MCP server for AI agents

Dreamlit’s Model Context Protocol (MCP) server lets AI agents inspect your Dreamlit workspace, create or update workflows, and publish workflows. You can ask your AI agent things like:

List my published workflows in Dreamlit.
Give me the last 5 workflow runs for the welcome email workflow and summarize the results.
Create a recurring email that sends me a weekly usage digest every Monday at 9 AM America/New_York. Include new signups, active users, and failed payments from the previous week.
Send me a test of the welcome email draft so I can review it in my inbox before publishing.
Publish the “trial ending” reminder workflow. Check for any warnings or errors before publishing.

The key advantage is the closed loop: your agent can use context from your app, codebase, and data model to understand what you want, work back and forth with Dreamlit to fix issues, and only return a preview URL once the workflow matches your intent and is ready to review.

Server URL

https://mcp.dreamlit.ai/mcp

Dreamlit hosts the MCP server. You do not need to install or run a local Dreamlit package.

Remote MCP server

Add the URL above to any client that supports remote MCP over Streamable HTTP.

Free to use

Connecting to Dreamlit MCP and calling its tools doesn’t add charges to your Dreamlit bill.

Quick start

Add Dreamlit MCP to your AI client, authorize Dreamlit, then ask the agent to create or update workflows in plain English. To get started, select your AI client from the list below and follow the dedicated quick start guide.

Agents

Claude Code

Claude Desktop

Codex

Cursor

OpenClaw

Hermes

Gemini CLI

VS Code

Windsurf

Zed

App platforms

Lovable

Bolt

Replit

v0

Using an API key instead of OAuth?

Use a Dreamlit personal access token when cannot complete OAuth or when you want one project-scoped credential.

Create a token

Open Dreamlit, go to Project Settings -> Project Details -> MCP Access, then click Create token.

Choose scopes

Select the smallest set of permissions needs.

Copy the token now

Dreamlit only shows the token once. Store it securely.

Pass the token as a Bearer token

Configure to send:

Authorization: Bearer dlpt_your_token_here

JSON config
VS Code
Codex
Connector UI

{
  "mcpServers": {
    "dreamlit": {
      "url": "https://mcp.dreamlit.ai/mcp",
      "headers": {
        "Authorization": "Bearer dlpt_your_token_here"
      }
    }
  }
}

{
  "servers": {
    "dreamlit": {
      "type": "http",
      "url": "https://mcp.dreamlit.ai/mcp",
      "headers": {
        "Authorization": "Bearer dlpt_your_token_here"
      }
    }
  }
}

Store the token in an environment variable:

export DREAMLIT_MCP_TOKEN="dlpt_your_token_here"

Add the server:

codex mcp add dreamlit --url https://mcp.dreamlit.ai/mcp \
  --bearer-token-env-var DREAMLIT_MCP_TOKEN

If asks for an authentication method, choose API key, Bearer token, or custom header. Use Authorization as the header name and Bearer dlpt_your_token_here as the value.

AI clients can be tricked by untrusted prompts. Review Dreamlit MCP tool calls before approving workflow edits, publishing, or unpublishing.

What is MCP?

MCP is an open standard that lets connect to external tools and data sources through one shared protocol. Instead of needing a custom Dreamlit integration, connects to Dreamlit’s MCP server and discovers the tools Dreamlit exposes. For Dreamlit, MCP means can work with notification workflows using product-level actions:

Find the right workspace, project, or workflow
Understand Dreamlit concepts and project setup state
Create or update workflow drafts from plain-English prompts
Return preview links so you can inspect the result in Dreamlit
Prepare publishing and ask for explicit confirmation before anything goes live

Learn more in the official Model Context Protocol documentation.

What can Dreamlit MCP do?

Dreamlit MCP is focused on workflow authoring and safe workflow operations. It is not a low-level database API.

Capability	What it means
Inspect setup	Check the approved workspace, project setup, Dreamlit page links, table and column summaries, and prompting guidance.
List projects and workflows	Find the project or workflow should work on.
List brand styles	Find saved Brand Style ids and style summaries with pagination before asking Dreamlit to use a specific style.
Inspect workflows	Return normalized workflow structure and a Dreamlit preview URL before editing.
Create drafts	Ask Dreamlit to create a workflow draft from an outcome-oriented prompt.
Update drafts	Continue editing an existing workflow through the same draft history you see in the web app.
Test draft messages	Send a draft email or Slack message to yourself or a chosen recipient for review before publishing.
Query analytics	Read notification analytics, recipient engagement, and workflow run rows with filters and pagination.
Prepare publish	Validate a workflow and return a publish confirmation payload with a preview URL.
Confirm publish	Publish only after the user explicitly approves the prepared publish request.
Unpublish	Disable a live workflow when has publish permission.
Hand off to the browser	Send you to Dreamlit when setup, unsupported edits, or manual review need the web app.

