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dbx

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t8y2

25 MB lightweight cross-platform database client for 90+ databases, including MySQL, PostgreSQL, SQLite, Redis, MongoDB, DuckDB, SQL Server, and Dameng. Built-in AI, MCP Server, CLI, desktop and Docker. | 轻量级跨平台数据库管理工具,支持 MySQL、PostgreSQL、SQLite、Redis、MongoDB、达梦等 90+ 数据库,提供桌面端、Docker、CLI、内置 AI 助手和 MCP Server。

Publishert8y2
Repositorydbx
LanguageRust
Forks
2K
Stars
20.4K
Available tools
0
Transport typestdio, streamable-http
Categories
LicenseApache-2.0
Links
  • Connect tools to AI workflows

    dbx exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    20.4K stars and 2K forks from the linked repository.

❤️ Sponsors

🤝 Partners

Why DBX?

Features

90+ Databases, One Tool

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. Message queue admin is also available for Pulsar, Kafka, and RocketMQ. 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 .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

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

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.

bash
npx @dbx-app/mcp-server

Add to your .mcp.json:

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:

json
{
  "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:

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

See the MCP server README and CLI README for details.

Install

Download the latest release from the Releases page.

Homebrew (macOS):

bash
brew install --cask dbx

Scoop (Windows):

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

WinGet (Windows):

winget install t8y2.dbx

Flatpak (Linux):

bash
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.

Self-Hosted (Docker)

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

bash
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:

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

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:

yaml
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.

Getting Started

Prerequisites

System Dependencies

macOS:

No additional dependencies required.

Linux (Ubuntu/Debian):

bash
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.

Development

bash
make

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:

bash
# 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:

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

Documentation site:

bash
make docs

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/:

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

JDBC agent driver development projects live in agents/:

bash
cd agents
./gradlew test

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

Build

bash
make package

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

Tech Stack

LayerTechnology
FrameworkTauri 2
FrontendVue 3 + TypeScript
UIshadcn-vue + Tailwind CSS
EditorCodeMirror 6
BackendRust + sqlx / tiberius / redis-rs / mongodb

Documentation

Support DBX

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

Contributors

Community

LINUX DO 1Panel

Star History

License

Apache-2.0

Installation

TypingMind
{
  "mcpServers": {
    "dbx": {
      "command": "node",
      "args": [
        "path/to/your/main.js"
      ]
    }
  }
}

Use dbx MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once dbx is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. You can run MCP locally on your device or connect to a remote MCP server URL.

Option 1: Use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add dbx as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the dbx MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "dbx": {
      "command": "npx",
      "args": [
        "-y",
        "dbx"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the dbx MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the dbx MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use dbx to help me with this task?
dbx
Sure. I read it.
Here is what I found using dbx.

Option 2: Add an MCP server URL

Use this when dbx is already hosted remotely or your team wants one shared connector that multiple users can access.

1

Open MCP connectors

In TypingMind, go to Plugins, open MCP connectors, then choose Add URL.

  1. Open TypingMind in your browser.
  2. Go to Plugins.
  3. Open MCP connectors.
  4. Click Add URL.
TypingMind Add Custom MCP Server URL form
2

Paste the server URL

Enter the MCP server URL from the provider in the Server URL field. Add a connection name, description, icon, custom HTTP headers, or OAuth client settings if the server requires them.

  1. Paste the MCP server URL from the provider into the Server URL field.
  2. Enter a connection name for dbx.
  3. Add a description and icon if you want it to be easier to identify.
  4. Add custom HTTP headers or OAuth client details if the server requires authentication.
3

Create the connection

Click Create connection, then return to the Plugins list and confirm the new MCP connection is active.

  1. Click Create connection.
  2. Return to the MCP connectors list.
  3. Confirm the dbx connection appears as active.
  4. Refresh the plugin list if the connection does not appear immediately.
4

Switch models without reconnecting

Start a chat with your preferred model, enable the dbx tools from Plugins, and switch to another model whenever needed. The MCP connection stays available to the TypingMind workspace.

  1. Start a new chat in TypingMind.
  2. Select the AI model you want to use.
  3. Enable the dbx tools from Plugins.
  4. Ask the model to use the tool when needed.
  5. Switch to another AI model and reuse the same MCP connection.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use dbx to help me with this task?
dbx
Sure. I read it.
Here is what I found using dbx.

Frequently asked questions

What is the dbx MCP server used for?

dbx is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use dbx MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use dbx with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use dbx MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With dbx connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect dbx MCP to TypingMind?

dbx can be connected in TypingMind with the local MCP connector or by adding a remote MCP server URL. Use the local connector when the server needs access to files, apps, or private resources on your device, and use a server URL when the MCP server is hosted remotely.

What tools does dbx MCP provide in TypingMind?

dbx exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use dbx MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If dbx requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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