OpenGraph.io MCP Server

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 <img> 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. Uses 100 API credits per request (200 with the 'mini' model); a cached answer uses 1.

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. LONG PAGES — prefer retrieval over truncation. Set `query` with `chunking: true` to get back only the passages that answer your question (ranked by relevance) instead of the whole page. Use `max_chars` to cap raw output when you genuinely need prose. `chunk_size` and `chunk_overlap` tune the split; `heading_aware` keeps sections intact. EXTRAS — `include_links`, `include_images`, and `include_headings` return structured link, image, and outline data, which avoids a second scrape call just to enumerate them. UNTRUSTED CONTENT — this fetches arbitrary pages. Set `ai_sanitize: true` when the result will be fed to a model: it scans for prompt-injection attempts and returns a safety report. `ai_sanitize_mode: 'block'` rejects a risky page outright (HTTP 422) rather than returning it. 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)

Build a structured brand profile for a website via the OpenGraph.io Brand Intelligence API. Crawls about ten of the brand's own pages and returns: brand (name, description, tagline, category), identity (logos, an inline SVG logo when the site draws one, icon, colors, fonts), products, audiences, positioning, messaging, voice, visual style, and links. Values with too little evidence come back null rather than guessed. Use it when you need to understand or write as a brand; use getOgData or getOgMarkdown for a single page. COST: a fresh analysis uses 500 API credits; a cached one uses 1; a failed one uses nothing. The cache is reused only for the same url AND the same sections, so changing sections, adding questions, or cache_ok:false each run and bill a fresh analysis. To read one section of a profile you already fetched, reuse that result instead of calling again. Synchronous; can take up to a minute. Rendering and proxies are chosen server-side; the usual fetch parameters do not apply. identity.colors is a ranked candidate list, not the verified brand color: a 'primary' role is a best-effort guess and is omitted for an all-neutral palette.

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\"

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. Files are only ever written inside one export folder (~/Downloads/opengraph-mcp, or MCP_EXPORT_DIR); pass a file name or a path inside it. SVG is returned as a file only, never inline, because it can carry script. 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="logo.png")