
Dbx
io.github.t8y2由 GitHub 帳號 t8y2 發布v0.1.3更新於 Oct 24, 2026
Query databases from AI agents using connections configured in DBX.
概覽
讓 AI 程式開發代理使用 DBX 中已設定的連線來查詢資料庫。
- 可以做什麼
- DBX MCP 伺服器會把 DBX 中設定的資料庫連線提供給相容於 MCP 的代理。它支援列出連線、瀏覽資料表、執行 SQL,以及直接在 DBX 介面中開啟資料表。存取受連線允許清單與三種權限模式控制:唯讀、資料讀寫與完整存取。
- 適用情境
- 適合已在 DBX 中管理資料庫連線,並希望 AI 程式開發代理不必重新輸入憑證就能檢視結構或執行 SQL 的情境。適用於重複使用現有 DBX 連線的編輯器與終端機工作流程。
- 執行需求
- 以本機程序執行,通常透過 npx @dbx-app/mcp-server 啟動;macOS、Linux 與 Windows 的預先編譯原生二進位檔不需 Node.js。連線來自 DBX,因此必須安裝並設定 DBX。用於 DBX Web 或 Docker 部署時,需設定 DBX_WEB_URL;若登入頁面需要密碼,還需設定 DBX_WEB_PASSWORD。Windows 可攜版需要 DBX_DATA_DIR。
安裝
README
100+ databases in 25 MB. Desktop, Docker, CLI, built-in AI assistant, and MCP Server.
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Why DBX?
Features
100+ Databases, One Tool
MySQL, PostgreSQL, SQLite, Cloudflare D1, Redis, MongoDB, DuckDB, ClickHouse, SQL Server, Oracle, Elasticsearch, Easysearch, Meilisearch, CouchDB, 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.
Query Editor
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.
AI SQL Assistant
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.
Data Grid
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 Tools
- 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
Data Operations
- 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
.sqlfiles directly - File preview — drag & drop Parquet, CSV, JSON to preview instantly (powered by DuckDB)
- Connection import — bring connection profiles from DBeaver or Navicat
Specialized Browsers
- 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
Plugin System
- 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-cliscaffolding; publish to the Marketplace viat8y2/dbx-store
Safety & Connectivity
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
Polished UI
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:
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:
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:
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.
Install
Download the latest release from the Releases page.
Homebrew (macOS):
Scoop (Windows):
WinGet (Windows):
Flatpak (Linux):
Updates then arrive through the regular flatpak update. See the DBX page on FlatPark for details.
Self-Hosted (Docker)
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.
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:
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.
Windows portable builds are the exception to the desktop platform-key rule.
To remain portable across computers, they keep the local storage key at
data/.dbx/secret.key; move and back up the complete data directory. If an
older portable profile already contains ciphertext protected by Windows
Credential Manager, launch the new build once on the original computer so DBX
can verify and copy that key to the USB drive. If the original computer or key
is gone, the ciphertext cannot be recovered automatically; restore the original
key or a pre-migration backup. Keeping the key beside the database means anyone
who obtains or copies the whole drive can also decrypt its credentials.
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. For installed builds, or when copying only dbx.db, platform
keys do not move with the database; use encrypted export/import instead. A
Windows portable build must move the complete data directory containing both
dbx.db and .dbx/secret.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:
When building the frontend yourself with an absolute asset base, set
VITE_DBX_BASE_PATH=/dbx/ before pnpm build.
Getting Started
Prerequisites
System Dependencies
macOS:
No additional dependencies required.
Linux (Ubuntu/Debian):
NIXOS/NIX :
Windows:
No additional dependencies required.
Development
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:
The
--no-default-featuresflag only affects local development. Release builds (pnpm tauri build) always include DuckDB.
Web version:
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/:
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.
Build
The installer will be in src-tauri/target/release/bundle/.
pnpm build explicitly removes the previous root dist/ directory before running Vite, so desktop packaging starts with fresh frontend output.
Tech Stack
Documentation
- Official docs — feature guides and tutorials
- Plugin development — create plugins and submit Marketplace listings to the correct repository
- Database Test Lab — local database recipes for development and verification
- Contributing — how to pick up issues and open PRs
- Web API reference — HTTP API for Docker/Web deployments
- Examples — CLI, MCP, Docker, and API samples
Support DBX
DBX is free and open source, but ongoing maintenance, database compatibility testing, infrastructure, and release work require sustained time and resources.
- Support DBX — voluntary donations via WeChat or Alipay
- Sponsors & Partners — sponsorship, infrastructure, tools, and community collaboration
Contributors
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0版本歷史
1- v0.1.3最新Sep 16, 2026
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