How do I install Dreamlit?

Dreamlit is a remote plugin. You do not need to install anything locally. Add the server URL to your AI app's MCP configuration and you are ready to go.

What AI apps work with Dreamlit?

Dreamlit uses the Model Context Protocol (MCP) and works with any MCP-compatible AI app, including Claude, ChatGPT / Codex, Gemini, Copilot, Cursor, and more.

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Dreamlit MCP Server

by Dreamlit Ai

Developer ToolsLow Risk10.0MCP RegistryRemote

Free

Server data from the Official MCP Registry

Create, test, publish, and manage Dreamlit notification workflows from AI clients.

About

Create, test, publish, and manage Dreamlit notification workflows from AI clients.

Remote endpoints: streamable-http: https://mcp.dreamlit.ai/mcp

Security Report

10.0

Low Risk10.0Low Risk

Valid MCP server (1 strong, 1 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry.

9 tools verified · Open access · No issues found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Required

This plugin requests these system permissions. Most are normal for its category.

HTTP Network Access

Connects to external APIs or services over the internet.

How to Connect

Remote Plugin

No local installation needed. Your AI client connects to the remote endpoint directly.

Add this to your MCP configuration to connect:

{
  "mcpServers": {
    "ai-dreamlit-mcp": {
      "url": "https://mcp.dreamlit.ai/mcp"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

Dreamlit MCP

Dreamlit MCP lets AI clients create, inspect, test, publish, and unpublish Dreamlit notification workflows.

Dreamlit is a database-driven notification workflow platform for Supabase and Postgres apps. Use this MCP server when you want an AI client to help build notification workflows from outcome-oriented prompts, then review and publish them through Dreamlit.

Server

Production MCP URL: https://mcp.dreamlit.ai/mcp
Transport: Streamable HTTP
Authentication: OAuth, with personal access token fallback for clients that do not support OAuth

This repository contains public setup docs and MCP registry metadata for Dreamlit's hosted remote MCP server. The production backend implementation is not open source.

Quick Start

Use your MCP client's remote server flow and enter:

https://mcp.dreamlit.ai/mcp

The client should open a Dreamlit authorization page. Choose the workspace you want the AI client to access and approve the requested scopes.

Codex CLI

codex mcp add dreamlit --url https://mcp.dreamlit.ai/mcp
codex mcp login dreamlit

MCP Inspector

npx @modelcontextprotocol/inspector

Then choose Streamable HTTP and use:

https://mcp.dreamlit.ai/mcp

Tools

Dreamlit exposes workflow-level tools, not low-level graph editing APIs.

Tool	Scope	Purpose
`get_status`	`workflows:read`	Get Dreamlit guidance, workspace context, project setup, schema hints, workflow state, and app URLs.
`list_projects`	`workflows:read`	Find accessible Dreamlit projects in the approved workspace.
`list_workflows`	`workflows:read`	Find workflows in a project by name, description, trigger type, and pagination.
`get_workflow_and_preview_url`	`workflows:read`	Inspect a workflow draft and get the Dreamlit preview or builder URL before editing or publishing.
`create_or_update_workflow`	`workflows:write`	Create a new workflow draft or update an existing draft from a natural-language prompt.
`send_workflow_test`	`workflows:write`	Confirm and send a draft email or Slack test without publishing the workflow.
`prepare_publish`	`workflows:publish`	Validate a workflow before publishing and return confirmation fields.
`confirm_publish`	`workflows:publish`	Publish or schedule a workflow after explicit user confirmation.
`unpublish_workflow`	`workflows:publish`	Disable live triggers or schedules for a workflow.

Recommended Flow

Call get_status first to understand the workspace, project setup, and prompting guidance.
Use list_projects and list_workflows if the user names a project or workflow without IDs.
Use get_workflow_and_preview_url before editing an existing workflow.
Use create_or_update_workflow to create or update a draft.
Open the returned preview or builder URL and send workflow tests for important email or Slack messages.
Publish only after explicit user confirmation, using prepare_publish followed by confirm_publish.

Drafts are not live after authoring. Publishing is always a separate explicit step.

Prompting Tips

Ask for the outcome, not a workflow graph. Good prompts include:

The event or schedule that should start the workflow.
The audience or recipient.
The message goal and tone.
The data needed for personalization.
Timing, timezone, and business rules.
Whether recipients should be able to unsubscribe.

Examples:

When a new organization row is inserted, send an internal Slack alert with the organization name, owner email, and plan.

Every Monday at 9 AM America/New_York, send admins a weekly usage digest summarizing active users, failed payments, and new signups.

Tomorrow at 10 AM, announce the launch to active users who opted into product updates. Include unsubscribe.

Access Model

OAuth access is scoped to the workspace selected during authorization. Personal access tokens are project scoped and can be created from Dreamlit project settings.

Available scopes:

workflows:read
workflows:write
workflows:publish

Use the least privilege that fits the client. Read-only clients should request only workflows:read.

Data Handling

Dreamlit MCP can access workflow metadata and connected project context needed to perform the requested workflow actions. It does not require clients to send database credentials through MCP.

Do not paste secrets, raw credentials, or private tokens into prompts. Use Dreamlit's app settings for integrations and credentials.

Support

For support, contact support@dreamlit.ai.

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