Docker 启动需自行设置 DS_SECRET_KEY、BETTER_AUTH_SECRET 等环境变量,默认初始账号为 [email protected] / admin;Agent Skill 不会自动安装 CLI 或配置 MCP,需另按文档接入;HTTP MCP 默认监听 127.0.0.1:3318,需先创建 token 才能连接
dory
dorylabApache-2.0活跃维护面向人类和智能体的 AI 原生 SQL 客户端,支持查询、探索、可视化,并能把智能体的数据库操作转成可编辑的 SQL 工作区。
AI-native SQL client for humans and agents. Query, explore, visualize, and open agent database work as editable SQL workspaces.
brew install dorylab/dory/doryREADME 未说明;提供 macOS(Homebrew 或安装包)、Windows 安装包以及 Docker 部署方式
面向人和 AI Agent 的 AI 原生 SQL 客户端,把 Agent 的数据库操作变成可编辑的 SQL 工作区
面向人类和智能体的 AI 原生 SQL 客户端,支持查询、探索、可视化,并能把智能体的数据库操作转成可编辑的 SQL 工作区。
核心能力
- Agent 通过 MCP 执行只读 SQL 并创建可编辑的 SQL 标签页
- 结果集、筛选、图表与生成它们的 SQL 保持绑定
- 交互式 Schema 图展示主外键关系并可导出 PNG/SVG
- 基于真实库表结构的 AI 助手生成、修复和解释 SQL
- CLI 支持 stdio 与 HTTP 两种 MCP 服务模式
容易踩的坑
- v0.37.4-beta.1pre-release2026-10-19 · 2026-10-19 03:44 UTC
查看更新说明
What's Changed
- OSSIE Schema Support: Updated the Olist evaluation logic and associated tests to align with the OSSIE semantic schema, improving accuracy and consistency for semantic model evaluations in demo and script contexts.
- v0.37.4-beta.0pre-release2026-10-19 · 2026-10-19 03:01 UTC
查看更新说明
What's Changed
Semantic Context & Knowledge Management
- Added support for semantic context in artifacts and agent queries, enabling richer AI reasoning over business definitions.
- Introduced GitHub knowledge connector for syncing documentation, issues, and PRs into the knowledge base.
- Added knowledge relations to model connections between definitions, sources, and verified queries.
- Increased knowledge source upload limit and localized UI elements across English, Spanish, Japanese, and Chinese.
- Enhanced knowledge definition detail views with query and source references, metadata, and editing capabilities.
Agent Run Experience
- Redesigned agent run details page to prominently display findings, evidence, and verification status.
- Improved responsive layout and readability of agent run reports, including dedicated evidence and finding components.
- Added lifecycle tracking for chat-initiated agent runs, improving traceability and debugging.
- Refined legacy data handling and clarified presentation of findings, handoff prompts, and verification instructions.
SQL Console & Query Workflow
- Added business knowledge options when saving SQL queries, allowing users to associate saved queries with semantic definitions.
- Automatically generate AI metadata (e.g., purpose, domain tags) upon query save.
- Improved verified query table behavior and reference editors for better maintainability and consistency.
UI & Navigation Improvements
- Hid navigation items that are irrelevant to the current connection context (e.g., semantic or knowledge tabs for unsupported connections).
- Streamlined app sidebar behavior and refined connection card interactions.
- Allowed configurable width for upload source selectors in knowledge source panels.
Infrastructure & Auth
- Upgraded Electron keychain signing configuration for improved macOS build reliability.
- Configured optional Better Auth Sentinel and social login providers (e.g., GitHub, Google) for flexible authentication setups.
Internal
- Refactored application structure across web and CLI packages to improve maintainability and testability.
- Added comprehensive commerce and Olist evaluation test suites, including MCP replay, seeding, and reporting scripts.
- Introduced new database migrations for semantic knowledge sources, knowledge traceability, and agent activities.
- v0.37.3最新正式版2026-09-08 · 2026-09-08 08:08 UTC
What's Changed
Improvements
- Upgraded Next.js across the web and admin apps, enabling configurable instant navigation for faster page transitions.
- Refactored AI-related application workflows—including chatbot message rendering, streaming endpoints, and agent logic—to improve consistency and maintainability of AI interactions.
