Visual MCP
Visual MCP
Ein Model Context Protocol Server, der einer KI eine strukturierte visuelle Ebene bereitstellt: Er beschreibt, was existiert, und erhält ein sauberes, präzises SVG-Diagramm zurück – anstelle von ASCII-Art.
Was ist Visual MCP?
Bittet man eine KI, "die Architektur zu zeichnen", erhält man dies:
+----------+ +---------+ +------------+
| React |----->| NestJS |----->| PostgreSQL |
+----------+ +---------+ +------------+
|
+-----> Redis?Box-Zeichen sind ein schlechtes Medium für räumliche Informationen. Ausrichtung bricht, Pfeile erreichen ihr Ziel nicht, nichts lässt sich nachträglich bearbeiten, und das Modell verbraucht Rechenleistung für das Zählen von Zeichen.
Die naheliegende Lösung – "die KI SVG schreiben lassen" – ist noch schlimmer. Dann muss sie viewBoxes, Pfaddaten, Pfeilspitzen-Polygone, Textbaselines und Randüberschneidungen berechnen, alles von Hand, alles ohne Rückmeldung, und alles wieder von Grund auf, sobald der Benutzer eine kleine Änderung wünscht.
Visual MCP entfernt die Geometrie aus der Aufgabe des Modells. Das Modell arbeitet mit einem Szenengraphen:
{
"title": "Service architecture",
"elements": [
{ "id": "frontend", "type": "node", "label": "React" },
{ "id": "backend", "type": "node", "label": "NestJS" },
{ "id": "db", "type": "database", "label": "PostgreSQL" },
{ "id": "cache", "type": "database", "label": "Redis" },
{ "id": "c1", "type": "connection", "from": "frontend", "to": "backend" },
{ "id": "c2", "type": "connection", "from": "backend", "to": "db" },
{ "id": "c3", "type": "connection", "from": "backend", "to": "cache" }
]
}Beachten Sie, was nicht da ist: keine Koordinaten, keine Größen, keine Linienendpunkte, keine Pfeilspitzen, kein SVG. Der Server berechnet alles – Knotengrößen aus den Beschriftungen, Positionen aus dem Verbindungsgraphen, Kanten, die die Ränder treffen, Pfeilspitzenmarkierungen, Textumbruch und eine viewBox, die nichts abschneiden kann.
Und weil die Szene ein Graph mit stabilen IDs ist, ist der nächste Gesprächsschritt eine einzeilige Bearbeitung statt einer Neuzeichnung:
"Setze Redis oberhalb des Backends und PostgreSQL unterhalb." →
update_element× 2, alles andere bleibt unberührt.
"Stecke nun die gesamte Infrastruktur in eine Box namens AWS." →
group_elements, und nichts bewegt sich.
Related MCP server: Mermaid MCP Server
Architektur
ChatGPT
│ tool call: render_diagram / update_element / …
▼
MCP server src/mcp/ (transport, tools, error shaping)
│
▼
Scene graph src/scene/ (Zod schemas, validation, store, mutations)
│
├─▶ layout src/layout/ (sizes and positions for elements with no coordinates)
├─▶ semantic src/semantic/ (node/connection/axis/… ▸ primitives)
│
▼
SvgNode tree src/renderer/ (closed, allow-listed representation of an SVG document)
│
├─▶ toSvgString() ─────────────────▶ SVG returned by the MCP tools
└─▶ <SceneRenderer> ────────────────▶ React, for the interactive UIFünf Ideen halten das Ganze zusammen
1. Der Szenengraph ist das Artefakt, SVG ist nur ein Ausgabeformat.
Alles, was das Modell sendet, wird zu einer Scene validiert und gespeichert. Das Rendern ist eine reine Funktion dieser Szene, sodass dasselbe Diagramm später in einem anderen Thema oder durch ein anderes Backend neu gerendert werden kann, ohne dass das Modell involviert ist.
2. Semantische Elemente werden zu Primitiven kompiliert.
database wird zu einem Pfad, einer Ellipse und zwei Textblöcken. connection wird zu einem Pfad mit einer Markierung. Der Renderer sieht nur die zehn Primitiven – das hält ihn klein, und das Hinzufügen von neuron, decisionTree oder functionPlot später ist eine Erweiterungsdatei in src/semantic/, ohne Änderung der Schema-Union, der Layout-Engine oder des Renderers.
3. Eine Geometrie-Pipeline, zwei Backends.
Die eigentliche Ausgabe des Renderers ist ein SvgNode-Baum, kein String. serialize() wandelt ihn in Markup für die MCP-Tools um; <SceneRenderer> bildet ihn auf React-Elemente für die UI ab. Es gibt keine zweite Implementierung, die abweichen könnte, und kein dangerouslySetInnerHTML irgendwo im Projekt.
4. Fehler werden für ein Modell geschrieben, nicht für eine Logdatei.
{
"success": false,
"error": {
"code": "ELEMENT_NOT_FOUND",
"message": "Connection 'c1' points to 'router-2' (to), which does not exist in the scene.",
"path": "c1.to",
"hint": "Existing elements you can connect: pc, switch, router-1, server."
}
}Ein Code, nach dem verzweigt werden kann, ein Satz, der das Problem benennt, und ein Hinweis, der die Antwort enthält. Niemals ein Stacktrace.
5. Jede Mutation ist atomar. Eine abgelehnte Bearbeitung hinterlässt die gespeicherte Szene bytegenau so, wie sie war. Ohne das würde ein einziger fehlerhafter Aufruf das Diagramm für den Rest des Gesprächs zerstören.
Abweichungen vom ursprünglich skizzierten Layout
src/layout/ist ein eigenes Modul, getrennt vonsrc/semantic/. Positionierung und Expansion von Bedeutung zu Form sind unterschiedliche Probleme, und die Aufteilung ist es, die das Austauschen von Dagre oder ELK später zu einer Änderung in einer Datei (src/layout/flow.ts) macht – derenFlowItem-in-/out-Schnittstelle bewusst die Form dieser Bibliotheken widerspiegelt.SvgNodesitzt zwischen dem Renderer und seiner Ausgabe (Idee 3 oben), was es ermöglicht, dass die React-Ansicht ohne einen zweiten Renderer und ohne unsichere HTML-Injektion existiert.src/mcp/widget.tsist ein abhängigkeitsfreier Vanilla-Viewer, getrennt von der React-App insrc/ui/. Die ChatGPT-iframe-Ressource muss ein einzelner, in sich geschlossener HTML-String sein, ohne Build-Schritt, der zur Laufzeit veraltet oder fehlen könnte; die React-App ist der lokale Spielplatz. Sie teilen dasselbe Verhalten (Zoom/Pan/Fit/Kopieren/Exportieren) und dieselbe Erlaubnisliste.Auto-Fit ist standardmäßig aktiviert, sodass
width/heightals Hinweise und nicht als harte Leinwand fungieren. Dies beseitigt den häufigsten Fehlermodus – ein Modell wählt eine zu kleine Leinwand und schneidet sein eigenes Diagramm ab.
Installation
git clone <this repo>
cd visual-mcp
npm installErfordert Node 20+ (entwickelt auf Node 22/26).
