Elasticsearch, Easysearch, Meilisearch, Qdrant, Milvus, Weaviate, MariaDB, TiDB, OceanBase, openGauss, GaussDB, KWDB, KingbaseES, Vastbase, GoldenDB, Doris, SelectDB, StarRocks, Manticore Search, Redshift, DM, TDengine, XuguDB, CockroachDB, Access, HighGo, UXDB, Dolt, and more. Agent-based profiles extend DBX to H2, Snowflake, Trino, PrestoSQL, Hive, DB2, Informix, Neo4j, Cassandra, BigQuery, Cloud Spanner, Kylin, SunDB, JDBCX, and custom JDBC connections. New native and agent-driven drivers also cover Databricks, SAP HANA, Teradata, Vertica, Firebird, Exasol, YashanDB, GBase 8a/8s, Databend, RQLite, Turso, InfluxDB, QuestDB, IoTDB, etcd, ZooKeeper, Nacos, Consul KV, IRIS, and more. All in a single ~25 MB app. No bundled Chromium.

CodeMirror 6 with SQL syntax highlighting, metadata-aware autocomplete, Cmd+Enter execution, selected SQL execution, SQL formatting, diagnostics, and 9 editor themes. Persistent query history, saved SQL snippets, tab restore, and SQL file execution keep repeat work close at hand.

Describe what you want in plain language — get SQL back. DBX can explain queries, optimize SQL, fix errors, and run AI-generated SQL through built-in safety checks. Works with Claude, OpenAI, local models, or any OpenAI-compatible endpoint.

Virtual-scrolled table that handles large result sets. Inline editing, SQL preview before save, WHERE / ORDER BY controls, DataGrip-style filters, LIKE / NOT LIKE context filters, sorting, full-text search, pagination, column resize, auto-fit, row numbers, zebra stripes, and full cell details. Export or copy as CSV, JSON, Markdown, XLSX, or INSERT statements.

• Schema browser — databases, schemas, tables, columns, indexes, foreign keys, triggers, with sidebar search & pin

• Object browser — grouped procedures, functions, views, and source editing where supported

• Table structure editor — reviewable column and index changes for supported engines

• ER diagram — visualize table relationships

• Schema diff — compare structures across connections

• Explain plan — visual query execution plan

• Field lineage — column-level lineage analysis

• Database search — find objects across large schemas

• Table import — CSV, Excel

• Data transfer — migrate between databases

• Database export — full database dump

• Data compare — compare table data and review synchronization output

• SQL file execution — run .sql files directly

• File preview — drag & drop Parquet, CSV, JSON to preview instantly (powered by DuckDB)

• Connection import — bring connection profiles from DBeaver or Navicat

• Redis — key pattern search, batch key operations, command runner, TTL editing, and all data types (String, Hash, List, Set, ZSet, Stream)

• MongoDB — document CRUD with pagination, Atlas & replica set URL connection

Message Queue & Middleware Consoles

• Kafka / RocketMQ / RabbitMQ / Pulsar — topics, consumer groups, message browsing, query and trace, broker monitoring, permissions and policies

• MQTT — topic tree navigation, subscribe, and publish

• Nacos / Consul / ZooKeeper / etcd — service discovery, KV / config browsing, health, and ACL

• Extensible by design — new connection types and tools arrive as plugins: S3 browsing, Kubernetes, LDAP, and more from the built-in store

• Signed & sandboxed — every plugin package is signature-verified before install; plugin UI runs sandboxed with its own sidecar process

• Build your own — Go / TypeScript SDKs with npx @dbx-app/plugin-cli scaffolding; publish to the Marketplace via t8y2/dbx-store

SSH tunnel (key & password) · database and AI proxy settings · auto-reconnect on connection loss · confirmation dialogs for destructive operations · encrypted config export/import · color-coded connections · driver store and optional JDBC plugin

Dark mode with native title bar sync · 9 editor themes · English, 简体中文 & Español · layout preferences · built-in auto-update

AI Agent Integration (MCP)

DBX provides a separate Rust-powered MCP server that lets AI coding agents query databases using connections configured in DBX. The MCP server is distributed independently from the desktop application, so installing DBX does not automatically install the MCP executable.