Fixes
- Disabled standalone output in Next.js configuration to ensure compatibility with Vercel deployments.
- Updated
electron-builderkeychain signing configuration to resolve signing issues during Electron app builds.
Dependencies
- Bumped
fflatefrom0.4.8to0.4.9for improved compression reliability. - Upgraded
nanoidfrom5.1.16to6.0.0, adopting breaking changes aligned with modern ID generation practices.
- v0.37.22026-09-04 · 2026-09-04 08:28 UTC
查看更新说明
What's Changed
Improvements
- Artifact navigation and context: Organized artifacts under a collapsible "More" sidebar menu for cleaner UI. Preserved agent run context when viewing individual artifacts, improving workflow continuity.
- Artifact titles and evidence handling: Improved artifact title generation and now require explicit finding evidence—enhancing clarity and reliability of artifact metadata.
Fixes
- Agent Workspace execution results: Consolidated and standardized how SQL execution results are hydrated and displayed in the Agent Workspace, reducing inconsistencies and improving result fidelity.
Internal
- Dependency updates: Updated several dependencies including
browserslist,nanoid,@faker-js/faker,@humanfs/node,qs,@xmldom/xmldom, andfast-urito their latest patch/minor versions for security, stability, and compatibility.
- v0.37.12026-09-02 · 2026-09-02 16:17 UTC
查看更新说明
What's Changed
Features
- Artifact integration in Agent Runs: Artifacts and persisted findings are now displayed directly on agent run detail and list pages, improving traceability between agent executions and their generated outputs.
Improvements
- Artifact metadata and usage display: Refreshed artifact list UI with updated metadata, retention indicators, and usage context—localized for English, Spanish, Japanese, and Chinese.
- ClickHouse command support: Command statements (e.g.,
CREATE TABLE,DROP DATABASE) now execute correctly without attempting result-set formatting, improving reliability for DDL/DML operations.
Fixes
- Stricter artifact evidence requirement: Agent Run findings now require associated Artifact evidence, enforcing data integrity and preventing orphaned or unverifiable results.
Internal
- Dependency updates: Upgraded core dependencies across the stack:
- Next.js bumped from
16.2.7to16.2.11(inapps/web,apps/admin,packages/i18n, andpackages/web-utils) - Hono upgraded to
4.13.1,@hono/node-serverto1.19.17,pacoteto21.5.1, andpostcss-selector-parserto7.1.5
- Next.js bumped from
- Docker build enhancements: Export and schema-compare packages are now included in Docker images, ensuring full CLI tooling availability in containerized deployments.
用户点评
登录用户的真实使用记录,可按版本和硬件筛选还没有人点评。第一个说出真实体验的人最有价值。
Dory is an AI-native SQL client for humans and agents.
Dory is a SQL workspace where humans can query, explore, and visualize data, and where AI agents can safely work with databases through MCP.
Unlike a plain database MCP server that only sends query results back to a chat, Dory turns agent work into editable SQL workspaces: SQL tabs, result sets, charts, saved queries, and execution context can all be opened, inspected, modified, and continued by humans.
Use Dory as your everyday SQL client, or as the database execution layer for agents like Claude Code, Codex CLI, and other MCP-compatible tools.
No signup required. Click "Try Dory without an account" to start instantly.

Why Dory?
AI agents can now write SQL, inspect schemas, and answer analytical questions. But raw agent output is not enough for real data work.
Teams still need to:
- see the exact SQL that was run
- inspect real result sets
- fix wrong queries
- turn results into charts or exports
- preserve context across multiple steps
- continue the work in a real SQL workspace
Dory is built for this workflow.
How Dory works
Dory provides the same underlying database actions to both the UI and agents:
- Humans use Dory as a SQL client: write SQL, browse schema, run queries, filter results, create charts, and save queries.
- Agents use Dory through MCP: list connections, explore schemas, run read-only SQL, create tabs, and organize database work.
- Agent-generated work becomes a real workspace that humans can review, edit, and continue.