Entwicklung
npm run dev:http # MCP server over Streamable HTTP on http://localhost:3333/mcp
npm run dev:stdio # MCP server over stdio (Claude Desktop, MCP Inspector, tunnels)
npm run dev:ui # React playground on http://localhost:5180
npm test # 128 tests
npm run typecheck
npm run build # server → dist/
npm run build:ui # playground → dist-ui/
npm run examples # render the reference scenes → examples/out/index.htmlSchneller End-to-End-Check gegen einen laufenden Server:
npm run dev:http &
npx tsx scripts/smoke-mcp.tsEs spielt die gesamte Zielkonversation nach – baue ein Diagramm ohne Koordinaten, inspiziere es, verschiebe zwei Knoten, verpacke alles in eine Box – und prüft das Ergebnis bei jedem Schritt.
Verfügbare MCP-Tools
Tool | Was es tut | Wann das Modell danach greifen sollte |
| Erstellt und rendert eine ganze Szene in einem Aufruf, gibt eine | Jede Aufforderung, etwas zu zeichnen, visualisieren, diagrammieren, illustrieren oder visuell zu erklären. Der Standard-Einstiegspunkt. |
| Rendert eine gespeicherte Szene erneut. | Nach einer Reihe von Bearbeitungen, um das Ergebnis zu zeigen. |
| Gibt die Szene plus die berechneten Boxen jedes Elements zurück. | Vor dem Bearbeiten – insbesondere für relative Änderungen ("etwas nach rechts"). |
| Fügt ein Element hinzu, optional innerhalb einer Gruppe. | "Füge einen Load Balancer hinzu", "zeichne einen Pfeil von A nach B". |
| Ändert nur die angegebenen Felder; | Jede "ändere das"-Anfrage. Niemals dafür neu zeichnen. |
| Löscht ein Element, kaskadierend seine Verbindungen und Beschriftungen. | "Entferne den Cache". |
| Fasst Elemente der obersten Ebene in einer beschrifteten Box zusammen, ohne etwas zu verschieben. | "Stecke das alles in AWS", "gruppiere diese in eine VPC". |
| Erstellt eine leere Leinwand. | Nur beim schrittweisen Aufbau eines großen Diagramms. |
| Leert eine Szene, behält ihre Leinwand/Thema/Überschrift. | "Weg damit, fangen wir von vorne an". |
| Gibt funktionierende Beispielszenen und den Typenkatalog zurück. | Wenn man unsicher ist, wie man etwas ausdrückt – kopieren und anpassen. |
Jede Toolbeschreibung sagt, was es tut, wann man es verwendet, wann nicht, und was jede Eigenschaft bedeutet, weil ein anderes Modell diese liest und selbstständig entscheidet. Schreibgeschützte Tools tragen readOnlyHint: true und destruktive destructiveHint: true, die Hosts verwenden, um zu entscheiden, was eine Bestätigung erfordert.
Szenen-Schema
interface Scene {
id?: string;
title?: string;
subtitle?: string;
width?: number; // hint; autoFit grows the canvas so nothing is clipped
height?: number;
autoFit?: boolean; // default true
background?: string;
theme?: "dark" | "light" | "blueprint" | "paper";
themeOverrides?: Partial<Theme>;
layout?: "auto" | "layered" | "horizontal" | "vertical" | "grid" | "manual";
direction?: "right" | "down" | "left" | "up";
gap?: number;
padding?: number;
legend?: boolean;
elements: VisualElement[];
}Jedes Element hat id und type. IDs sind stabil und ermöglichen die konversationelle Bearbeitung.
Primitive – was der Renderer zeichnen kann
circle · ellipse · rectangle · line · arrow · text · polygon · polyline · path ·
group
Semantische Elemente – was das Modell tatsächlich verwenden sollte
Typ | Zweck |
| Beschriftete Box. Zehn Formen ( |
| Verknüpfung nach ID: |
| Beschrifteter Container mit eigenem Layout. Begrenzungen wie "AWS", "VLAN 10". |
| Ein Koordinatensystem und ein Datenrahmen. |
| Markierungen und Linien in Daten-Koordinaten, wenn |
| Beschriftung, die nach ID an ein anderes Element angehängt werden kann und ihm folgt. |
| Domänenvorgaben – ein |
Layout
layout: "auto" (Standard) erstellt einen geschichteten Fluss aus dem Verbindungsgraphen, falls vorhanden, ansonsten eine Zeile. Elemente mit explizitem x/y werden nie bewegt, sodass das Modell einen Knoten verschieben kann, ohne die anderen zu stören. direction steuert, in welche Richtung der Fluss wächst.
Datenrahmen
Ein axis deklariert eine Abbildung von Dateneinheiten zu Pixeln; alles mit frame: "<axis id>" wird in Datenkoordinaten platziert, mit y, das nach oben wächst, wie es sein sollte:
{ "id": "plot", "type": "axis", "x": 90, "y": 70, "width": 620, "height": 420,
"xRange": [0, 10], "yRange": [0, 10], "xLabel": "Feature 1", "yLabel": "Feature 2" },
{ "id": "class-a", "type": "cluster", "frame": "plot", "x": 3.4, "y": 6.6,
"count": 40, "spread": 0.8, "label": "Class A", "hull": true, "seed": 7 }Themen
Vier eingebaute Themen (dark, light, blueprint, paper), jedes eine vollständige Palette plus einen Schriftstapel, der keine externen Schriftarten benötigt. Elemente beziehen sich auf Token – primary, surface, muted, danger – anstatt auf hartcodierte Farben, sodass ein ganzes Diagramm umgestaltet wird, ohne seine Geometrie zu berühren. themeOverrides ändert jeden Token.
Lokales Ausführen
Als Bibliothek, ganz ohne MCP
import { renderScene } from "visual-mcp";
const svg = renderScene({
title: "Request flow",
elements: [
{ id: "client", type: "computer", label: "Client" },
{ id: "api", type: "server", label: "API" },
{ id: "c", type: "connection", from: "client", to: "api", label: "HTTPS" },
],
});Als HTTP-Server
npm run dev:httpRoute | |
| MCP Streamable HTTP-Endpunkt |
| Health-Check |
| Gespeicherte Szenen |
| Eine gerenderte Szene |
| Der interaktive Viewer, eigenständig |
Der Server ist zustandslos: Jede Anfrage erhält einen eigenen McpServer und Transport, und der Szenenspeicher ist der einzige gemeinsame Zustand. Das macht ihn sicher hinter einem Load Balancer oder auf einer serverlosen Plattform, wo zwei Schritte einer Konversation möglicherweise nicht denselben Prozess erreichen.
Als stdio-Server (MCP Inspector, Claude Desktop, Cursor)
npx @modelcontextprotocol/inspector npx tsx src/mcp/stdio.ts{
"mcpServers": {
"visual-mcp": {
"command": "node",
"args": ["/absolute/path/to/visual-mcp/dist/mcp/stdio.js"]
}
}
}Verbindung zu ChatGPT
ChatGPT erreicht entfernte MCP-Server über Streamable HTTP an einem öffentlichen HTTPS-Endpunkt, daher muss der Server vom Internet aus erreichbar sein. Zwei Möglichkeiten:
A. Schneller Test mit einem Tunnel
npm run dev:http # http://localhost:3333/mcp
npx localtunnel --port 3333 # or: ngrok http 3333, or cloudflared tunnelB. Bereitstellung mit Docker auf einem VPS
docker-compose.yml startet zwei Container: den MCP-Server auf Port 4000 (nicht ins Internet veröffentlicht) und Caddy, der davor TLS terminiert und das Zertifikat automatisch erneuert.