Add to your .mcp.json:

{
  "mcpServers": {
    "dbx": { "command": "npx", "args": ["-y", "@dbx-app/mcp-server"] }
  }
}

Manage the connection allowlist and the Read only , Data read/write , and Full access modes in DBX Settings → MCP. The machine-readable values remain read_only, safe_write, and high_risk_write; client configs do not need permission or connection-scope environment variables.

For upgrade compatibility, an existing DBX_MCP_ALLOW_WRITES=0 (or false) remains a read-only restriction only until a central MCP policy is saved for the first time; it can never enable writes or override a saved policy.

Windows portable builds need DBX_DATA_DIR in the MCP config, pointing to the data directory next to DBX.exe (the folder that contains dbx.db).

For DBX Web or Docker deployments, point the MCP server at the Web backend API. If the Web login page requires a password, set DBX_WEB_PASSWORD to the same password used there:

{
  "mcpServers": {
    "dbx": {
      "command": "npx",
      "args": ["-y", "@dbx-app/mcp-server"],
      "env": {
        "DBX_WEB_URL": "http://localhost:4224",
        "DBX_WEB_PASSWORD": "your-web-login-password"
      }
    }
  }
}

Works with Claude Code, Cursor, Windsurf, and any MCP-compatible agent. Supports listing connections, browsing tables, executing SQL, and opening tables directly in DBX's UI.

Precompiled native binaries are also published for macOS, Linux, and Windows in package releases. They run without Node.js and are suitable for offline or server environments. The npm installation uses the same Rust binary through a small Node.js launcher.

DBX also provides a dedicated CLI package for terminal, script, and Codex workflows:

npm install -g @dbx-app/cli
# or via Homebrew
brew tap t8y2/tap && brew install dbx-cli
dbx agent setup
dbx connections list --json
dbx query local "select 1" --json

The CLI includes the official DBX Agent Skill. dbx agent setup installs or updates it offline under ~/.agents/skills/dbx, so shell-capable AI agents know how to use DBX CLI safely.

See the MCP server README and CLI README for details.

Download the latest release from the Releases page.

Homebrew (macOS):

Scoop (Windows):

scoop bucket add dbx https://github.com/t8y2/scoop-bucket
scoop install dbx

WinGet (Windows):

Flatpak (Linux):

flatpak remote-add --if-not-exists flatpark https://dl.flatpark.org/flatpark.flatpakrepo
flatpak install flatpark com.dbxio.dbx

Updates then arrive through the regular flatpak update. See the DBX page on FlatPark for details.

For scheduled backups after closing the desktop app or browser, see Background Database Backups, including Windows/macOS/Linux startup and persistent container backup volumes.

DBX provides a web version that can be deployed via Docker. The examples use the latest tag to pull the current release.

# The default keeps the key in the persistent /app/data volume.
docker run -d --pull=always --name dbx -p 4224:4224 \
  -v dbx-data:/app/data \
  t8y2/dbx:latest

This uses the cross-platform dbx-data named volume. Users in China can use the CNB image, docker.cnb.cool/dbxio.com/dbx:latest, for faster pulls.

For Docker Compose, deploy/docker-compose.yml remains the source-build configuration. To deploy a published image, use deploy/docker-compose.release.yml:

docker compose -f deploy/docker-compose.release.yml up -d


services:
  dbx:
    image: t8y2/dbx:latest
    # For faster pulls in China, use the CNB image instead:
    # image: docker.cnb.cool/dbxio.com/dbx:latest
    pull_policy: always
    ports:
      - "4224:4224"
    volumes:
      - dbx-data:/app/data
    restart: unless-stopped

volumes:
  dbx-data:

Open http://localhost:4224 in your browser. Multi-arch images (amd64 / arm64) are available.

Connection, plugin, AI, and tunnel credentials are encrypted before they are written to dbx.db. Desktop builds use the local platform credential store (macOS Keychain, Windows Credential Manager, or Linux Secret Service). Web/Docker and directly running dbx-web use the same managed data-directory key by default: ${DBX_DATA_DIR}/.dbx/secret.key. The key is created only when migration starts or the first sensitive value is written, and must be backed up together with dbx.db. Persisting /app/data is therefore sufficient for a normal Docker deployment. This key protects the database contents, but cannot protect the whole data volume if the volume itself is copied or exposed.

