poster-design-mcp
poster-design-mcp
Ein MCP-Server, der Geschäftsposter gestaltet. Bitten Sie Ihren KI-Client in einfacher Sprache um ein Poster, und er schreibt eine echte PNG- oder JPG-Datei auf die Festplatte – in Druckauflösung, gestaltet von einem Designsystem statt nach Bauchgefühl.
Jedes Poster auf dieser Seite wurde mit einem einzigen Tool-Aufruf erzeugt. Mehr in Galerie.
Inhalt
Related MCP server: Canvora MCP
Was es tut
Die meisten KI-Bildwerkzeuge malen ein Poster, daher ist die Schrift verschmiert und die Telefonnummer erfunden. Dieses hier setzt ein Poster in Typografie um. Die Schlagzeile ist echter Text in einer echten Schrift, der Preis ist der Preis, den Sie angegeben haben, und die Ausgabe erfolgt auf exakten Pixelmaßen – 2480×3508 für A4 bei 300 dpi, druckfertig.
Sie erhalten:
Vier Layouts, abgeleitet von vier Referenzpostern – Veranstaltungen, Markenbotschaften, Produktanzeigen und Meilensteinzahlen.
Eine Palette aus einem Hex-Code. Geben Sie Ihre Markenfarbe an; Feld, Textfarbe, Akzentfarbe und Muster-Skala werden daraus abgeleitet, wobei die Textfarbe anhand des Kontrastverhältnisses gewählt wird, damit Text lesbar bleibt.
Automatisch eingepasste Anzeigetypografie. Die Schlagzeile wächst, bis die längste Zeile den Rand berührt, und stoppt dann. Sie wählen die Zeilenumbrüche; der Server wählt die Größe.
Echte Foto-Verarbeitung – randlose Beschnitte, Fokuspunkte, Verlaufs-Überblendungen, damit Typografie nie direkt auf einem Bild sitzt.
Druck- oder Social-Media-Formate, PNG oder JPG, auf Anfrage.
So funktioniert es
your prompt
│
▼
AI client ──MCP/stdio──▶ poster-design-mcp
│
│ 1. pick a template (src/templates/*.js)
│ 2. derive the palette from brandColor
│ 3. build an HTML + CSS document
▼
headless Chrome ── screenshot ──▶ poster.png
│
▼
~/Documents/Poster Designs/Das Designsystem sind Zahlen, keine Stimmungen. Zwölf Regeln wurden von vier Referenzpostern abgelesen und in
src/design-system.jsals Werte geschrieben, die die Vorlagen tatsächlich konsumieren – Rand bei 6,8 % der Breite, Hero-Schrift zwischen 0,055 und 0,155 der Breite, Zeilenabstand 0,90, Laufweite −0,03em. Der Text in DESIGN-PRINCIPLES.md und die gerenderten Pixel lesen aus denselben Konstanten, sodass die Dokumentation nicht von der Ausgabe abweichen kann.Eine Vorlage verwandelt Ihren Text in ein Dokument. Jede der vier Vorlagen (
src/templates/) ist eine Funktion: Inhalt rein, HTML und CSS raus. Sie platziert die Bänder, legt die Typografie-Rollen fest, erzeugt das dekorative Muster aus einem Seed und bettet jedes lokale Bild als Data-URI ein.Headless Chrome übernimmt das Layout. Das Rendern in einem Browser bringt echtes Textlayout – Schrift-Fallback, Silbentrennung,
object-fit-Beschneidung,mix-blend-mode: multiply-Buchstabenformen – und die Auto-Fit-Schleife misst die tatsächlich gesetzte Schlagzeile und skaliert sie neu, bis sie das Satzmaß füllt. Die Seite wird dann mitdeviceScaleFactorin den exakten Ausgabemaßen als Screenshot aufgenommen, sodass ein A4 mit 300 dpi tatsächlich 2480×3508 Pixel groß ist statt hochskaliert.Die Datei kommt in den Dokumente-Ordner. Ein MCP-Server wird von seinem Client gestartet und hat kein sinnvolles Arbeitsverzeichnis. Daher werden Ergebnisse an einem auffindbaren Ort gespeichert, und das Werkzeug gibt den Pfad zurück.
Es wird nichts hochgeladen. Kein API-Schlüssel, kein Netzwerkaufruf – die gesamte Pipeline läuft auf Ihrem Rechner.