Dieser VPS hat bereits andere Dienste auf den Ports 80 und 443, daher:
Port | Grund | |
HTTPS / MCP-Endpunkt | 500 | 443 ist belegt |
ACME HTTP-01-Challenge | 90 | 80 ist belegt |
MCP-Server | 4000 | nur intern, nie veröffentlicht |
Der Haken: Let's Encrypt verbindet sich für HTTP-01 immer mit Port 80 – das ist durch RFC 8555 festgelegt und kann nicht konfiguriert werden – und TLS-ALPN ist ebenfalls auf 443 festgelegt. Caddy kann auf 90 hören, aber irgendetwas muss die Anfrage dorthin leiten. Also muss der Dienst, der bereits Port 80 belegt, den Challenge-Pfad an Caddy weiterleiten.
1. Wähle einen öffentlichen Hostnamen. ChatGPT benötigt HTTPS, und eine reine IP kann kein Zertifikat haben. Ohne eine eigene Domain verwende sslip.io – es löst <ip>.sslip.io ohne Registrierung zu dieser IP auf, und Let's Encrypt stellt Zertifikate dafür aus:
curl -4 ifconfig.me # on the VPS -> e.g. 203.0.113.45
# hostname becomes: 203.0.113.45.sslip.io2. Leite die ACME-Challenge vom Port-80-Server weiter. Identifiziere ihn zuerst:
sudo ss -lptn 'sport = :80'nginx – innerhalb des server { listen 80; }-Blocks:
location /.well-known/acme-challenge/ {
proxy_pass http://127.0.0.1:90;
proxy_set_header Host $host;
}Apache – innerhalb des <VirtualHost *:80>:
ProxyPreserveHost On
ProxyPass /.well-known/acme-challenge/ http://127.0.0.1:90/.well-known/acme-challenge/
ProxyPassReverse /.well-known/acme-challenge/ http://127.0.0.1:90/.well-known/acme-challenge/Caddy – innerhalb des Site-Blocks, der Port 80 bedient:
handle /.well-known/acme-challenge/* {
reverse_proxy 127.0.0.1:90
}Verwende einen echten Proxy, keine 301-Weiterleitung: Let's Encrypt folgt Weiterleitungen nur zu den Ports 80 und 443, daher würde eine Weiterleitung zu :90 fehlschlagen.
3. Konfiguriere und starte:
cp .env.example .env
# MCP_DOMAIN=203.0.113.45.sslip.io
docker compose up -d --buildWenn der Port-80-Server in einem eigenen Container und nicht auf dem Host läuft, ist 127.0.0.1:90 von dort aus nicht erreichbar – setze MCP_HTTP_BIND=0.0.0.0 in .env und richte den Proxy auf die interne IP des VPS (oder platziere beide Container in einem Docker-Netzwerk).
4. Überprüfe (die erste Anfrage kann einige Sekunden dauern, während das Zertifikat ausgestellt wird):
curl https://$MCP_DOMAIN:500/health # {"status":"ok",...}
docker compose logs caddy | grep -i "certificate obtained"Die MCP-URL lautet dann https://<MCP_DOMAIN>:500/mcp und ist dauerhaft: restart: unless-stopped überlebt Neustarts, und die Zertifikate leben im caddy_data-Volume, sodass Erneuerungen über docker compose down/up hinweg bestehen bleiben. Nur docker compose down -v löscht sie. Behalte die Challenge-Weiterleitung bei – Erneuerungen alle ~60 Tage benötigen sie genauso wie die Erstausstellung.
PUBLIC_URL und ALLOWED_HOSTS werden von Compose aus MCP_DOMAIN und MCP_HTTPS_PORT abgeleitet. Beide müssen den Port enthalten: PUBLIC_URL, weil svgUrl-Links sonst auf 443 zeigen würden, und ALLOWED_HOSTS, weil das SDK den rohen Host-Header – der bei einem nicht standardmäßigen Port <domain>:500 lautet – als exakten String vergleicht.
Wenn du den Port-80-Server nicht anfassen kannst, ist HTTP-01 überhaupt nicht verfügbar. Die Optionen sind eine DNS-01-Challenge (benötigt eine echte Domain bei einem unterstützten DNS-Anbieter – sslip.io hat keine API) oder ein Cloudflare Tunnel, der überhaupt keine eingehenden Ports benötigt.
Ohne Compose
docker build -t visual-mcp .
docker run -d --name visual-mcp --restart unless-stopped -p 127.0.0.1:4000:4000 \
-e PUBLIC_URL=https://your-host -e ALLOWED_HOSTS=your-host visual-mcpRichte dann einen beliebigen Reverse-Proxy auf http://127.0.0.1:4000 aus. Der Container läuft als nicht-root node-Benutzer, hat einen /health-HEALTHCHECK und enthält nur Produktionsabhängigkeiten. Auch verwaltete Plattformen (Fly.io, Railway, Render, Cloud Run) funktionieren – sie injizieren ihren eigenen PORT, den der Server beachtet.
Dann in ChatGPT
Aktiviere den Entwicklermodus. Er ist auf ChatGPT Business, Enterprise und Edu im Web verfügbar. Ein Admin aktiviert ihn unter Workspace-Einstellungen → Berechtigungen & Rollen → Verbundene Daten → Entwicklermodus / Benutzerdefinierte MCP-Connectors erstellen.
Einstellungen → Connectors → Erstellen / Erweitert → Entwicklermodus → Benutzerdefinierten Connector hinzufügen.
Fülle aus:
Name:
Visual MCPMCP-Server-URL:
https://<your-host>/mcpAuthentifizierung:
Keine Authentifizierung(dieser Server wird ohne Authentifizierung ausgeliefert – siehe Sicherheit)
Speichern. ChatGPT ruft sofort
tools/listauf; du solltest die zehn Tools aufgelistet sehen.Aktiviere in einem neuen Chat den Connector und bitte um ein Diagramm.
Der Server registriert auch eine MCP Apps UI-Ressource (ui://visual-mcp/scene.html, text/html;profile=mcp-app), die über _meta.ui.resourceUri und das ChatGPT-Alias _meta["openai/outputTemplate"] an die Rendering-Tools gebunden ist. Wo dies unterstützt wird, erscheint das Diagramm in einem interaktiven Frame mit Zoom, Schwenken, Anpassen, Kopieren und Exportieren; andernfalls geben die Tools das SVG weiterhin in structuredContent zurück, sodass der Server anmutig degradiert.
Beispiele
npm run examples rendert alle fünf nach examples/out/index.html, und list_examples serviert sie dem Modell.
1. Netzwerk – examples/out/network.svg
Domain-Voreinstellungen und automatisches Layout von links nach rechts. computer → switch → router → server, mit VLAN-Beschriftungen auf den Verbindungen. Keine Koordinaten irgendwo in der Quell-Szene.
