io.github.securecoders/opengraph-io-mcp

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by securecoders · TypeScript

OpenGraph.io MCP Server

MCP server for OpenGraph.io API - fetch OG data, screenshots, scrape, and generate images

Fetches OpenGraph data, screenshots, scrapes content, and generates images from URLs.

Topics

mcpmcp-serverunfurl

README.md11 KBView on GitHub

OpenGraph MCP Server (og-mcp)

og‑mcp is a Model‑Context‑Protocol (MCP) server that makes every OpenGraph.io ( https://opengraph.io ) API endpoint available to AI agents (e.g. Anthropic Claude, Cursor, LangGraph) through the standard MCP interface.

Why? If you already use OpenGraph.io to unfurl links, scrape HTML, extract article text, or capture screenshots, you can now give the same capabilities to your autonomous agents without exposing raw API keys.

Global Installation

You can install this package globally via npm:

code

npm install -g opengraph-io-mcp

Quick Install

CLI Installer (Recommended)

The easiest way to configure OpenGraph MCP for any supported client:

bash

# Interactive mode - guides you through setup
npx opengraph-io-mcp-install

# Direct mode - specify client and app ID
npx opengraph-io-mcp-install --client cursor --app-id YOUR_APP_ID

Supported clients: cursor, claude-desktop, windsurf, vscode, zed, jetbrains

Claude Desktop Extension

For Claude Desktop users, you can also download the .mcpb extension for one-click installation from the Releases page.

Client Configuration

All configurations below use the hosted HTTPS transport (recommended). Replace YOUR_OPENGRAPH_APP_ID with your OpenGraph.io App ID. No local installation or npx required — just point your client at the hosted URL.

Claude Desktop

Config location:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json

json

{
  "mcpServers": {
    "opengraph": {
      "url": "https://mcp.opengraph.io/mcp",
      "headers": {
        "x-app-id": "YOUR_OPENGRAPH_APP_ID"
      }
    }
  }
}

Claude Code

One-command installation:

bash

claude mcp add --transport http --header "x-app-id: YOUR_OPENGRAPH_APP_ID" opengraph https://mcp.opengraph.io/mcp

Cursor

Config location: ~/.cursor/mcp.json

json

{
  "mcpServers": {
    "opengraph": {
      "url": "https://mcp.opengraph.io/mcp",
      "headers": {
        "x-app-id": "YOUR_OPENGRAPH_APP_ID"
      }
    }
  }
}

VS Code

Config location: .vscode/mcp.json (in your project directory)

VS Code supports input prompts for secure credential handling:

json

{
  "inputs": [
    {
      "type": "promptString",
      "id": "opengraph-app-id",
      "description": "OpenGraph App ID",
      "password": true
    }
  ],
  "servers": {
    "opengraph": {
      "type": "http",
      "url": "https://mcp.opengraph.io/mcp",
      "headers": {
        "x-app-id": "${input:opengraph-app-id}"
      }
    }
  }
}

Windsurf

Config location: ~/.codeium/windsurf/mcp_config.json

json

{
  "mcpServers": {
    "opengraph": {
      "url": "https://mcp.opengraph.io/mcp",
      "headers": {
        "x-app-id": "YOUR_OPENGRAPH_APP_ID"
      }
    }
  }
}

JetBrains AI Assistant

Add to your JetBrains AI Assistant MCP configuration:

json

{
  "mcpServers": {
    "opengraph": {
      "url": "https://mcp.opengraph.io/mcp",
      "headers": {
        "x-app-id": "YOUR_OPENGRAPH_APP_ID"
      }
    }
  }
}

Zed

Config location: ~/.config/zed/settings.json

Note: Zed uses context_servers instead of mcpServers:

json

{
  "context_servers": {
    "opengraph": {
      "transport": "http",
      "url": "https://mcp.opengraph.io/mcp",
      "headers": {
        "x-app-id": "YOUR_OPENGRAPH_APP_ID"
      }
    }
  }
}

Available Tools

OpenGraph.io Data Tools

Tool Name	OpenGraph.io API Endpoint	Description	Documentation
Get OG Data	`/api/1.1/site/<URL>`	Extracts Open Graph data from a URL	OpenGraph.io Docs
Get OG Scrape Data	`/api/1.1/scrape/<URL>`	Scrapes data from a URL using OpenGraph's scrape endpoint	OpenGraph.io Docs
Get OG Screenshot	`/api/1.1/screenshot/<URL>`	Gets a screenshot of a webpage using OpenGraph's screenshot endpoint	OpenGraph.io Docs
Get OG Query	`/api/1.1/query/<URL>`	Query a site with a custom question and optional response structure	OpenGraph.io Docs
Get OG Extract	`/api/1.1/extract/<URL>`	Extract specific HTML elements (h1, p, etc.) from a webpage	OpenGraph.io Docs

Image Generation Tools

Tool Name	Description
Generate Image	Create professional images: illustrations, diagrams (Mermaid/D2/Vega), icons, social cards, or QR codes
Iterate Image	Refine, modify, or create variations of existing generated images
Inspect Image Session	Retrieve session metadata and asset history for image generation sessions
Export Image Asset	Export generated image assets as inline base64, with optional disk write when running locally

Image Generation

The og-mcp server includes powerful AI-driven image generation capabilities, perfect for creating social media cards, architecture diagrams, icons, and more.

