Dreamlit MCP for Gemini CLI

Gemini CLI has one of the largest context windows of any agent. Drop in your full schema, a directory of migrations, or a week of logs, and it can absorb all of it before drafting a workflow. Dreamlit’s Model Context Protocol (MCP) server turns that depth of context into notification workflows that account for the whole picture, not just the part you remembered to mention. You can ask Gemini CLI things like:

List my published workflows in Dreamlit.
I’m rolling out a new pricing tier. Plan and build the announcement email, the upgrade-prompt email, and a follow-up reminder, all in my brand voice.
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: Gemini CLI 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.

Why use Dreamlit MCP with Gemini CLI?

Gemini’s signature strength is its context window. Dreamlit MCP turns that into workflows informed by far more than what you typed into the prompt.

Whole-codebase context: drop in a directory of migrations or every model file in your app, and Gemini CLI uses all of it when drafting the workflow.
Multi-file reasoning: connect the trigger column you’re adding to the user fields you’d want for personalization without spelling either out.
Logs and data analysis: paste a week of logs or CSV exports, ask for a workflow shaped around what you see, and have Gemini draft it.
Test and ship: send a test through send_workflow_test and confirm the workflow handles the data shape you expect.

Server URL

https://mcp.dreamlit.ai/mcp

Dreamlit hosts this remote MCP server over Streamable HTTP. Gemini CLI can store it in user or project settings and authenticate with OAuth.

Quick install

Add the MCP server

Add Dreamlit to your user-level Gemini CLI settings:

gemini mcp add --transport http --scope user dreamlit https://mcp.dreamlit.ai/mcp

Authorize Dreamlit

Start Gemini CLI. If it does not automatically prompt for OAuth, run:

/mcp auth dreamlit

Restart Gemini CLI

Exit and reopen Gemini CLI after authorization, then run /mcp to confirm Dreamlit is connected. Open sessions can keep a stale MCP tool list.

Confirm the server

List configured MCP servers:

gemini mcp list

Start prompting

Ask Gemini CLI:

Use Dreamlit MCP to check status and list my Dreamlit workflows.

Using an API key instead of OAuth?

Use a Dreamlit personal access token when Gemini CLI 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 Gemini CLI needs.

Copy the token now

Dreamlit only shows the token once. Store it securely.

Pass the token as a Bearer token

Configure Gemini CLI 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 Gemini CLI 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.

What is MCP?

MCP is an open standard that lets Gemini CLI connect to external tools and data sources through one shared protocol. Instead of needing a custom Dreamlit integration, Gemini CLI connects to Dreamlit’s MCP server and discovers the tools Dreamlit exposes. For Dreamlit, MCP means Gemini CLI 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 Gemini CLI 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 raw notification analytics: email and Slack sends and deliveries, email opens, clicks and bounces, overview metrics, per-recipient rows and workflow run rows.
Get prepared analysis	Ask Dreamlit for a lifecycle report or prioritized recommendations on Pro and Scale.
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 Gemini CLI 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 Gemini CLI:

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 Gemini CLI 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 Gemini CLI 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 Gemini CLI supports remote server authentication. Gemini CLI 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

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

Check status

Ask Gemini CLI:

Check Dreamlit MCP status and list my projects.

If Gemini CLI 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`, `edit_workflow_steps`, `rename_workflow`, `move_workflow_to_folder`, `send_workflow_test`	Create, edit, rename, or organize workflows into folders, and send draft message tests.
`workflows:publish`	`prepare_publish`, `confirm_publish`, `unpublish_workflow`	Validate, publish, schedule broadcasts, or unpublish workflows.
`analytics:read`	`get_analytics`, `get_lifecycle_report`, `get_recommendations`	Read raw notification analytics and request prepared analysis (Pro and Scale).