Installation
Erfordert Node 20+ und eine Chrome-/Chromium-Binärdatei.
git clone https://github.com/suprisedr/poster-design-mcp.git
cd poster-design-mcp
npm installnpm install zieht Puppeteer nach, das normalerweise sein eigenes Chrome herunterlädt. Falls das nicht geschah oder Sie den Download übersprungen haben:
npx puppeteer browsers install chromeChrome wird in dieser Reihenfolge gesucht: $POSTER_CHROME_PATH → das von Puppeteer verwaltete Chrome → Google Chrome oder Chromium an den üblichen Systemorten. Um auf eine bestimmte Binärdatei zu zeigen:
export POSTER_CHROME_PATH="/Applications/Google Chrome.app/Contents/MacOS/Google Chrome"Prüfen Sie, ob es funktioniert:
npm testDas startet den Server über stdio, übt jedes Werkzeug aus und prüft die Token-Budgets. Dann, für etwas zum Anschauen:
npm run demoJe ein Poster pro Vorlage in ./examples.
Mit Ihrem KI-Client verbinden
Claude Code
claude mcp add poster-design -- node /absolute/path/to/poster-design-mcp/src/server.jsClaude Desktop oder eine beliebige MCP-Konfigurationsdatei
Fügen Sie zu mcpServers hinzu (unter macOS liegt die Konfiguration von Claude Desktop unter ~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"poster-design": {
"command": "node",
"args": ["/absolute/path/to/poster-design-mcp/src/server.js"],
"env": {
"POSTER_BASE_DIR": "/absolute/path/to/poster-design-mcp"
}
}
}
}Verwenden Sie absolute Pfade – der Client startet den Server aus einem unvorhersehbaren Verzeichnis.
Umgebungsvariable | Bedeutung |
| Wogegen relative Bild- und Ausgabepfade aufgelöst werden |
| Verschiebt den Standard-Ausgabeordner von |
| Explizite Chrome-/Chromium-Binärdatei |
Starten Sie den Client neu, und die vier Werkzeuge erscheinen.
Verwendung
Sobald verbunden, fragen Sie einfach:
Erstell mir ein A4-Poster für Golden Crust Bakery – handgefertigte Brote und Gebäck, 123 Maple Street, geöffnet 6–18 Uhr Dienstag bis Sonntag. Warmes Orange, nimm dieses Brotfoto.
Der Client wählt eine Vorlage und ruft create_poster auf. Unter der Haube ist das ein einziges JSON-Payload:
{
"template": "photo-overlay",
"brandColor": "#0F918F",
"size": "instagram-portrait",
"format": "jpg",
"content": {
"brandName": "Guski",
"logoBadge": true,
"headline": "You love it,\nwe cover it",
"subhead": "Cover that changes everything",
"cta": { "label": "Get a quote", "phone": "061 306 081" },
"legal": "Guski Short Term Insurance Ltd. Reg. No. 89/524.",
"image": "examples/sample-photo.jpg",
"imageFocus": "50% 45%"
}
}Es gibt eine knappe Zeile zurück – path | 2480x3508 png | 191KB | ... – und die Datei liegt auf der Festplatte.
Zwei Dinge, die Sie beim Verfassen des Texts wissen sollten:
Verwenden Sie
\nin einer Schlagzeile, um zu bestimmen, wo sie umbricht. Der Generator skaliert die Schrift so, dass sie den von Ihnen geschriebenen Zeilenfall füllt – der Umbruch ist also eine Designentscheidung, und zwar Ihre.Halten Sie es kurz. Schlagzeile 2–5 Wörter, Untertitel unter 45 Zeichen, Fließtext zwei Zeilen. Die Schriftskala basiert auf extremem Kontrast; langer Text lässt ein Poster wie ein Flugblatt aussehen.
Galerie
Echte Ausgabe, jeweils ein einziger Tool-Aufruf.
| Dasselbe Poster ohne Foto. Lassen Sie das |
|
|
|
|
Die Beispielbilder sind Platzhaltergrafiken zur
Die Tool-Liste umfasst ~990 Tokens statt ~2.600. Sie enthält Namen, Optionen und Feld-Namen; die Feld-Bedeutungen wurden in
list_poster_templatesausgelagert, das einmal von den Aufrufern aufgerufen wird, die es benötigen.list_poster_templatesgibt ~390 Tokens statt ~1.700 zurück; übergib einetemplate-ID, um ein Layout statt aller vier zu erhalten.get_design_principlesgibt ~280 Tokens statt ~1.700 zurück;detail: truefür die vollständige Begründung.Ergebnisse sind eine knappe Zeile statt hübsch formatiertem JSON.
Das Inline-Vorschaubild (200–500 Tokens pro Poster) ist über
preview: trueopt-in. Die Datei liegt in Documents, wo man sie sich besser ansehen kann.
npm test prüft das Budget der Tool-Liste, sodass eine Regression in der teuersten Oberfläche den Build scheitern lässt.
