Dreamlit MCP

MCP serverCommunication

Set up notifications without building them by hand. Once added, your AI can create, test, publish, and manage Dreamlit notification workflows, so you can get notifications running by describing what you need.

Available today. Use it from your connected AI after setup.

After adding it, ask your AI to create your first notification workflow and run a test. When the test looks right, have it publish the workflow.

Then ask your AI: use Dreamlit MCP to get status

What your AI can do with it

  • Create new notification workflows
  • Test workflows before they go live
  • Publish workflows so notifications start sending
  • Manage and update your existing workflows

From the project's README

As published by dreamlit-ai/dreamlit-mcp in README.md.

Dreamlit MCP lets AI clients create, inspect, test, publish, unpublish, analyze, and style 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, review and publish them through Dreamlit, or answer bounded analytics questions about notification performance.

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

To request every supported v1 scope explicitly:

codex mcp login dreamlit --scopes workflows:read,workflows:write,workflows:publish,analytics:read

MCP Inspector

npx @modelcontextprotocol/inspector

Then choose Streamable HTTP and use:

https://mcp.dreamlit.ai/mcp

Tools

Dreamlit exposes product-level workflow and analytics tools, not low-level graph editing or database APIs.

ToolScopePurpose
get_statusworkflows:readGet Dreamlit guidance, workspace context, project setup, schema hints, workflow state, and app URLs.
list_projectsworkflows:readFind accessible Dreamlit projects in the approved workspace.
list_workflowsworkflows:readFind workflows in a project by name, description, trigger type, and pagination.
list_brand_kitsworkflows:readFind saved brand kit ids and style summaries with pagination before applying one to generated email drafts.
get_workflow_and_preview_urlworkflows:readInspect a workflow draft and get the Dreamlit preview or builder URL before editing or publishing.
get_analyticsanalytics:readQuery bounded notification analytics, recipient engagement, and workflow run data with filters and cursor pagination.
create_or_update_workflowworkflows:writeCreate a new workflow draft or update an existing draft from a natural-language prompt.
send_workflow_testworkflows:writeConfirm and send a draft email or Slack test without publishing the workflow.
prepare_publishworkflows:publishValidate a workflow before publishing and return confirmation fields.
confirm_publishworkflows:publishPublish or schedule a workflow after explicit user confirmation.
unpublish_workflowworkflows:publishDisable live triggers or schedules for a workflow.

Recommended Flow

  1. Call get_status first to understand the workspace, project setup, and prompting guidance.
  2. Use list_projects and list_workflows if the user names a project or workflow without IDs.
  3. Use list_brand_kits when the user wants a specific saved brand kit applied to generated email drafts.
  4. Use get_workflow_and_preview_url before editing an existing workflow.
  5. Use get_analytics for bounded analytics questions, filtering first and paginating with returned cursors for larger result sets.
  6. Use create_or_update_workflow to create or update a draft.
  7. Open the returned preview or builder URL and send workflow tests for important email or Slack messages.
  8. 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
  • analytics:read

Use the least privilege that fits the client. Read-only workflow and brand-kit clients should request only workflows:read; analytics clients should request analytics:read.

Data Handling

Dreamlit MCP can access workflow metadata, saved brand kit summaries, connected project context, and bounded analytics results needed to perform the requested actions. It does not require clients to send database credentials through MCP.

Analytics access is structured and paginated. Use filters and cursors for larger result sets; CSV exports and bulk dumps are not exposed 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.

Tools it offers (11)

What this server listed when ahel dialed its public endpoint in Sep 2026, with no key and no account of yours. The names are the server’s own.

  • get_status
  • create_or_update_workflow
  • list_projects
  • list_workflows
  • list_brand_styles
  • get_workflow_and_preview_url
  • get_analytics
  • send_workflow_test
  • prepare_publish
  • confirm_publish
  • unpublish_workflow

Signals

Last commit
May 2026
Advanced
Delivery
mcp MCP server → your ahel gateway (mcp.ahel.ai) → every connected AI client.
Catalog kind
mcp-server
Gateway key
ai-dreamlit-mcp
Source
github.com/dreamlit-ai/dreamlit-mcp
Hosted endpoint
https://mcp.dreamlit.ai/mcp