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Dory MCP Server

Organization
dorylab

AI-native SQL client for humans and agents. Query, explore, visualize, and open agent database work as editable SQL workspaces.

Publisherdorylab
Repositorydory
LanguageTypeScript
Forks
20
Stars
286
Available tools
0
Transport typestdio
Categories
LicenseApache-2.0
Links
  • Connect tools to AI workflows

    Dory MCP Server 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

    286 stars and 20 forks from the linked repository.

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.

Dory AI-native SQL workspace

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

CapabilityPlain DB MCP ServerDory
Run SQL from agents✅✅
Explore schema✅✅
Editable SQL tabs❌✅
Persistent result sets❌✅
Charts and filters❌✅
Human review workflowLimited✅
Saved queries and workspace contextLimited✅
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

Dory Schema Explorer


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.

DatabaseStatus
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 GRANT or CREATE USER statement
  • Cluster-level privilege operations with On Cluster support

Dory ClickHouse monitoring

🚀 Quick Start

Install on macOS with Homebrew

bash
brew install dorylab/dory/dory

Run with Docker

Make sure Docker is installed, then run:

bash
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 DORY_INIT_USER_EMAIL=admin@getdory.dev \
  -e DORY_INIT_USER_PASSWORD=admin \
  dorylab/dory:latest

Then:

Username: admin@getdory.dev

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.

bash
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.

bash
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:

bash
codex mcp add dory -- npx -y @getdory/cli mcp serve --stdio --data standalone
codex mcp list
bash
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:

bash
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:

bash
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:

bash
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:

bash
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:

ProviderEnv DORY_AI_PROVIDERDescription
OpenAIopenaiDefault provider. Uses official OpenAI API.
OpenAI-Compatibleopenai-compatibleAny service exposing an OpenAI-compatible API.
AnthropicanthropicClaude models via Anthropic official API.
GooglegoogleGemini models via Google Generative AI API.
Qwen (Alibaba)qwenQwen models via DashScope OpenAI-compatible endpoint.
xAIxaiGrok models via xAI API.

🗺️ Roadmap

See the latest roadmap here:

⚙️ 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

Use Dory MCP Server MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once Dory MCP Server is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to 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 Dory MCP Server 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 Dory MCP Server 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": {
    "dory": {
      "command": "npx",
      "args": [
        "-y",
        "<mcp-server-package>"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the Dory MCP Server 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 Dory MCP Server 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 Dory MCP Server to help me with this task?
Dory MCP Server
Sure. I read it.
Here is what I found using Dory MCP Server.

Frequently asked questions

What is the Dory MCP Server MCP server used for?

Dory MCP Server 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 Dory MCP Server MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use Dory MCP Server 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 Dory MCP Server 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 Dory MCP Server connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect Dory MCP Server MCP to TypingMind?

Dory MCP Server runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does Dory MCP Server MCP provide in TypingMind?

Dory MCP Server 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 Dory MCP Server MCP?

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

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