Entwicklung
npm run demo # one poster per template into ./examples
npm test # boots the server over stdio, exercises every tool, checks the token budgetssrc/
server.js MCP wiring: tool list, dispatch, terse results
poster.js orchestration — template → HTML → render → write
design-system.js the twelve rules as numbers: palettes, type scale, layout ratios
templates/ one file per layout, each content → { body, css }
lib/
html.js document assembly and escaping
pattern.js seeded decorative pattern generation
media.js image resolution and data-URI inlining
render.js headless Chrome lifecycle and screenshotting
paths.js output directory resolutionsaveHtml: true schreibt den HTML-Quelltext neben das Bild – das ist der schnellste Weg, um zu sehen, warum etwas so angeordnet wurde. seed macht das Muster und den Jitter reproduzierbar.
Fehlerbehebung
Symptom | Lösung |
|
|
Tools erscheinen nicht im Client | Verwende einen absoluten Pfad zu |
Bilder werden nicht gerendert | Lokale Pfade werden relativ zu |
Poster wird an unerwartetem Ort geschrieben | Standard ist |
Überschrift läuft über | Füge eigene |
Ersteller
Erstellt von Suprise Nkosi.
Facebook — facebook.com/suprise.nkosi.524
GitHub — @suprisedr
Issues und Pull-Requests sind willkommen.
Lizenz
MIT — siehe LICENSE.
Available Tools
4 toolscreate_posterB
Render a business poster to a PNG/JPG in ~/Poster Designs. Auto-fitted display type, band structure, one accent colour, protected legibility. Returns the file path.
| Name | Required | Description | Default |
|---|---|---|---|
| seed | No | Same seed = same pattern/jitter. | |
| size | No | Default a4-print. | |
| fonts | No | Roles display/text. grotesque|humanist|black|geometric|serif|mono or a CSS font-family. | |
| width | No | Custom px width (with height). | |
| format | No | Default png. | |
| height | No | ||
| content | Yes | Copy and imagery. Fields (* = required): banded-editorial(headline*, subhead, details, eyebrow, badge, partners, image, imageFocus, patternDensity); chromatic-type(word*, tagline, brandLine, overlap, jitter, shards, bleed, fill); photo-overlay(headline*, subhead, cta, brandName, logo, logoBadge, legal, image*, imageFocus, scrim, treatment); stat-hero(headline*, subhead, figure*, labelTop, labelBottom, body, tag, image, cutout, logo, figureStyle). Field meanings: list_poster_templates. Use \n in a headline to set the rag. | |
| palette | No | festival-block|prism-glass|night-drive|signal-teal|mono-ink or a hex. Beats brandColor. | |
| preview | No | Return an inline thumbnail to look at. Costs tokens; default false. | |
| quality | No | JPEG quality 1-100, default 92. | |
| filename | No | Name without extension. | |
| saveHtml | No | Also write the HTML source. | |
| template | Yes | ||
| outputDir | No | Absolute path, or a subfolder of ~/Poster Designs (the default). | |
| brandColor | No | Brand hex; a full palette is derived from it. | |
| outputPath | No | Exact output path. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral disclosure burden. It does transparently mention file output formats, the output directory, and the return value, and it adds design automation traits such as auto-fitted display type and protected legibility. However, it does not mention overwrite behavior, permissions, or other side effects beyond writing the poster file.
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: purpose, key output behavior, and return value appear in three short sentences. The design-behavior clause is useful but uses some jargon (e.g., 'band structure', 'protected legibility') that is not explained; still, there is minimal waste.
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 (16 parameters, nested content objects, four templates), the description is brief but the schema compensates with rich parameter documentation. It covers the output path and basic design behavior, but it lacks guidance on when to choose this tool over create_poster_variants and does not summarize template requirements in the main 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 description coverage is high (88%), and the schema already documents parameter meanings, defaults, enums, and nested template-specific fields. The description adds no parameter-level detail beyond general design intent, so the baseline 3 applies because the schema carries most of the semantic weight.
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 states a specific action ('Render a business poster to a PNG/JPG'), a target location ('~/Poster Designs'), and the return value ('Returns the file path'). It clearly identifies this as a poster-generation tool, though it does not explicitly distinguish it from the sibling create_poster_variants.
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?
No guidance is given on when to use this tool versus create_poster_variants, or how it relates to list_poster_templates and get_design_principles. Usage context is only implied by the phrase 'Render a business poster' and the parameter schema; there are no exclusions or alternative-selection hints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
create_poster_variantsA
Same message across several templates/palettes in one call, to compare directions.
| Name | Required | Description | Default |
|---|---|---|---|
| content | Yes | Shared copy; fields as in create_poster. | |
| template | No | Fallback when a variant names none. | |
| variants | Yes | Up to 4 override objects: template, palette, brandColor, seed, fonts, filename or extra content fields. Any create_poster option may also be set at the top level as a shared default. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the behavioral disclosure burden. It accurately communicates the key batch behavior (several variants in one call) and the comparison intent, but it does not mention return format, failure modes, or any side effects. This is adequate but not rich.
