Fetch Open Graph metadata, HTML-inferred tags, and hybrid social preview data for any URL via the OpenGraph.io API (v3). Returns og:title, og:description, og:image, og:type, favicon, and more, merged from three sources: raw Open Graph tags (openGraph), HTML-inferred fallbacks (htmlInferred), and a best-of hybrid (hybridGraph). Use hybridGraph as your primary source — it fills gaps automatically.

Pick the right tool: getOgData → Open Graph tags, social preview metadata (title, description, image, favicon) getOgMarkdown → Clean readable text / article prose — ideal for feeding into an LLM getOgScrapeData → Raw HTML — use when you need to do your own parsing or link extraction getOgExtract → Targeted elements by tag (html_elements) or named CSS selectors (selectors) getOgScreenshot → Visual capture of a page as an image getOgQuery → Natural-language question answered from page content (100–200 credits/request)

Scrape and return the raw HTML of a URL via the OpenGraph.io API (v3). Returns the complete page HTML — use this when you need to do your own parsing, extract all links, inspect the DOM structure, or feed raw markup into another tool or model. The text response includes the first 3 000 characters; the full HTML is in the structured html field.

For JS-heavy or single-page applications set full_render: true to guarantee JavaScript execution before the HTML is captured. For most sites, the default auto_render handles this automatically.

Pick the right tool: getOgData → Open Graph tags, social preview metadata (title, description, image, favicon) getOgMarkdown → Clean readable text / article prose — ideal for feeding into an LLM getOgScrapeData → Raw HTML — use when you need to do your own parsing or link extraction getOgExtract → Targeted elements by tag (html_elements) or named CSS selectors (selectors) getOgScreenshot → Visual capture of a page as an image getOgQuery → Natural-language question answered from page content (100–200 credits/request)

Capture a screenshot of any URL via the OpenGraph.io API (v3). Supports full-page or viewport captures, custom viewport dimensions, dark mode, image format/quality control, cookie-banner dismissal, and CSS selector-based element targeting or exclusion.

Returns a screenshotUrl — a hosted URL pointing to the screenshot image file, not inline image data. Use this URL directly in a browser, an tag, or pass it to another tool.

Pick the right tool: getOgData → Open Graph tags, social preview metadata (title, description, image, favicon) getOgMarkdown → Clean readable text / article prose — ideal for feeding into an LLM getOgScrapeData → Raw HTML — use when you need to do your own parsing or link extraction getOgExtract → Targeted elements by tag (html_elements) or named CSS selectors (selectors) getOgScreenshot → Visual capture of a page as an image getOgQuery → Natural-language question answered from page content (100–200 credits/request)

Ask a natural-language question about the content of any URL and receive an AI-generated answer via the OpenGraph.io API. Optionally pass a responseStructure schema to extract structured data. Note: uses 100 API credits per request (or 200 with a large model). Query API remains on v1.1 until the billing path check is updated for v3.

Extract specific content from any URL via the OpenGraph.io API (v3). Two modes — choose based on what you need:

Mode 1 — Tag-based (html_elements): pass an array of HTML tag names, e.g. ['h1','h2','p','a']. The API collects all matching elements and joins their text into a single concatenatedText string. Best for bulk content extraction where you want all headings, paragraphs, or links as one block of text.

Mode 2 — Selector-based (selectors): pass a CSS selector map where each key is your chosen label and each value is a CSS selector, e.g. { "title": "article h1", "price": ".price-box .price", "sku": "#product-sku" }. The API returns a data object keyed by those labels — ideal for structured scraping of specific named fields.

Response shape by mode:

• html_elements only → { concatenatedText }

• selectors only → { data, concatenatedText }

• Both provided → { data, concatenatedText }

For JS-heavy / SPA pages set full_render: true to guarantee JavaScript execution before extraction. Use wait_for_selector when content loads asynchronously.

Pick the right tool: getOgData → Open Graph tags, social preview metadata (title, description, image, favicon) getOgMarkdown → Clean readable text / article prose — ideal for feeding into an LLM getOgScrapeData → Raw HTML — use when you need to do your own parsing or link extraction getOgExtract → Targeted elements by tag (html_elements) or named CSS selectors (selectors) getOgScreenshot → Visual capture of a page as an image getOgQuery → Natural-language question answered from page content (100–200 credits/request)

Convert any URL's HTML into clean Markdown via the OpenGraph.io API (v3 markdown endpoint). Strips navigation, ads, and boilerplate by default — the result is main-content prose, headings, links, and images ready to read or feed into another model. Use include_tags / exclude_tags to target or remove specific page sections.

IMPORTANT — JavaScript-heavy pages: the v3 smart defaults (auto_render) do NOT apply to the markdown pipeline. If the target URL is an SPA or requires JS execution, you must explicitly set full_render: true to get rendered HTML before conversion. Without it, you will receive the raw server-side HTML (which may be mostly empty for JS apps).