Dory vs a plain database MCP server
| Capability | Plain DB MCP Server | Dory |
|---|---|---|
| Run SQL from agents | ✅ | ✅ |
| Explore schema | ✅ | ✅ |
| Editable SQL tabs | ❌ | ✅ |
| Persistent result sets | ❌ | ✅ |
| Charts and filters | ❌ | ✅ |
| Human review workflow | Limited | ✅ |
| Saved queries and workspace context | Limited | ✅ |
| Works as a daily SQL client | ❌ | ✅ |
✨ Key Features
Editable Agent Workspaces
Agent database work should not disappear into a chat transcript.
- Open agent-created SQL tabs as normal workspace tabs
- Inspect SQL, result sets, filters, charts, and saved context
- Edit generated SQL and rerun it yourself
- Continue an agent run from the same workspace instead of restarting from scratch
Dory CLI and MCP for Agents
@getdory/cli is the agent entrypoint for running Dory without opening the desktop app.
- Works with Claude Code, Codex CLI, and other MCP-compatible clients
- Runs standalone MCP servers over stdio or HTTP
- Acts as a headless runtime for automation and direct Dory Actions
- Can use standalone data, hosted Dory Web, or Desktop local data with
--data desktop
SQL Workspace for Humans
- Multi-tab SQL editor with multiple result sets
- Schema browser for tables, columns, and database objects
- Saved queries for reusable analysis
- Built-in query execution history and workspace context
Schema Explorer
Understand unfamiliar databases at a glance with an interactive map of tables and relationships.
- Visualize primary keys, foreign keys, and relationships across schemas
- Search for tables, select schemas, and switch between all columns and keys only
- Auto-arrange the graph, fit it to the viewport, and open any table directly
- Export the complete schema graph as PNG or SVG

Result Sets, Filters, and Charts
- Inspect real result sets in a table view
- Filter, search, and review returned rows
- Turn query output into charts directly inside the workspace
- Keep results attached to the SQL that produced them
Schema-aware AI Assistance
An AI assistant grounded in real database schema and current query context.
- Generate SQL from natural language
- Rewrite, fix, and explain SQL in the current tab
- Use current database schema and query context
- Keep AI assistance inside the real SQL workspace
Saved Queries and Reusable Context
- Save useful SQL as reusable queries
- Organize query work across connections and workspaces
- Let humans and agents build on previous database work
- Preserve context beyond a single chat response
Database Support
Dory is a multi-database SQL client, with broad driver support and deeper integrations where Dory can provide more than generic SQL execution.
| Database | Status |
|---|---|
| ClickHouse | ✅ Deeply integrated |
| PostgreSQL | ✅ Supported |
| Neon | ✅ Supported |
| Supabase | ✅ Supported |
| Cloudflare D1 | ✅ Supported |
| MySQL | ✅ Supported |
| MariaDB | ✅ Supported |
| SQLite | ✅ Supported |
| DuckDB | ✅ Supported |
| SQL Server | ✅ Supported |
| Oracle | ✅ Supported |
| Snowflake | ✅ Supported |
ClickHouse Deep Integration
Dory includes native ClickHouse operations surfaces for teams that need more than a generic SQL editor.
- Query monitoring with slow queries, errors, active users, latency, and throughput
- Multi-dimensional filtering by user, database, query type, and time range
- User and role management without hand-writing every
GRANTorCREATE USERstatement - Cluster-level privilege operations with On Cluster support

🚀 Quick Start
Install on macOS with Homebrew
brew install dorylab/dory/dory
Run with Docker
Make sure Docker is installed, then run:
docker run -d --name dory \
-p 3000:3000 \
-e DS_SECRET_KEY="$(openssl rand -base64 32 | tr -d '\n')" \
-e BETTER_AUTH_SECRET="$(openssl rand -hex 32)" \
-e BETTER_AUTH_URL="http://localhost:3000" \
-e DORY_AI_PROVIDER=openai \
-e DORY_AI_MODEL=gpt-4o-mini \
-e DORY_AI_API_KEY=your_api_key_here \
-e DORY_AI_URL=https://api.openai.com/v1 \
-e NEXT_PUBLIC_REQUIRE_EMAIL_VERIFICATION=false \
-e [email protected] \
-e DORY_INIT_USER_PASSWORD=admin \
dorylab/dory:latest
Then:
Username: [email protected]
Password: admin
The initial administrator account is controlled by DORY_INIT_USER_EMAIL and DORY_INIT_USER_PASSWORD in .env.
