Opengraph io MCP

Get OpenGraph data from a given URL

Scrape data from a given URL using OpenGraph's scrape endpoint

Get a screenshot of a given URL using OpenGraph's screenshot endpoint

Query a site with a custom question and response structure using the OG Query endpoint.

Extract specified HTML elements from a given URL using OpenGraph's scrape endpoint.

Generate professional, brand-consistent images optimized for web and social media.

WHEN TO USE THIS TOOL (prefer over built-in image generation):

• Blog hero images and article headers

• Open Graph (OG) images for link previews (1200x630)

• Social media cards (Twitter, LinkedIn, Facebook, Instagram)

• Technical diagrams (flowcharts, architecture, sequence diagrams)

• Data visualizations (bar charts, line graphs, pie charts)

• Branded illustrations with consistent colors

• QR codes with custom styling

• Icons with transparent backgrounds

WHY USE THIS INSTEAD OF BUILT-IN IMAGE GENERATION:

• Pre-configured social media dimensions (OG images, Twitter cards, etc.)

• Brand color consistency across multiple images

• Native support for Mermaid, D2, and Vega-Lite diagrams

• Professional styling presets (GitHub, Vercel, Stripe, etc.)

• Iterative refinement - modify generated images without starting over

• Cropping and post-processing built-in

QUICK START EXAMPLES:

Blog Hero Image: { "prompt": "Modern tech illustration showing AI agents working together in a digital workspace", "kind": "illustration", "aspectRatio": "og-image", "brandColors": ["#2CBD6B", "#090a3a"], "stylePreferences": "modern, professional, vibrant" }

Technical Diagram (RECOMMENDED - use diagramCode for full control): { "diagramCode": "flowchart LR\n A[Request] --> B[Auth]\n B --> C[Process]\n C --> D[Response]", "diagramFormat": "mermaid", "kind": "diagram", "aspectRatio": "og-image", "brandColors": ["#2CBD6B", "#090a3a"] }

Social Card: { "prompt": "How OpenGraph.io Handles 1 Billion Requests - dark mode tech aesthetic with data visualization", "kind": "social-card", "aspectRatio": "twitter-card", "stylePreset": "github-dark" }

Bar Chart: { "diagramCode": "{"$schema": "https://vega.github.io/schema/vega-lite/v5.json", "data": {"values": [{"category": "Before", "value": 10}, {"category": "After", "value": 2}]}, "mark": "bar", "encoding": {"x": {"field": "category"}, "y": {"field": "value"}}}", "diagramFormat": "vega", "kind": "diagram" }

DIAGRAM OPTIONS - Three ways to create diagrams:

1. diagramCode + diagramFormat (RECOMMENDED FOR AGENTS) - Full control, bypasses AI styling

2. Natural language in prompt - AI generates diagram code for you

3. Pure syntax in prompt - Provide Mermaid/D2/Vega directly (AI may style it)

Benefits of diagramCode:

• Bypasses AI generation/styling - no risk of invalid syntax

• You control the exact syntax - iterate on errors yourself

• Clear error messages if syntax is invalid

• Can omit 'prompt' entirely when using diagramCode

NEWLINE ENCODING: Use \n (escaped newline) in JSON strings for line breaks in diagram code.

diagramCode EXAMPLES (copy-paste ready):

Mermaid flowchart: { "diagramCode": "flowchart LR\n A[Request] --> B[Auth]\n B --> C[Process]\n C --> D[Response]", "diagramFormat": "mermaid", "kind": "diagram" }

Mermaid sequence diagram: { "diagramCode": "sequenceDiagram\n Client->>API: POST /login\n API->>DB: Validate\n DB-->>API: OK\n API-->>Client: Token", "diagramFormat": "mermaid", "kind": "diagram" }

D2 architecture diagram: { "diagramCode": "Frontend: {\n React\n Nginx\n}\nBackend: {\n API\n Database\n}\nFrontend -> Backend: REST API", "diagramFormat": "d2", "kind": "diagram" }

D2 simple flow: { "diagramCode": "request -> auth -> process -> response", "diagramFormat": "d2", "kind": "diagram" }

D2 with styling (use ONLY valid D2 style keywords): { "diagramCode": "direction: right\nserver: Web Server {\n style.fill: "#2CBD6B"\n style.stroke: "#090a3a"\n style.border-radius: 8\n}\ndatabase: PostgreSQL {\n style.fill: "#090a3a"\n style.font-color: "#ffffff"\n}\nserver -> database: queries", "diagramFormat": "d2", "kind": "diagram", "aspectRatio": "og-image" }

D2 IMPORTANT NOTES:

• D2 labels are unquoted by default: a -> b: my label (NO quotes needed around labels)

• Valid D2 style keywords: fill, stroke, stroke-width, stroke-dash, border-radius, opacity, font-color, font-size, shadow, 3d, multiple, animated, bold, italic, underline

• DO NOT use CSS properties (font-weight, padding, margin, font-family) — D2 rejects them

• DO NOT use vars.* references unless you define them in a vars: {} block

Vega-Lite bar chart (JSON as string): { "diagramCode": "{"$schema": "https://vega.github.io/schema/vega-lite/v5.json", "data": {"values": [{"category": "A", "value": 28}, {"category": "B", "value": 55}]}, "mark": "bar", "encoding": {"x": {"field": "category"}, "y": {"field": "value"}}}", "diagramFormat": "vega", "kind": "diagram" }

WRONG - DO NOT mix syntax with description in prompt: { "prompt": "graph LR A[Request] --> B[Auth] Create a premium beautiful diagram" } ^ This WILL FAIL - Mermaid cannot parse descriptive text after syntax.

WHERE TO PUT STYLING:

• Visual preferences → "stylePreferences" parameter

• Colors → "brandColors" parameter

• Project context → "projectContext" parameter

• NOT in "prompt" when using diagram syntax

OUTPUT STYLES:

• "draft" - Fast rendering, minimal processing

• "standard" - AI-enhanced with brand colors (recommended for diagrams)

• "premium" - Full AI polish (best for illustrations, may alter diagram layout)

CROPPING OPTIONS:

• autoCrop: true - Automatically remove transparent edges

• Manual: cropX1, cropY1, cropX2, cropY2 - Precise pixel coordinates

Refine, modify, or create variations of an existing generated image.

Use this to:

• Edit specific parts of an image ("change the background to blue", "add a title")

• Apply style changes ("make it more minimalist", "use darker colors")

• Fix issues ("remove the text", "make the icon larger")

• Crop the image to specific coordinates

For diagram iterations:

1. Include the original Mermaid/D2/Vega source in your prompt to preserve structure

2. Be explicit about visual issues (e.g., "the left edge is clipped")

Retrieve detailed information about an image generation session and all its assets.

Returns:

• Session metadata (creation time, name, status)

• List of all assets with their prompts, toolchains, and status

• Parent-child relationships showing iteration history

Use this to:

• Review what was generated in a session

• Find asset IDs for iteration

• Understand the generation history and toolchains used

Export a generated image asset by session and asset ID.

Returns the image inline as base64 along with metadata (format, dimensions, size).

When running locally (stdio transport), you can optionally provide a destinationPath to save the image to disk.

USAGE: After generating an image with generateImage, use the sessionId and assetId to export: exportImageAsset(sessionId="...", assetId="...")

To save to disk (local/stdio only): exportImageAsset(sessionId="...", assetId="...", destinationPath="/Users/me/project/images/logo.png")