2. LDA – examples/out/lda.svg
Ein axis-Datenrahmen, zwei gesäte cluster mit weichen Hüllen, eine gestrichelte Entscheidungsgrenze und die LDA-Richtung – alles in Datenkoordinaten, beide Linien auf den Plot beschnitten.
3. Regression – examples/out/regression.svg
Achse, eine scatter-Serie und eine angepasste plotLine mit extend: true, im hellen Thema.
4. Softwarearchitektur – examples/out/architecture.svg
React → REST API → { Redis, PostgreSQL }, mit den beiden Speichern innerhalb einer beschrifteten group ("Data layer"), in die die Verbindungen hineinführen.
5. Binärbaum – examples/out/tree.svg
Sieben kreisförmige Knoten und sechs Verbindungen; das geschichtete Layout mit Flussrichtung down erzeugt den Baum.
Auszuprobierende Prompts in ChatGPT
Draw the architecture where React talks to NestJS, NestJS uses PostgreSQL and also queries Redis.
Now put Redis above the backend and the database below it.
Now put all the infrastructure inside a box called AWS.
Make PostgreSQL bigger and give it a purple border.
Explain Linear Discriminant Analysis visually.
Show me graphically how linear regression works.
Draw a network where a PC in VLAN 20 reaches a server in VLAN 10 through a switch and a router.
Draw a balanced binary tree with 7 nodes.
Explain the TCP three-way handshake as a diagram.
Diagram merge sort on [5, 2, 9, 1].Sicherheit
Das Bedrohungsmodell ist einfach: Alles, was der Server rendert, stammt von einem Sprachmodell, und diese Ausgabe kann selbst Text enthalten, den der Benutzer von woanders eingefügt hat. Daher wird niemals etwas, das vom Modell stammt, als Code behandelt.
Geschlossenes Schema. Nur die vierundzwanzig bekannten Elementtypen werden geparst. Farben müssen einer Hex-/RGB-/HSL-/Schlüsselwort-/Token-Grammatik entsprechen –
url(javascript:…)wird bei der Validierung abgewiesen. Pfaddaten müssen SVG-Pfadbefehlen und Zahlen entsprechen, sonst nichts.Positivliste für Ausgaben. Der Renderer kann nur Tags und Attribute aus zwei expliziten Listen in
src/renderer/svgNode.tsausgeben. Es gibt keinon*, keinhref, keinstyle, keinclass, kein<foreignObject>, kein<script>– das Modell kann sie nicht ausdrücken, und der Serialisierer würde sie ohnehin fallen lassen.Escaping. Textinhalte und Attributwerte werden beim Verlassen XML-escaped.
Kein
dangerouslySetInnerHTML, keineval, keinnew Functionirgendwo im Projekt. Die React-Ansicht baut Elemente aus demSvgNode-Baum; das ChatGPT-Widget parst das SVG und baut es Knoten für Knoten gegen dieselben Positivlisten neu auf, sodass selbst ein kompromittierter Server kein Skript in diesen Frame bringen kann.Begrenzte Eingabe. Elementanzahlen, Zeichenkettenlängen, Punktanzahlen, Pfadlänge und gespeicherte Szenen sind alle begrenzt; Szenen werden nach dem FIFO-Prinzip verdrängt.
Keine Stack-Traces für das Modell. Jeder Handler ist umschlossen; alles Unerwartete wird zu
INTERNAL_ERRORmit einer kurzen Nachricht.
Tests in tests/security.test.tsx bestätigen jeden dieser Punkte.
Nicht enthalten, absichtlich: Authentifizierung. Der Server gibt keine Geheimnisse preis und berührt kein externes System, aber eine öffentliche Bereitstellung ist ein öffentlicher Szenenspeicher. Setze ihn hinter die Authentifizierung deiner Plattform oder füge OAuth über die Auth-Helfer des SDKs hinzu, bevor du ihn anderen als dir selbst zugänglich machst. Setze ALLOWED_HOSTS, um den DNS-Rebinding-Schutz zu aktivieren, wenn er von einem Browser aus erreichbar ist.
Aktuelle Einschränkungen
Textmetriken werden geschätzt, nicht gemessen – es gibt keine Schriftart-Engine auf dem Server. Breiten liegen für die gebündelten serifenlosen Stapel innerhalb weniger Prozent, was für Boxen und Zeilenumbrüche ausreicht, aber eine ungewöhnliche Schriftart oder viel CJK wird etwas locker dimensioniert.
Die Layout-Engine ist bewusst klein. Längster-Pfad-Schichtung mit Rangzentrierung. Sie hat keine Kreuzungsminimierung und keine Überlappungsauflösung, daher erzeugt ein dichter Graph (etwa 25+ Knoten mit vielen Querverbindungen) Kreuzungen, die eine echte Engine vermeiden würde. Die Schnittstelle ist genau aus diesem Grund Dagre-förmig.
Baumlayouts sind nicht kindzentriert; ein Elternteil sitzt in der Mitte seines Ranges, nicht über dem Mittelpunkt seiner Kinder.
Das JSON-Schema von
render_diagramist etwa 50 KB (~12k Tokens), weil es das gesamte Elementvokabular lehrt. Die anderen neun Tools summieren sich auf ~5 KB. Das ist ein bewusster Kompromiss: Das Modell erhält feldweise Dokumentation und benötigt selten eine Reparaturrunde.Innerhalb einer Gruppe mit automatischem Layout werden explizite
x/yder Kinder ignoriert – das Layout gewinnt. Verwendelayout: "manual"auf der Gruppe, um Kinder selbst zu positionieren.Der Speicher ist im Arbeitsspeicher. Szenen überleben keinen Neustart, und bei mehreren Replikaten lebt eine Szene auf der Instanz, die sie erstellt hat. Das
SceneStore-Interface existiert, sodass dies eine auszutauschende Klasse ist.Statische Ausgabe. Noch keine Animation, kein 3D, kein Mathe-Ausdrucksparser – siehe unten.
Fahrplan
Als Nächstes
Persistenter
SceneStore(zuerst SQLite) – das Interface ist bereits vorhanden.Rückgängig/Wiederholen. Jede Mutation wird bereits als
SceneMutationaufgezeichnet; es ist eine Frage der Speicherung der Umkehrung.Dagre oder ELK hinter
src/layout/flow.tsfür dichte Graphen, mit der kleinen Engine als Standard.Kindzentriertes Baumlayout.
Mathe – der axis-Datenrahmen ist die Grundlage; jeder davon ist ein Expander in src/semantic/, ohne Renderer-Änderung:
functionPlot ({ "expression": "x^2", "domain": [-5, 5] }), vector, matrix, plane, distribution, projection, decisionBoundary und regressionLine als benannte Aliase von plotLine.
Diagrammvokabular – neuron, neuralNetwork, decisionTree, sequenceDiagram, stateMachine, gantt, swimlane.
Animation – { "animation": { "type": "flow", "duration": 1200 } } auf einer Verbindung, ausgegeben als SVG SMIL oder CSS, sodass es deklarativ bleibt und keine Laufzeit benötigt. Pakete, die sich entlang einer Verbindung bewegen, eine Anfrage, die durch eine Pipeline reist, ein Algorithmus, der durch eine Struktur schreitet.
