Dashboard MCP
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Dashboard MCPCreate a dashboard called Ops with a stats widget showing uptime."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Dashboard MCP
MCP connector + read-only web viewer for dashboards fully controlled by an AI agent. Supports any number of independent dashboards — each with its own slug, file, and URL /d/<slug>.
Live service: https://dashboard.89-207-254-32.nip.io
Dashboard list:
/Specific dashboard (read-only, auto-refresh every 5s):
/d/<slug>JSON API (also read-only):
/api/dashboards,/api/dashboards/<slug>MCP endpoint (OAuth required):
/mcp
How it works
mcp_app.py— creates a singleMCPServer, with OAuth (ifOAUTH_*variables are set) or without (for local development).tools.py— MCP tools (@mcp.tool()):list_dashboards,create_dashboard,get_dashboard,update_dashboard_meta,delete_dashboard,add_widget,update_widget,remove_widget,reorder_widgets,replace_widgets. This is how the agent manages dashboards. They are protected by OAuth at/mcp.web.py— public HTML pages and JSON API (@mcp.custom_route, per the SDK documentation do not require authorization) — this is what people look at in the browser.models.py— pydantic widget schemas:text,list,stats,progress,chart.store.py— file storage, one JSON per dashboard indata/dashboards/.
Related MCP server: Agent Team MCP Server
Widget types
{"type": "text", "title": "Заметка", "body": "..."}
{"type": "list", "title": "Задачи", "ordered": false, "items": [{"label": "...", "value": "...", "note": "..."}]}
{"type": "stats", "title": "Метрики", "items": [{"label": "MRR", "value": "128k", "unit": "₽", "delta": "+12%", "trend": "up"}]}
{"type": "progress", "title": "Прогресс", "items": [{"label": "Q3", "value": 62, "max": 100, "color": "#395b4b"}]}
{"type": "chart", "title": "Динамика", "chartType": "line", "labels": ["Пн","Вт"], "series": [{"name": "Заказы", "data": [3, 7]}]}Common fields: title (optional), size: sm|md|lg|full (width in the grid).
Local run
pip install -r requirements.txt
cp .env.example .env # можно оставить OAUTH_* пустыми — сервер поднимется без auth
MCP_TRANSPORT=streamable-http python server.py
# либо просто `python server.py` для stdio (claude mcp add / MCP Inspector)How to connect the connector in Claude
A static OAuth client has been created on the server (Client ID/Secret are issued separately).
In Claude: Settings → Connectors → Add custom connector.
URL:
https://dashboard.89-207-254-32.nip.io/mcpClient ID / Client Secret — as issued during deployment.
After authorization, the tools from
tools.pybecome available to the agent.
Deployment
The production server pulls this repository itself: deploy/deploy.sh runs via cron every 2 minutes, compares the local HEAD with origin/main, and if there are new commits — git reset --hard + docker compose up -d --build + a /healthz check. Just git push to main — changes will be picked up on production automatically within ~2 minutes.
Last verified deploy: 2026-08-19T15:29:01Z
This server cannot be deployed
Maintenance
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