Generate Image

Create images from natural language prompts or diagram code.

Supported Image Types (kind):

illustration - General-purpose AI-generated images
diagram - Technical diagrams from Mermaid, D2, or Vega syntax
icon - App icons and logos
social-card - OG images optimized for social sharing
qr-code - QR codes with optional styling

Preset Aspect Ratios:

Social: og-image, twitter-card, twitter-post, linkedin-post, facebook-post, instagram-square, instagram-portrait, instagram-story, youtube-thumbnail
Standard: wide, square, portrait
Icons: icon-small, icon-medium, icon-large

Style Presets: github-dark, github-light, notion, vercel, linear, stripe, neon-cyber, pastel, minimal-mono, corporate, startup, documentation, technical

Diagram Templates: auth-flow, oauth2-flow, crud-api, microservices, ci-cd, gitflow, database-schema, state-machine, user-journey, cloud-architecture, system-context

Example Usage:

code

// Generate a social card
generateImage({
  prompt: "A modern tech startup hero image with abstract geometric shapes",
  kind: "social-card",
  aspectRatio: "og-image",
  stylePreset: "vercel",
  brandColors: ["#0070F3", "#000000"]
})

// Generate a diagram from Mermaid syntax
generateImage({
  prompt: "graph TD; A[User] --> B[API]; B --> C[Database]",
  kind: "diagram",
  diagramSyntax: "mermaid",
  stylePreset: "github-dark"
})

Iterate Image

Refine or modify an existing generated image.

Use cases:

Edit specific parts: "change the background to blue"
Apply style changes: "make it more minimalist"
Fix issues: "remove the text", "make the icon larger"
Crop to specific coordinates

Example:

code

iterateImage({
  sessionId: "uuid-from-generate",
  assetId: "uuid-from-generate",
  prompt: "Change the primary color to #0033A0 and add a subtle drop shadow"
})

Inspect Image Session

Review session details and find asset IDs for iteration.

Returns:

Session metadata (creation time, name, status)
List of all assets with prompts, toolchains, and status
Parent-child relationships showing iteration history

Example:

code

inspectImageSession({
  sessionId: "uuid-from-generate"
})

Export Image Asset

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. On hosted/HTTP transport, the path is ignored and the image is returned inline only.

Examples:

code

// Inline only (works everywhere)
exportImageAsset({
  sessionId: "uuid-from-generate",
  assetId: "uuid-from-generate"
})

// Save to disk (stdio/local only)
exportImageAsset({
  sessionId: "uuid-from-generate",
  assetId: "uuid-from-generate",
  destinationPath: "/Users/me/project/images/hero.png"
})

How it works

og-mcp Architecture Diagram <sup>Diagram generated with og-mcp's image generation tools</sup>

The og-mcp server acts as a bridge between AI clients (like Claude or other LLMs) and the OpenGraph.io API:

AI client makes a tool call to one of the available MCP functions
og-mcp server receives the request and formats it for the OpenGraph.io API
OpenGraph.io processes the request and returns data
og-mcp transforms the response into a format suitable for the AI client
AI client receives the structured data ready for use

This abstraction prevents exposing API keys directly to the AI while providing full access to OpenGraph.io capabilities.

Setup and Running

Clone this repository
Install dependencies:
code
```
npm install
```
Build the TypeScript code:
code
```
npm run build
```
Start the server:
code
```
npm start
```

The server will run on port 3010 by default (configurable via PORT environment variable).

Configuration

The server requires an OpenGraph.io App ID to function properly. You can provide this in several ways:

Using environment variables: Set OPENGRAPH_APP_ID or APP_ID in a .env file or as an environment variable
Using command-line arguments with stdio transport: --app-id YOUR_APP_ID
When using SSE transport: Include it in the URL as a query parameter (?app_id=YOUR_APP_ID)

Example .env file:

code

OPENGRAPH_APP_ID=your_app_id_here
# or
APP_ID=your_app_id_here

Transport Options

Stdio Transport (Recommended)

For command-line usage and npm global installation, the server can be run with stdio transport:

code

npm run start:stdio

You can pass the OpenGraph API key directly via command-line argument:

code

npm run start:stdio -- --app-id YOUR_APP_ID

When installed globally:

code

opengraph-io-mcp --app-id YOUR_APP_ID

This mode allows the server to be invoked directly by other applications that use MCP.

HTTP/SSE Transport

This method runs a web server that can be accessed over HTTP and uses SSE for streaming:

code

npm start

Troubleshooting

If tools aren't showing up, check that the server is running and the URL is correctly configured in Cursor
Check the server logs for any connection or authorization issues
Verify that Claude has been instructed to use the specific tools by name

Install

claude_desktop_config.json

{
  "mcpServers": {
    "opengraph-io-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "opengraph-io-mcp@1.3.5"
      ]
    }
  }
}