Andere Renderer – die Auflösungspipeline endet bereits in einem backend-agnostischen Baum. Eine Scene mit kind: "3d" und { "type": "sphere", "position": [0, 1, 0] } würde ein Three.js-Backend anstelle des SVG-Backends auswählen; ein Canvas-Backend würde sehr große Streudiagramme bedienen. Keine Änderung an der MCP-Schicht.
Lizenz
MIT
Available Tools
10 toolsadd_elementAdd an elementA
Add one element to a scene that already exists.
USE THIS when the user wants something new in a diagram you already drew: "add a load balancer", "put a Redis cache next to the API", "draw an arrow from A to B".
Call get_scene first if you are not certain which ids exist. To link the new element to an existing one, make a second call with an element of type 'connection' referencing the two ids - the geometry is computed for you.
Omit x/y and the layout engine places it. Set parentId to put it inside a group.
This does not display anything. Call render_scene once your edits are done.
| Name | Required | Description | Default |
|---|---|---|---|
| element | Yes | The element to add: an object with a unique `id`, a `type`, and the properties of that type - exactly the same shape as the entries of `elements` in render_diagram. Types: node, connection, group, axis, point, scatter, cluster, plotLine, label, server, database, router, switch, computer, cloud, circle, ellipse, rectangle, line, arrow, text, polygon, polyline, path. Example: { "id": "cache", "type": "database", "label": "Redis" }. | |
| sceneId | Yes | Id of the scene to work on, as returned by render_diagram or create_scene. | |
| parentId | No | Id of a 'group' element to nest this inside. |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | Present only when success is false. |
| sceneId | No | |
| success | Yes | |
| elementId | No | |
| elementCount | No | Top-level elements in the scene after the add. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (which are all false and give no safety hints), the description richly discloses behavior: 'Omit x/y and the layout engine places it', 'the geometry is computed for you', and 'This does not display anything. Call render_scene once your edits are done.' It also explains that parentId nests the element inside a group. These are meaningful behavioral traits not present in annotations or schema descriptions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded: a one-sentence summary, a bold 'USE THIS' callout, then prerequisites, special cases, and rendering note. Every sentence adds unique value—no fluff or repetition of schema content. It is compact despite covering multiple scenarios (first-time adds, connections, layout, grouping, rendering).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is remarkably complete for a tool with nested objects and 3 parameters. It covers prerequisites (get_scene), the exact workflow for linking elements (connection type), layout behavior (omit x/y), grouping (parentId), and the follow-up step (render_scene). Since an output schema exists, the lack of return-value explanation is acceptable. The tool feels self-contained for an agent to invoke successfully.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so parameters are well-documented in the schema. The tool description nevertheless adds significant value: it explains that the element object is 'exactly the same shape as the entries of elements in render_diagram', provides a concrete example, and clarifies behavior of x/y (omit for auto-layout). This goes beyond the schema, though the core parameter meanings are already covered, so a 4 is appropriate rather than 5.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a clear, specific statement: 'Add one element to a scene that already exists.' This uses a strong verb ('Add'), defines the resource ('element'), and the target ('scene'). It distinguishes itself from sibling tools like update_element, remove_element, and group_elements by focusing solely on adding new elements. Concrete usage examples ('add a load balancer', 'draw an arrow from A to B') further clarify the purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit 'USE THIS' guidance tells the agent exactly when to apply the tool: 'when the user wants something new in a diagram you already drew.' It also provides alternative and prerequisite actions: 'Call get_scene first if you are not certain which ids exist' and 'Call render_scene once your edits are done.' The connection workflow is explained with 'make a second call with an element of type 'connection'', giving clear usage boundaries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
clear_sceneEmpty a sceneADestructiveIdempotent
Remove every element from a scene while keeping its id, canvas, theme and title.
USE THIS when the user wants to restart the drawing but keep talking about the same diagram: "scrap that, let's do it differently".
DO NOT use it for corrections - update_element and remove_element exist for that, and they preserve everything the user already approved.
| Name | Required | Description | Default |
|---|---|---|---|
| sceneId | Yes | Id of the scene to work on, as returned by render_diagram or create_scene. |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | Present only when success is false. |
| sceneId | No | |
| success | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds significant behavioral context beyond what annotations provide. Annotations already indicate destructiveHint=true, so the destructive nature is known. But the description clarifies exactly what is destroyed (every element) and what is preserved (id, canvas, theme, title). It also notes that this is idempotent (idempotentHint=true is already in annotations). The only missing detail is whether undo is possible or what the output schema returns, but the output schema exists to specify that.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences with zero wasted words. The first sentence defines purpose and scope concisely. The second and third sentences provide usage guidelines and sibling differentiation in a clear, front-loaded manner. The 'USE THIS when' and 'DO NOT use it' structure is exceptionally clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple tool with only one parameter, clear annotations, and an output schema, the description is complete. It covers purpose, scope, preservation details, usage context, and exclusions. There is no missing critical information for an AI agent to correctly select and invoke this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single parameter, and the schema already documents that sceneId must match a specific pattern and length, and gives a helpful description. The description adds context by referring to 'as returned by render_diagram or create_scene', which helps in understanding how to obtain the correct ID. This surpasses the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool removes every element from a scene while preserving its id, canvas, theme, and title. It specifies the verb 'Remove every element' and the resource 'scene', and distinguishes itself from siblings like update_element and remove_element by describing its unique behavior of clearing all elements.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use the tool ('when the user wants to restart the drawing but keep talking about the same diagram') and provides a concrete user utterance ('scrap that, let's do it differently'). It also explicitly tells when NOT to use it ('DO NOT use it for corrections') and names the appropriate alternatives (update_element and remove_element).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
create_sceneCreate an empty sceneA
Create a new, empty scene and get back its id.
USE THIS when you want to build a diagram incrementally - create the canvas, then add elements one at a time with add_element, then call render_scene when it is complete.
DO NOT use this when you already know the whole picture: render_diagram does the same job in one round trip and is almost always the better choice. Incremental building is only worth it for large diagrams you are assembling as the conversation goes.
Nothing is shown to the user until you call render_scene.