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?
One concise sentence that delivers the core value proposition without wasted words. It is front-loaded with the batch concept and ends with the purpose, making it easy to scan. Slightly more explicit structure would improve it, but it is appropriately sized.
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?
For a 3-parameter tool with nested objects and no output schema, the description gives enough context to select the tool and understand its general purpose. However, an agent would still need to rely on the schema for override semantics and would not know what the response contains. Functional for selection, incomplete for full invocation confidence.
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 structured schema already documents content, template fallback behavior, and variant overrides. The description adds the conceptual 'same message across templates' framing but no additional parameter-level detail beyond what the schema provides.
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 conveys that the tool generates the same message across multiple templates/palettes in a single call, which differentiates it from the singular create_poster sibling. It lacks an explicit verb but the resource and batch scope are 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 phrase 'to compare directions' provides a clear context for when this tool is appropriate: when the user wants to explore multiple visual directions at once. It does not explicitly name alternatives or exclusions, but the batch comparison purpose is evident from the description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_design_principlesA
The design rules, type scale and layout ratios the generator applies. For writing copy that fits, or critiquing output.
| Name | Required | Description | Default |
|---|---|---|---|
| detail | No | Full rationale per rule instead of one line each. | |
| brandColor | No | Also return the palette derived from this hex. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of explaining behavior. It communicates that this is a read-oriented informational tool returning rules, type scale, and ratios, but it does not explicitly state the return format, side effects, or any constraints such as whether brandColor changes the returned rules.
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?
Two short sentences with no filler. The first sentence establishes what the tool returns and the second gives actionable usage guidance, so every sentence earns its place.
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?
For a simple getter with two optional parameters and no output schema, the description names the key return content and intended use. It would be more complete with a sentence about what the response contains, but for this complexity the coverage is adequate.
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 schema already documents both parameters. The description adds no parameter-level meaning, but the baseline of 3 applies because the schema handles the heavy lifting.
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 identifies the resource as the generator's design rules, type scale, and layout ratios, and states its intended use in writing or critiquing copy. It does not explicitly contrast with sibling tools, but the subject matter is obviously distinct from template listing and poster creation.
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 second sentence gives explicit use cases: 'For writing copy that fits, or critiquing output.' It does not state exclusions or point to alternatives, so it stops short of a 5, but the situational context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_poster_templatesA
Field guide for the poster layouts, plus palettes, sizes and fonts. Pass a template id for that one layout only. Call once before create_poster if unsure.
| Name | Required | Description | Default |
|---|---|---|---|
| template | No | Just this layout, in full. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It implies read-only behavior through 'field guide' and describes the optional filter behavior ('Pass a template id for that one layout only'), which adds useful context. However, it never explicitly states that the operation is read-only, nor does it describe the default return behavior when no template is passed.
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?
Three short sentences with no fluff. The purpose is front-loaded, the optional parameter behavior is stated in the second sentence, and the workflow guidance is in the third. Every sentence earns its place.
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?
For a tool with one optional parameter and no output schema, the description adequately covers what the tool returns, the filtering behavior, and when to call it. The main gap is the absence of any distinction from the sibling get_design_principles, which could leave an agent uncertain which reference tool to select.
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 schema already documents the template parameter. The description adds only 'for that one layout only,' which reinforces the schema's 'Just this layout, in full' but does not materially extend it. This is the appropriate baseline when the schema handles parameter documentation.
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 identifies the tool as a reference for poster layouts, palettes, sizes, and fonts, which is a specific resource and content scope. It does not explicitly use the verb 'list' but the name and 'field guide' make the informational purpose clear. It distinguishes itself from create_poster by placement in workflow, though it does not differentiate from sibling get_design_principles.
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 gives explicit contextual guidance: 'Call once before create_poster if unsure.' This tells the agent when to use the tool and provides a workflow cue. It does not state when not to use it or explicitly compare to get_design_principles, so it stops short of full alternative routing.
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.
4 tool updates
v1.1.0- First observed
create_poster - First observed
create_poster_variants - First observed
get_design_principles - First observed
list_poster_templates
TDQS
Scored across 4 tools
Each tool has a clearly distinct purpose: discovering templates, learning design principles, creating a single poster, and creating variants. Even the two create tools are distinguishable by single vs. batch behavior.
All tool names follow the same verb_noun snake_case pattern: list_, get_, create_, create_. The naming is predictable and indicates the action and resource clearly.
Four tools is well-scoped for a poster design server, covering discovery, guidance, creation, and variation. The set feels intentionally minimal rather than bloated or incomplete.
The core workflow is covered: browse templates, learn design rules, create a poster, and generate variants. Minor gaps exist around modifying or deleting generated posters, but these are not clearly required for the server's stated purpose.
Maintenance
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