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

Tools

Gemini CLI 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. Each workflow includes the folder it’s in.
`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. Pass `includeEmailHtml` to get each email’s HTML.
`get_analytics`	`analytics:read`	Query raw notification analytics: email and Slack sends and deliveries, email opens, clicks and bounces, overview metrics, per-recipient rows and workflow run rows, with filters, sorting, and pagination.
`get_lifecycle_report`	`analytics:read`	Get Dreamlit’s prepared lifecycle analysis on Pro and Scale, or request one and check back when ready.
`get_recommendations`	`analytics:read`	Get prioritized emails or workflows to add and changes to existing ones on Pro and Scale, or request recommendations and check back when ready.
`create_or_update_workflow`	`workflows:write`	Create or update a draft from a natural-language prompt. Pass `name` to name a new workflow, or `startNewChat` to start a fresh chat.
`edit_workflow_steps`	`workflows:write`	Make up to 5 exact edits to existing email, Slack, query, and wait steps without AI: subject, HTML, sender, Slack message, SQL, wait, or description. Each edit applies on its own and shows in the workflow’s chat.
`rename_workflow`	`workflows:write`	Rename an existing workflow. Doesn’t change the draft or what’s live.
`move_workflow_to_folder`	`workflows:write`	Put a workflow or broadcast in a folder by name, creating the folder if needed, or pass `null` to take it out. Folders belong to one list (for example, Drafts), so a draft’s folder doesn’t carry over when you publish it.
`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 Gemini CLI supports MCP resources, it can read the guide for prompting guidance, trigger types, unsubscribe guidance, and the recommended Dreamlit MCP flow.

How do I get Dreamlit’s analysis?

Use get_lifecycle_report for Dreamlit’s prepared analysis of key metrics worth tracking, the signup-to-paid funnel and where users drop off, deliverability health, and which lifecycle stages have no emails yet: welcome, onboarding, engagement, retention, and winback. Use get_recommendations for prioritized emails or workflows to add and what to fix or change in existing ones. Both tools are available on Pro and Scale plans and require analytics:read. These reports are prepared by Dreamlit’s agents and reviewed by our team. Use get_analytics for raw notification analytics: email and Slack sends and deliveries, email opens, clicks and bounces, overview metrics, per-recipient rows and workflow run rows. Both accept an optional projectId. You can leave it out when your token is pinned to a project or your approved workspace has one accessible project.

If a report is ready, the tool returns state: "ready" with its Markdown body and timestamps.
Otherwise, it requests one and returns state: "processing". Check back later. Dreamlit also emails the original requester when it’s ready.
Pass refresh: true only when the user asks for a new report; when checking on a pending report, call without refresh. Refresh reuses an open request, otherwise returns the latest report if it was ready within the last 24 hours, or creates a new request. While it is being prepared, every call returns the processing state and includes the last ready report as previousReport.
On Free and AppSumo plans, the tool returns plan_upgrade_required with a billing link. Upgrade to Pro or Scale to use it. On Enterprise, it returns the same code with a support link; contact us to add reports to your plan.

Recommended workflow

Ask Gemini CLI to work in this order:

Check status

Start with get_status. This gives Gemini CLI 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. When editing, describe the steps to change by what they do, like “the email with subject Welcome back”, not by step ID.Each call continues the workflow’s current Dreamlit chat. For an unrelated change, or if Dreamlit keeps misreading the request, pass startNewChat to start fresh. The new chat still sees the current draft.When you already know the exact new value, like a new subject line, a fixed HTML body, or a corrected query, use edit_workflow_steps instead. It’s instant, uses no AI credits, and takes step IDs from get_workflow_and_preview_url.

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 Gemini CLI 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. Gemini CLI 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, including email activity such as recent opens or clicks, who opened a specific broadcast, emails that failed, or people this workflow already emailed this period
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 Gemini CLI 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 Gemini CLI is sending it as an Authorization: Bearer ... header.

Dreamlit tools do not appear after authorization

Start a new chat or session in Gemini CLI. If the tools still do not appear, restart Gemini CLI or restart the Dreamlit MCP server entry. Gemini CLI 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 Gemini CLI did not specify one. Ask Gemini CLI 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 Gemini CLI.

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 Gemini CLI 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

Get Started

Dreamlit for...

Guides

Configuration

Workflow

Step types

Troubleshooting

MCP

Resources

Dreamlit MCP for Gemini CLI

Why use Dreamlit MCP with Gemini CLI?

Server URL

Quick install

What is MCP?

What can Dreamlit MCP do?

Prerequisites

How does authorization work?

Permissions

Tools

How do I get Dreamlit’s analysis?

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

​Why use Dreamlit MCP with Gemini CLI?

​Server URL

​Quick install

​What is MCP?

​What can Dreamlit MCP do?

​Prerequisites

​How does authorization work?

​Permissions

​Tools

​How do I get Dreamlit’s analysis?

​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

Why use Dreamlit MCP with Gemini CLI?

Server URL

Quick install

What is MCP?

What can Dreamlit MCP do?

Prerequisites

How does authorization work?

Permissions

Tools

How do I get Dreamlit’s analysis?

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