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | Stable, meaningful id (e.g. 'backend'). Reuse it later to update or remove this element. | |
| gap | No | Spacing used by the automatic layout. Default 90. | |
| theme | No | Visual theme. 'dark' (default) is a modern technical look, 'light' is for documents, 'blueprint' is a blue schematic, 'paper' is warm and printable. | |
| title | No | Diagram title, drawn at the top. Keep it short - it is a caption, not a sentence. | |
| width | No | Canvas width in pixels. Default 960. Use 1200+ for wide flows. | |
| height | No | Canvas height in pixels. Default 600. | |
| layout | No | How elements without explicit x/y are placed. 'auto' (default) builds a layered flow from the connections when there are any, otherwise a row. 'layered' forces the flow layout, 'horizontal'/'vertical'/'grid' force a simple arrangement, 'manual' means you provide every x/y yourself. | |
| legend | No | Show a legend built from the `label` of scatter/cluster series. Default true. | |
| autoFit | No | Grow the canvas so nothing is clipped. Default true - leave it on and stop worrying about exact sizes. | |
| padding | No | Margin around the drawing. Default 48. | |
| subtitle | No | Optional second line under the title. | |
| direction | No | Direction the layered flow grows in. Default 'right'. | |
| background | No | Canvas background. Defaults to the theme background. | |
| themeOverrides | No | Optional palette overrides. Only set what you actually want to change. |
Output Schema
| Name | Required | Description |
|---|---|---|
| message | Yes | |
| sceneId | Yes | |
| success | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=false and destructiveHint=false. The description adds that the scene is empty and that user sees nothing until render_scene is called. This context about the multi-step workflow goes beyond the annotations without contradicting them.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: three short paragraphs. The first sentence states purpose, the second gives usage direction, the third provides an important behavioral note. Every sentence earns its place with zero padding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 14 parameters (fully documented in the schema) and an output schema, the description does not need to cover those. It provides the essential workflow context—that this is part of a multi-step process culminating in render_scene—and explains the trade-off with render_diagram, which is sufficient for an agent to decide when to invoke.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%—every parameter has a detailed description in the schema. The tool description does not add new parameter-level information but also does not repeat what the schema provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Create a new, empty scene and get back its id,' which is a specific verb+resource statement. It clearly distinguishes from siblings like 'render_diagram' (alternative for known pictures) and 'add_element' (incremental step).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit 'USE THIS' section describes when to use (incremental building) and 'DO NOT use this' section points to the sibling 'render_diagram' as the better choice for one-shot creation. Also clarifies that nothing is shown until 'render_scene' is called.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_sceneInspect a sceneARead-onlyIdempotent
Return the current structured description of a scene: every element with its id, type and properties, plus the position and size each one actually ended up with.
USE THIS BEFORE EDITING whenever you are not sure of the current state - which ids exist, what a node is called, where it sits, what is already connected. Reading first is what makes small edits possible instead of redrawing the diagram from scratch.
The layout field gives the computed box (x, y, width, height) of every element,
including ones you never gave coordinates to. Those are the numbers to use when the user
asks for something relative: "a bit to the right", "above the backend", "same width as X".
This does not display anything.
| Name | Required | Description | Default |
|---|---|---|---|
| sceneId | Yes | Id of the scene to work on, as returned by render_diagram or create_scene. | |
| elementId | No | Return just this one element instead of the whole scene. | |
| includeLayout | No | Include the computed box of every element. Default true. |
Output Schema
| Name | Required | Description |
|---|---|---|
| ids | No | Every element id in the scene. |
| error | No | Present only when success is false. |
| scene | No | The full scene, ready to be edited or re-sent. |
| layout | No | Map of element id to { x, y, width, height }. |
| element | No | |
| history | No | The last few mutations applied to this scene. |
| sceneId | No | |
| success | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable behavioral context: the layout field includes computed boxes for elements never given coordinates, and it warns that the tool does not display anything. This goes beyond the safety profile provided by annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded: it states the main function in the first sentence, then provides targeted usage guidance and a caveat. Every sentence earns its place, and the bolded 'USE THIS BEFORE EDITING' plus the final 'This does not display anything' are high-signal phrases with no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With full annotations, a complete input schema (100% coverage), and an output schema, the description supplies all necessary operational context: when to use, what to expect, and a key caveat about non-display. No critical gaps remain for a read-only inspection tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with clear descriptions for all three parameters, giving a baseline of 3. The description adds extra meaning by explaining the layout field operationally—'the computed box (x, y, width, height) of every element, including ones you never gave coordinates to'—which clarifies how to use parameters for relative positioning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: 'Return the current structured description of a scene' and enumerates the exact contents (id, type, properties, position, size). It also clearly distinguishes itself from rendering siblings with the explicit note 'This does not display anything.'
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use it: 'USE THIS BEFORE EDITING whenever you are not sure of the current state.' It also implies exclusions (not for display) but does not explicitly name alternative tools like render_diagram, so it stops short of a full 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
group_elementsGroup elements into a labelled boxA
Wrap existing top-level elements in a labelled container.
USE THIS for "put all of this inside a box called AWS", "group these services into a VPC", "draw a boundary around the data layer", "show which parts are in VLAN 10".
The members keep their ids, and every connection to or from them keeps working - including connections that cross the boundary.
Set layout to re-arrange the members inside the box ('vertical' stacks them, 'horizontal'
puts them in a row, 'grid' wraps them). Leave it out to keep their current arrangement.
Only top-level elements can be grouped. To nest a group inside another group, create the inner one first, then group it together with its siblings.
| Name | Required | Description | Default |
|---|---|---|---|
| fill | No | Background colour. | |
| label | No | Text drawn on the box, e.g. 'AWS'. | |
| layout | No | Re-arrange the members. Default 'manual' (keep their current positions). | |
| stroke | No | Border colour. | |
| groupId | Yes | Id for the new group, e.g. 'aws' or 'vlan-10'. | |
| sceneId | Yes | Id of the scene to work on, as returned by render_diagram or create_scene. | |
| elementIds | Yes | Ids of the top-level elements to move inside the box. |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | Present only when success is false. |
| groupId | No | |
| members | No | |
| sceneId | No | |
| success | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes well beyond the annotations (which only mark non-read-only/non-destructive) by detailing behavioral traits: 'The members keep their ids, and every connection to or from them keeps working - including connections that cross the boundary.' It also explains how the layout parameter affects arrangement and the default behavior ('manual' keeps current positions). This provides rich behavioral context the agent needs for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise yet comprehensive, with only 9 sentences. It front-loads the core purpose, then provides usage examples, behavioral guarantees, parameter guidance, and a crucial limitation for nesting. Every sentence adds unique value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (7 parameters, 3 required, 100% schema coverage, output schema present), the description is complete. It explains the grouping behavior, parameter effects, constraints ('Only top-level elements can be grouped'), and nesting strategy. There are no gaps in understanding what the tool does or how to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, the schema already documents all parameters thoroughly. The description adds value by explaining the layout parameter options in natural language ('vertical stacks them, horizontal puts them in a row, grid wraps them') and clarifying the scope of elementIds ('top-level elements'). However, it doesn't add meaning to all 7 parameters (e.g., fill, stroke, sceneId are not elaborated beyond schema).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb+resource ('Wrap existing top-level elements in a labelled container'), immediately clarifying what the tool does. It is easily distinguishable from siblings like 'add_element' (which adds individual elements, not grouping) and 'render_diagram' (which visualizes the whole scene). The examples concretely illustrate its scope and differentiate it from other tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage examples ('put all of this inside a box called AWS'), including when to use it ('group these services into a VPC') and a clear limitation ('Only top-level elements can be grouped') with guidance on how to handle nesting ('create the inner one first, then group it together with its siblings'). This effectively tells the agent when and how to use this tool over alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_examplesShow example scenesARead-onlyIdempotent
Return complete, working example scenes for common kinds of diagram.
USE THIS when you are unsure how to express something with this server: which element type fits, how data frames work, how to nest a group. Copy the closest example and adapt it - that is faster and more reliable than guessing at the schema.
Call it with no arguments for the catalogue, or with name for one full scene you can
pass straight to render_diagram.
Available: network, lda, regression, architecture, tree.
