D
Dreamlit
Create, test, publish, and manage Dreamlit notification workflows from AI clients.
Quick Install
Automated & IDE SetupCopy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.
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Manual Client & Custom JSON ConfigExpand JSON ▾
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💡 Paste into ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows)
Capabilities & Tool Schemas (11)
Inspect callable tools, capabilities, and parameters exposed to AI agents by Dreamlit.
get_statusGet Dreamlit guidance, workspace context, project setup, schema hints, workflow state, and app URLs.
list_projectsFind accessible Dreamlit projects in the approved workspace.
list_workflowsFind workflows in a project by name, description, trigger type, and pagination.
list_brand_kitsFind saved brand kit ids and style summaries with pagination before applying one to generated email drafts.
get_workflow_and_preview_urlInspect a workflow draft and get the Dreamlit preview or builder URL before editing or publishing.
get_analyticsQuery bounded notification analytics, recipient engagement, and workflow run data with filters and cursor pagination.
Documentation Overview
Dreamlit MCP
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:
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
To request every supported v1 scope explicitly:
MCP Inspector
Then choose Streamable HTTP and use:
Tools
Dreamlit exposes product-level workflow and analytics tools, not low-level graph editing or database 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. |
list_brand_kits | workflows:read | Find saved brand kit ids and style summaries with pagination before applying one to generated email drafts. |
get_workflow_and_preview_url | workflows:read | Inspect a workflow draft and get the Dreamlit preview or builder URL before editing or publishing. |
get_analytics | analytics:read | Query bounded notification analytics, recipient engagement, and workflow run data with filters and cursor pagination. |
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_statusfirst to understand the workspace, project setup, and prompting guidance. - Use
list_projectsandlist_workflowsif the user names a project or workflow without IDs. - Use
list_brand_kitswhen the user wants a specific saved brand kit applied to generated email drafts. - Use
get_workflow_and_preview_urlbefore editing an existing workflow. - Use
get_analyticsfor bounded analytics questions, filtering first and paginating with returned cursors for larger result sets. - Use
create_or_update_workflowto 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_publishfollowed byconfirm_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:
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:readworkflows:writeworkflows:publishanalytics: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.
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Frequently Asked Questions about Dreamlit
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