Prerequisites

Before connecting :

Create a Dreamlit account at app.dreamlit.ai.
Finish workspace and project setup in Dreamlit.
Connect a Supabase or Postgres database.
Configure any channels the workflows will need, such as email domains, Brand Styles, or Slack.
Confirm supports remote MCP over Streamable HTTP, or can send MCP requests through an HTTP bridge.

Dreamlit MCP works against existing Dreamlit workspaces and projects. If says setup is required, open the Dreamlit link it returns and finish setup in the web app before reconnecting.

How does authorization work?

OAuth is the best option when supports remote server authentication. connects to Dreamlit, Dreamlit opens a browser authorization screen, and you approve access to one Dreamlit workspace.

Add Dreamlit MCP

Use the server URL:

https://mcp.dreamlit.ai/mcp

Approve Dreamlit access

should open a Dreamlit authorization page. Sign in, choose the workspace, review the requested scopes, and click Allow access.

Check status

Ask :

Check Dreamlit MCP status and list my projects.

If only receives read access, reconnect Dreamlit and approve workflow drafting, publishing, or analytics when prompted. Dreamlit defaults empty OAuth scope requests to the supported v1 scopes.

Permissions

Dreamlit MCP uses workflow and analytics scopes.

Scope	Allows	Typical use
`workflows:read`	`get_status`, `list_projects`, `list_workflows`, `list_brand_styles`, `get_workflow_and_preview_url`	Inspect setup, find workflows, Brand Styles, drafts, and published state.
`workflows:write`	`create_or_update_workflow`, `send_workflow_test`	Create or edit workflow drafts, and send draft message tests.
`workflows:publish`	`prepare_publish`, `confirm_publish`, `unpublish_workflow`	Validate, publish, schedule broadcasts, or unpublish workflows.
`analytics:read`	`get_analytics`	Query notification analytics, recipient engagement, and workflow runs.

OAuth grants are scoped to a workspace. Personal access tokens are scoped to one project.

Tools

discovers these tools from the server.

Tool	Required scope	Use it for
`get_status`	`workflows:read`	Learn how Dreamlit MCP works, inspect workspace/project setup, get Dreamlit page links, and retrieve prompting guidance.
`list_projects`	`workflows:read`	Find projects in the approved workspace. Project-scoped tokens only return their own project.
`list_workflows`	`workflows:read`	Find workflows in a project, optionally filtered by trigger type.
`list_brand_styles`	`workflows:read`	Find saved Brand Style ids and style summaries with pagination before asking Dreamlit to use a specific style.
`get_workflow_and_preview_url`	`workflows:read`	Inspect draft and published workflow structure before editing or publishing.
`get_analytics`	`analytics:read`	Query bounded analytics data with filters, sorting, and pagination.
`create_or_update_workflow`	`workflows:write`	Create or update a draft from a natural-language prompt.
`send_workflow_test`	`workflows:write`	Send the current draft email or Slack message to yourself or a chosen recipient for review. Doesn’t publish or edit the workflow.
`prepare_publish`	`workflows:publish`	Validate the workflow and return the exact payload needed for confirmation.
`confirm_publish`	`workflows:publish`	Publish only after the user approves the prepared publish request.
`unpublish_workflow`	`workflows:publish`	Disable a live workflow.

Dreamlit also exposes the dreamlit://mcp/guide resource. If supports MCP resources, it can read the guide for prompting guidance, trigger types, unsubscribe guidance, and the recommended Dreamlit MCP flow.

Recommended workflow

Ask to work in this order:

Check status

Start with get_status. This gives Dreamlit concepts, setup state, project context, and links back to relevant Dreamlit pages.

Find the target

Use list_projects and list_workflows if the project or workflow is unclear.

Choose a Brand Style

Use list_brand_styles when you want a specific saved Brand Style applied.

Inspect before editing

Use get_workflow_and_preview_url before changing an existing workflow.

Create or update the draft

Use create_or_update_workflow with an outcome-oriented prompt.

Review in Dreamlit

Open the returned workflow URL to inspect the draft, preview output, and make manual adjustments if needed.

Test important messages

For email or Slack messages that need to look right before going live, ask to send a test through send_workflow_test. Confirm the test before it sends, then review the real message in your inbox or Slack channel.

Publish deliberately

Use prepare_publish first. Only call confirm_publish after you explicitly approve the prepared publish request.

How do I test a draft email or Slack message before publishing?

Use send_workflow_test to send the current draft message to yourself (or a chosen recipient) so you can review it in the real channel before going live. Tests don’t publish, schedule, or change the workflow draft.

Email tests default to the authenticated user’s email address. Pass testRecipientEmail to send to a different inbox.
Slack tests post to the channel configured for the draft message.
Dreamlit returns a confirmation_required response describing the message and recipient. only sends after calling send_workflow_test again with confirmSend: true.
If a workflow has more than one testable message, Dreamlit returns a clarification_required response listing each message by label so you can choose one.
Test sends count toward the same draft rate limit as workflow authoring.