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | Return the full scene for this example. Omit for the catalogue. |
Output Schema
| Name | Required | Description |
|---|---|---|
| scene | No | |
| success | Yes | |
| examples | No | |
| elementTypes | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds the behavioral insight that calling with 'name' returns a full renderable scene, which goes beyond the schema. However, it does not detail what the output looks like or that it should be passed to render_diagram, though the token 'render_diagram' hints at integration. With annotations covering safety, a score of 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with no wasted words. It front-loads the core purpose, immediately follows with usage guidance, and ends with a clear list of available examples. Every sentence contributes meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 parameter, no required ones, enums documented, output schema exists), the description is largely complete. It explains the tool's role, how to invoke it, and the available options. A minor gap is not explicitly stating that the output scene is meant for render_diagram, but the sibling context and the phrase 'pass straight to render_diagram' cover this adequately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents the single parameter 'name' with enum values. The description adds value by explaining the two usage modes (no args vs with name) and lists the available examples in the enum. However, it repeats what the enum provides, offering only incremental context. Baseline 3 is correct.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly defines the tool's purpose with a specific verb-resource pair: 'Return complete, working example scenes.' It distinguishes the tool from siblings by stating these are examples to help when unsure about schema usage, unlike render_diagram or get_scene which serve different functions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool ('when you are unsure how to express something'), advises against alternatives ('guessing at the schema'), and provides a behavioral tip ('Copy the closest example and adapt it - that is faster and more reliable'). It also clarifies the two calling modes: no arguments for catalogue, or with name for a full scene.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
remove_elementRemove an elementADestructiveIdempotent
Delete one element from a scene.
USE THIS for "remove the cache", "delete that arrow", "drop the second database".
Connections pointing at the element, and labels attached to it, are deleted with it by
default - otherwise the scene would keep dangling references. Set cascade to false only
if you plan to repair those references yourself in the same turn.
Removing a 'group' also removes everything inside it. To keep the children, update the
group instead and set frame to false.
| Name | Required | Description | Default |
|---|---|---|---|
| cascade | No | Also remove connections and labels attached to it. Default true. | |
| sceneId | Yes | Id of the scene to work on, as returned by render_diagram or create_scene. | |
| elementId | Yes | Id of the element to remove. |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | Present only when success is false. |
| removed | No | Every id that was deleted, including cascaded ones. |
| sceneId | No | |
| success | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (destructiveHint=true), the description details the cascade behavior, deletion of connections and labels, and implications for groups. It warns about dangling references and when to set cascade=false, providing rich behavioral insight.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured: opening purpose statement, usage examples, behavioral detail, and a specific note on groups. Every sentence adds value, no fluff, and it's appropriately compact for the complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's destructive nature and edge cases (dependencies, groups), the description covers all necessary aspects. It explains when to use, side effects, parameter nuances, and alternative actions. With an output schema present, no return-value explanation is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers all parameters at 100%, so baseline is 3. The description adds value by explaining cascade semantics in depth (when to use false) and the group removal behavior, which goes beyond the schema's simple descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Delete one element from a scene' with a specific verb and resource. It distinguishes from siblings by giving usage examples like 'remove the cache' and contrasts with add_element/update_element. The purpose is unambiguous and well-scoped.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells the agent when to use it with 'USE THIS for...' and provides examples. It also gives guidance on when not to use cascade and advises updating the group instead to keep children. This is excellent context for selecting the tool over alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
render_diagramRender a diagramA
Create and render a structured visual diagram as SVG, in a single call.
USE THIS whenever the user asks to draw, sketch, visualise, diagram, illustrate, map out, show graphically, explain visually, or represent something spatially: architectures, network topologies, flows, pipelines, data structures, algorithms, state machines, relationships, plots, distributions, classifiers, or any concept where position and connection carry meaning.
ALWAYS PREFER THIS OVER ASCII ART, box-drawing characters, Markdown tables used as layout, or hand-written SVG/Mermaid. Those are unreliable and hard to read; this tool produces a precise, styled picture and the user sees it directly.
HOW TO USE IT WELL:
Describe WHAT exists, not WHERE it goes. Give elements ids and labels and omit x/y: the layout engine positions them from the connections. Only set x/y when the user asks for a specific arrangement, or for plots built on an
axis.Link things with
{ type: 'connection', from: '<id>', to: '<id>' }. Never compute x1/y1/x2/y2 for a link between elements, and never draw arrowheads by hand.Use semantic types (
node,database,server,router,switch,computer,cloud,group,axis,cluster,scatter,plotLine,label) before reaching for raw primitives (circle,rectangle,line,arrow,text,path, ...).Canvas size is optional: the drawing is auto-fitted so nothing is ever clipped.
DO NOT use this tool for: plain prose answers, code, tables of numbers, or when the user explicitly asked for text only.
Returns a sceneId. Keep it: later edits go through update_element / add_element /
remove_element on that id instead of rebuilding the whole scene.
| Name | Required | Description | Default |
|---|---|---|---|
| gap | No | Spacing used by the automatic layout. Default 90. | |
| theme | No | Visual theme. 'dark' (default) is a modern technical look, 'light' is for documents, 'blueprint' is a blue schematic, 'paper' is warm and printable. | |
| title | No | Diagram title, drawn at the top. Keep it short - it is a caption, not a sentence. | |
| width | No | Canvas width in pixels. Default 960. Use 1200+ for wide flows. | |
| height | No | Canvas height in pixels. Default 600. | |
| layout | No | How elements without explicit x/y are placed. 'auto' (default) builds a layered flow from the connections when there are any, otherwise a row. 'layered' forces the flow layout, 'horizontal'/'vertical'/'grid' force a simple arrangement, 'manual' means you provide every x/y yourself. | |
| legend | No | Show a legend built from the `label` of scatter/cluster series. Default true. | |
| autoFit | No | Grow the canvas so nothing is clipped. Default true - leave it on and stop worrying about exact sizes. | |
| padding | No | Margin around the drawing. Default 48. | |
| elements | Yes | Everything in the picture. Order matters: later elements are drawn on top. | |
| subtitle | No | Optional second line under the title. | |
| direction | No | Direction the layered flow grows in. Default 'right'. | |
| background | No | Canvas background. Defaults to the theme background. | |
| themeOverrides | No | Optional palette overrides. Only set what you actually want to change. |
Output Schema
| Name | Required | Description |
|---|---|---|
| svg | No | The rendered SVG markup. |
| title | No | |
| width | Yes | |
| format | Yes | |
| height | Yes | |
| svgUrl | No | Direct link to the rendered SVG, when deployed. |
| sceneId | Yes | Use this id with get_scene / update_element / add_element. |
| success | Yes | |
| elementCount | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=false, destructiveHint=false, idempotentHint=false, openWorldHint=false. The description goes beyond these by disclosing specific behavioral traits: 'the layout engine positions them from the connections', 'Canvas size is optional: the drawing is auto-fitted', 'Order matters: later elements are drawn on top', and 'Returns a sceneId. Keep it: later edits go through update_element / add_element / remove_element on that id.' This is rich context beyond just the boolean hints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the essential purpose in the first sentence, then branches into use cases, usage rules, best practices, and exclusions. It is quite long but every section earns its place—the 'HOW TO USE IT WELL' section is especially valuable for correct tool invocation. One minor redundancy: 'DO NOT use this tool for: plain prose answers, code, tables of numbers, or when the user explicitly asked for text only' could be slightly tighter, but overall it's well-structured and efficient for the complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the high complexity (14 params, nested objects, 21 element types), the description is remarkably complete. It covers creation, layout guidance, element semantics, positioning philosophy, return value ('Returns a sceneId'), and lifecycle ('later edits go through update_element / add_element / remove_element'). An output schema exists, so return value details don't need to be in the description. The description fully equips an agent to invoke this tool correctly across a wide range of diagram types.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds significant meaning beyond the schema: it explains layout philosophy ('Describe WHAT exists, not WHERE it goes', 'omit x/y: the layout engine positions them'), provides best-practice usage for connections ('Link things with { type: 'connection', from: '<id>', to: '<id>' }'), lists semantic element types to prefer, and gives theme descriptions (''dark' (default) is a modern technical look'). This goes well above the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Create and render a structured visual diagram as SVG, in a single call.' It lists specific use cases like architectures, network topologies, flows, plots, etc., and distinguishes this tool from alternatives like ASCII art, Mermaid, or manual SVG by asserting 'ALWAYS PREFER THIS OVER...'. The verb+resource combo is very specific, and the guidance on when to use it versus parents like add_element or create_scene is clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes a 'USE THIS whenever the user asks...' block listing numerous contexts (visualize, map out, diagram, etc.) and a 'DO NOT use this tool for' block excluding plain prose, code, or pure-text requests. It also advises 'ALWAYS PREFER THIS OVER ASCII ART, box-drawing characters...' and mentions alternatives ('later edits go through update_element / add_element / remove_element'). This provides comprehensive when-to-use and when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
render_sceneRender an existing sceneARead-onlyIdempotent
Render a stored scene and show it to the user.