The Markdown text block is capped at 6 000 characters; the full content is always available in the structured markdown field.

Pick the right tool: getOgData → Open Graph tags, social preview metadata (title, description, image, favicon) getOgMarkdown → Clean readable text / article prose — ideal for feeding into an LLM getOgScrapeData → Raw HTML — use when you need to do your own parsing or link extraction getOgExtract → Targeted elements by tag (html_elements) or named CSS selectors (selectors) getOgScreenshot → Visual capture of a page as an image getOgQuery → Natural-language question answered from page content (100–200 credits/request)

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")

Discover all pages on a domain by crawling it and parsing its sitemap. Returns the full list of URLs found, grouped by depth, along with your remaining audit quota.

Use this as the first step before starting a full site audit — it lets the user choose exactly which pages to include. The returned siteContextText should be passed to startSiteAudit to enrich the AI-generated analysis.

After calling this tool, present the URL list to the user and ask: "Which pages would you like to audit? You can say 'all', pick specific numbers, or describe a section (e.g. 'all blog posts' or 'just the homepage and product pages')."

Pick the right tool: discoverSiteUrls → Step 1: find and review all pages on the domain startSiteAudit → Step 2: audit the pages the user selected previewPageAudit → Skip discovery — instantly audit a single specific URL

Start a full site audit for a domain. Audits each page for Open Graph, social media, and SEO metadata quality, then generates an AI-powered overview and per-page scores.

The urls array can be sourced from anywhere — discoverSiteUrls structured output, a codebase route scan (read route files and construct full URLs), a sitemap, or a manually provided list. Calling discoverSiteUrls first is NOT required.

For 'audit all': pass every URL from discoverSiteUrls structured output directly. For 'codebase scan': find routes in the project files (Next.js app/, pages/, React Router config, etc.), prepend the domain, and pass them here. If urls is omitted the backend crawls the domain internally.

Audits are asynchronous and can take several minutes. This tool returns an audit ID immediately — use getSiteAuditStatus to poll progress, then getSiteAuditReport to retrieve the completed report.

Pick the right tool: discoverSiteUrls → Crawl-based page discovery (use when you don't have the codebase) startSiteAudit → Run the audit — accepts URLs from any source getSiteAuditStatus → Poll until COMPLETE getSiteAuditReport → Get the full report previewPageAudit → Instantly audit a single URL without waiting

Poll the status of a running site audit. Returns the current status (QUEUED, CRAWLING, SCORING, COMPLETE, or FAILED), plus progress counters and summary scores once the audit finishes.

Call this repeatedly every 5–10 seconds after startSiteAudit until status is COMPLETE, then call getSiteAuditReport to retrieve the full results.

Pick the right tool: getSiteAuditStatus → Poll progress after startSiteAudit getSiteAuditReport → Get the full report once status is COMPLETE

Retrieve the full structured report for a completed site audit. Returns an overall site score (0–100), per-page scores and issues, an AI-generated site overview with top priorities and issue rollup, and social preview data for each audited page.

Only available once the audit status is COMPLETE. Use getSiteAuditStatus to check progress first.

Report contents:

• Overall site score and summary (critical issues, total issues, passed checks)

• AI overview: site summary, top priorities, strength areas

• Issue rollup: business impact, affected page count, fix guidance

• Per-page: score, check results, issues, social card previews (Facebook, Twitter, LinkedIn, Google)

Pick the right tool: getSiteAuditReport → Full results after audit is COMPLETE getSiteAuditStatus → Check status while audit is running previewPageAudit → Instant single-URL audit without waiting

Run an instant quality audit of a single URL. Returns a score (0–100), a score label (Well Optimized / Good / Needs Attention / Poor), a breakdown of Open Graph and social metadata checks, any issues found, and mock social previews for Facebook, Twitter, LinkedIn, and Google.

This is a synchronous, single-URL check — it returns results immediately without creating a persisted audit. It does not count against your audit page quota.

Score labels: Well Optimized (≥90) · Good (≥80) · Room for Improvement (≥70) · Needs Attention (≥60) · Poor (<60)

Pick the right tool: previewPageAudit → Instant check of one URL (no quota consumed, returns immediately) startSiteAudit → Crawl and audit an entire domain (async, uses quota)

Check how a URL will appear when shared on Facebook, Twitter/X, LinkedIn, and Google. Returns platform-specific preview cards showing the title, description, and image each platform will render, plus a quality score (0–100) and a list of issues to fix.

Use this tool when the user asks:

• 'check the link preview for example.com'

• 'how does this page look when shared on social media?'

• 'check my og tags'

• 'what will this look like on Twitter / Facebook / LinkedIn?'

This is synchronous — results are returned immediately. Does not count against your monthly audit quota. Requires OAuth authentication.

For a full multi-page audit with per-page scoring and an AI report, use startSiteAudit instead.