For production deployments, replace the managed key with a Docker/Kubernetes Secret by setting DBX_SECRET_KEY_FILE, or provide DBX_SECRET_KEY through a secret manager. Explicit keys take precedence and must never be rotated while encrypted data is in use. Without a usable key, business APIs remain blocked and the browser displays the data security upgrade screen.

When running the binary directly, set DBX_DATA_DIR=/var/lib/dbx to use /var/lib/dbx/.dbx/secret.key with the same lifecycle and backup rules.

When upgrading from a release that stored credentials in plain text, Desktop and Web display a Data Security Upgrade wizard before opening the main application. Choose Start upgrade to create a restricted backup, migrate legacy database/JSON credentials, and verify that encrypted values can be read. Failures retain the original data and backup; fix the issue shown in the wizard and choose Retry. The backup path is shown after success. Once you have verified your connections, Delete migration backups asks for confirmation and removes the migration backup directory and the legacy JSON .bak files created by that migration. Unrelated backup files are kept. Users with no legacy data proceed directly after the initial check.

Local CLI and standalone MCP can reuse the existing platform credential store on the same device, or read an explicitly configured DBX_SECRET_KEY_FILE/DBX_SECRET_KEY. They do not create keys during the startup check or automatically migrate legacy data. A DATA_MIGRATION_REQUIRED error means that you must first open the same data directory in Desktop or Web and complete its upgrade wizard. For headless hosts without a platform credential store, configure the persistent key.

Cross-device exports use a separate sync passphrase and never contain the local storage key. A direct dbx.db copy is not a cross-platform sync method: platform keys do not move with the database. Use encrypted export/import so the target device stores credentials using its own local key.

For the complete design, migration state machine, implementation map, troubleshooting, and test plan, see DBX Data Security Upgrade and Migration.

To publish DBX under a reverse-proxy context path such as /dbx, set the runtime base path and proxy the same prefix to the container:

environment:
  - DBX_PUBLIC_BASE_PATH=/dbx

When building the frontend yourself with an absolute asset base, set VITE_DBX_BASE_PATH=/dbx/ before pnpm build.

macOS:

No additional dependencies required.

Linux (Ubuntu/Debian):

sudo apt-get install -y libwebkit2gtk-4.1-dev libgtk-3-dev libappindicator3-dev librsvg2-dev patchelf libssl-dev

NIXOS/NIX :

See README-NIX.md

Windows:

No additional dependencies required.

make installs root dependencies when needed and starts the local Tauri desktop development environment.

Development builds can run alongside an installed DBX instance and share its local data, including connections and history. Avoid changing the same connection or global setting in both windows at once.

Tip

DuckDB compilation takes a while. If you're not working on DuckDB features, skip it to speed up local builds:

# Fast checks (skip DuckDB)
make cargo-check-fast
make cargo-test-fast

# Tauri dev without DuckDB
make dev-fast

The --no-default-features flag only affects local development. Release builds (pnpm tauri build) always include DuckDB.

Web version:

make dev-web       # frontend
make dev-backend   # backend

Documentation site:

The official DBX documentation site lives in docs/. If you want to improve the website content or documentation pages, edit the files under docs/ and run make docs to preview the site locally.

Plugin authors should start with Develop and Submit DBX Plugins. Plugin source normally stays in its own repository; Marketplace listing pull requests go to t8y2/dbx-store, while plugin host, SDK, and CLI changes go to this repository.

For clean, reproducible local database instances, use the versioned Docker Compose recipes under deploy/database/:

make db-list
make db-verify DB=mysql@8.4

JDBC agent driver development projects live in agents/:

Build artifacts from agents/drivers/<db-type>/build/libs/ are picked up by local driver install flows when available.

The installer will be in src-tauri/target/release/bundle/.

DBX is free and open source, but ongoing maintenance, database compatibility testing, infrastructure, and release work require sustained time and resources.

Community

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