Example prompt:

Send me a test of the welcome email draft so I can review it
in my inbox before publishing.

Prompting Dreamlit through MCP

Dreamlit works best when you describe the notification outcome, not the internal workflow graph. Good prompts include:

The event or schedule that should start the workflow
The audience or recipient
The message goal
Data needed for targeting or personalization
Timing, timezone, and business rules
Whether unsubscribe should be enabled
Tone or brand notes when they matter

Examples:

Check Dreamlit status, then create a workflow for the main project:
when a new order row is inserted, send the customer an order confirmation
with the order number, total, and delivery estimate.

List my workflows, inspect the welcome email workflow, and update it so
users who have not created a project after 3 days get a follow-up email.
Keep unsubscribe off because this is account onboarding.

Create a repeating workflow that sends admins a weekly usage digest every
Monday at 9 AM America/New_York. Include new signups, active users, and
failed payments from the previous week.

Prepare publish for the trial reminder workflow. Show me the preview URL
and warnings before confirming anything.

Safety and control

Dreamlit MCP is designed so can help with workflows without making surprise production changes.

Draft changes stay draft-only until you publish.
Test sends require explicit confirmation and don’t publish, schedule, or edit the draft.
Publishing is always a separate confirmation step with a Dreamlit preview link.
If an action needs setup or manual review, Dreamlit sends you back to the web app.
Query steps are read-only against your application data.
Access is limited by the permissions you approve. Personal access tokens are project-scoped and can be revoked anytime.

Troubleshooting

Dreamlit authorization is required

Reconnect the MCP server and complete the browser authorization flow. If you are using a personal access token, confirm the token is still active and that is sending it as an Authorization: Bearer ... header.

Dreamlit tools do not appear after authorization

Start a new chat or session in . If the tools still do not appear, restart or restart the Dreamlit MCP server entry. can cache the MCP server and tool list for an open session.

Additional Dreamlit permission is required

The current OAuth grant or personal access token does not include the required scope. Reconnect with the requested access, or create a token with the missing scope.

Dreamlit says to choose a project

Your approved workspace has multiple projects and did not specify one. Ask to call list_projects, then retry with the right project.

Dreamlit says setup is required

Open the returned Dreamlit setup URL, finish workspace and project setup, then reconnect .

A workflow edit returns a browser handoff

Some changes still need the Dreamlit web app. Open the returned URL, review the draft, and continue from there.

Publishing fails after a preview

The workflow may have changed since the publish preview. Ask to run prepare_publish again, review the new preview and warnings, then confirm only if it still looks right.

Tools are visible but calls time out

Workflow authoring can take longer than read-only calls because Dreamlit is planning and applying a real workflow draft. Retry once. If it keeps failing, open the returned Dreamlit URL if one is present, or contact support.

Testing with MCP Inspector

You can use the MCP Inspector to verify the server connection.

Start the Inspector

npx @modelcontextprotocol/inspector

Choose Streamable HTTP

Select Streamable HTTP as the transport.

Enter the server URL

https://mcp.dreamlit.ai/mcp

Authenticate

Use OAuth if the Inspector supports it, or add a Bearer header:

Authorization: Bearer dlpt_your_token_here

Confirm the connection

Use List tools and call get_status to confirm the connection.

Next steps

Quickstart

Connect your database and create your first workflow.

Workflow basics

Learn how Dreamlit workflows are structured.

Get support

Reach the team if MCP setup blocks you.

Last validated: 2026-05-07

​Server URL

Remote MCP server

Free to use

​Quick start

​Agents

Claude Code

Claude Desktop

Codex

Cursor

OpenClaw

Hermes

Gemini CLI

VS Code

Windsurf

Zed

​App platforms

Lovable

Bolt

Replit

v0

​What is MCP?

​What can Dreamlit MCP do?

​Prerequisites

​How does authorization work?

​Permissions

​Tools

​Recommended workflow

​How do I test a draft email or Slack message before publishing?

​Prompting Dreamlit through MCP

​Safety and control

​Troubleshooting

​Dreamlit authorization is required

​Dreamlit tools do not appear after authorization

​Additional Dreamlit permission is required

​Dreamlit says to choose a project

​Dreamlit says setup is required

​A workflow edit returns a browser handoff

​Publishing fails after a preview

​Tools are visible but calls time out

​Testing with MCP Inspector

​Next steps

Quickstart

Workflow basics

Get support

Server URL

Quick start

Agents

App platforms

What is MCP?

What can Dreamlit MCP do?

Prerequisites

How does authorization work?

Permissions

Tools

Recommended workflow

How do I test a draft email or Slack message before publishing?

Prompting Dreamlit through MCP

Safety and control

Troubleshooting

Dreamlit authorization is required

Dreamlit tools do not appear after authorization

Additional Dreamlit permission is required

Dreamlit says to choose a project

Dreamlit says setup is required

A workflow edit returns a browser handoff

Publishing fails after a preview

Tools are visible but calls time out

Testing with MCP Inspector

Next steps