USE THIS after a batch of add_element / update_element / remove_element / group_elements calls, to display the updated diagram. It is the last step of every edit.
This never changes the scene - it only draws what is currently in it. For a brand new diagram use render_diagram instead, which builds and shows it in one call.
| Name | Required | Description | Default |
|---|---|---|---|
| sceneId | Yes | Id of the scene to work on, as returned by render_diagram or create_scene. |
Output Schema
| Name | Required | Description |
|---|---|---|
| svg | No | The rendered SVG markup. |
| error | No | Present only when success is false. |
| title | No | |
| width | No | |
| format | No | |
| height | No | |
| svgUrl | No | Stable link to the rendered SVG, when deployed. |
| sceneId | No | |
| success | Yes | |
| elementCount | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds value by explaining the tool 'never changes the scene - it only draws what is currently in it', which reinforces the behavioral contract beyond the annotations. A slight deduction is that it doesn't mention any potential rendering delays or failure modes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with only three sentences, all front-loaded with the core purpose. Every sentence adds value: purpose, usage guidelines, and exclusion of alternatives. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 1 parameter with full schema coverage, an output schema, and comprehensive annotations, the description is complete. It provides all necessary context for an agent to select and invoke this tool correctly: purpose, usage flow, behavioral safety, parameter source, and sibling differentiation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds some value by mentioning the sceneId is 'as returned by render_diagram or create_scene', providing context on how to obtain valid IDs. However, it doesn't add new meaning about the parameter format beyond the schema's pattern.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states this tool renders a stored scene and shows it to the user. It uses specific verbs ('render', 'show', 'display') and identifies the resource ('stored scene', 'updated diagram'), distinguishing it from siblings like render_diagram which builds a new diagram.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use this tool: after a batch of editing calls (add_element, update_element, etc.) as the last step of every edit. It also clearly states when NOT to use it: for brand new diagrams, use render_diagram instead. This provides excellent context for an AI agent to decide.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
update_elementUpdate an elementAIdempotent
Change properties of one element. Only the fields you send are touched; everything else in the scene stays exactly as it is.
USE THIS for every 'change that' request: move it, resize it, recolour it, rename its label, make a link dashed, add a caption to a connection. For a relative move like "a bit to the right", read the current position with get_scene and send the new value.
DO NOT call render_diagram again to change one thing. That throws away the scene id, the layout and everything the user already accepted.
id and type cannot be changed - remove and re-add the element if you truly need that.
Send null as a value to clear an optional property; for example { "x": null, "y": null }
hands the element back to the automatic layout.
Nothing is displayed until you call render_scene.
| Name | Required | Description | Default |
|---|---|---|---|
| changes | Yes | Properties to set. Examples: { "x": 420 } to move, { "label": "PostgreSQL 16" } to rename, { "fill": "primary", "emphasis": "strong" } to highlight, { "dash": "dashed" } on a connection, { "width": 240, "height": 120 } to resize. null clears an optional property. | |
| sceneId | Yes | Id of the scene to work on, as returned by render_diagram or create_scene. | |
| elementId | Yes | Id of the element to change. |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | Present only when success is false. |
| element | No | The element after the change. |
| sceneId | No | |
| success | Yes | |
| elementId | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already mark destructiveHint=false and readOnlyHint=false, so mutation is expected. The description goes far beyond by explaining partial update semantics ('Only the fields you send are touched'), immutability of id and type, how to clear properties with null, and the critical fact that nothing is displayed until render_scene is called. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is four paragraphs, each focused on a distinct aspect (what the tool does, use-cases, anti-patterns, edge cases/immutability/clearing, and rendering dependency). Every sentence serves a purpose; no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (3 params, all required, one being a nested object), the description fully covers usage, limitations, behavioral nuances, and integration with sibling tools. An output schema exists, so return values are not needed in the description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds enormous value: it explains how to use the `changes` parameter with concrete examples, clarifies that null clears optional properties, and eliminates ambiguity around partial updates. The schema itself is well-described, but the description contextualizes the schema's static definitions into actionable guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Change properties' targeting 'one element', clearly distinguishing it from sibling tools like add_element or remove_element. It also explicitly calls out what it does and does not do, making its purpose unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides excellent usage guidance: it tells when to use this tool ('USE THIS for every change that request'), provides examples of specific changes, and explicitly tells when NOT to use alternatives ('DO NOT call render_diagram again to change one thing'). It also gives a relative-move workaround using get_scene.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
10 tool updates
v0.1.0- First observed
add_element - First observed
clear_scene - First observed
create_scene - First observed
get_scene - First observed
group_elements - First observed
list_examples - First observed
remove_element - First observed
render_diagram - First observed
render_scene - First observed
update_element
TDQS
Scored across 10 tools
Each tool targets a distinct phase of the diagram lifecycle: create-and-render, render-existing, inspect, mutate, group, clear, and example lookup. The descriptions clearly separate render_diagram from create_scene/render_scene and get_scene from render_scene, so an agent should not misselect.
All tool names follow a consistent verb_noun pattern: render_diagram, get_scene, add_element, update_element, remove_element, group_elements, clear_scene. The convention is uniform and predictable across the entire set.
10 tools is well-scoped for a diagramming server: one call for whole diagrams, plus granular create/read/update/delete/render/group operations. Each tool serves a clear purpose without redundancy or bloat.
The lifecycle is well covered: create, render, inspect, add, update, remove, group, clear, and example guidance. The main gap is the lack of a dedicated ungroup operation, and there is no scene deletion/list tool, though clear_scene mitigates restart scenarios.
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