To enable email verification, set RESEND_API_KEY to a valid resend key and EMAIL_FROM to a validated email.
Self-host with Docker Compose
For long-running self-hosted deployments, Docker Compose runs Dory with a dedicated PostgreSQL database and persistent volumes.
cp docker-compose.env.example .env
# Edit .env and replace all placeholder secrets/passwords.
docker compose up -d
For comprehensive self-hosting documentation, environment variables, and deployment guides, see the Self-Hosting Documentation.
🧩 Dory Agent Skill
Install the Dory skill for Codex, ChatGPT, Claude, and other agents that support the open Agent Skills format.
npx skills add https://github.com/dorylab/skills --skill dory
The skill teaches agents when to use Dory, how to use Dory MCP tools, and how to preserve generated SQL, result sets, and findings in an editable Dory Agent Run workspace.
The skill does not install the Dory CLI or configure MCP automatically. For live database access, connect Dory MCP with the setup commands below.
🔗 Dory CLI and MCP
Use @getdory/cli to connect MCP-compatible agents to Dory. It can run a local stdio MCP server, host a long-running HTTP MCP endpoint, bridge to hosted Dory Web, or reuse Dory Desktop local data with --data desktop.
For the full MCP setup guide, including CLI stdio, headless HTTP, and hosted Dory bridge options, see Dory MCP Guide.
Run a local stdio MCP server when your agent client is on the same machine:
codex mcp add dory -- npx -y @getdory/cli mcp serve --stdio --data standalone
codex mcp list
claude mcp add dory -- npx -y @getdory/cli mcp serve --stdio --data standalone
claude mcp list
Run a local HTTP MCP endpoint when you want a long-running service:
npx -y @getdory/cli mcp token create --data standalone --name "local-http"
export DORY_MCP_TOKEN="dory_mcp_..."
npx -y @getdory/cli mcp serve \
--http \
--host 127.0.0.1 \
--port 3318 \
--token "$DORY_MCP_TOKEN" \
--data standalone
Add that HTTP endpoint to Codex CLI:
codex mcp add \
--url http://127.0.0.1:3318/api/mcp \
--bearer-token-env-var DORY_MCP_TOKEN \
dory
Add it to Claude Code:
claude mcp add \
--transport http \
dory \
http://127.0.0.1:3318/api/mcp \
--header "Authorization: Bearer $DORY_MCP_TOKEN"
Bridge hosted Dory Web to local MCP clients:
npx -y @getdory/cli mcp login --url https://your-dory-host
codex mcp add dory-hosted -- npx -y @getdory/cli mcp bridge --url https://your-dory-host
claude mcp add dory-hosted -- npx -y @getdory/cli mcp bridge --url https://your-dory-host
For the standalone @getdory/mcp bridge package, see packages/mcp. For the full CLI and headless runtime guide, see packages/cli.
🧠 Supported AI Providers
Dory is built with a pluggable AI provider architecture. You can freely switch between different model vendors by changing environment variables, with no code changes required.
Currently supported providers:
| Provider | Env DORY_AI_PROVIDER | Description |
|---|---|---|
| OpenAI | openai | Default provider. Uses official OpenAI API. |
| OpenAI-Compatible | openai-compatible | Any service exposing an OpenAI-compatible API. |
| Anthropic | anthropic | Claude models via Anthropic official API. |
google | Gemini models via Google Generative AI API. | |
| Qwen (Alibaba) | qwen | Qwen models via DashScope OpenAI-compatible endpoint. |
| xAI | xai | Grok models via xAI API. |
🗺️ Roadmap
See the latest roadmap here:
- Dory Roadmap
- Historical reference: GitHub Discussion #35
⚙️ Tech Stack
- Next.js + React + Tailwind
- Drizzle ORM
- Multi-model AI SDK integration
- PGLite
- Resend
- Shadcn UI
- Monaco Editor
🎯 Who is it for?
- Data engineers
- Data analysts
- Database platform teams
- Agent builders who need a database execution layer
- ClickHouse operations teams
📄 License
Apache-2.0