What is Opengraph Io Mcp

opengraph-io-mcp is a Model-Context-Protocol (MCP) server that provides access to OpenGraph.io API endpoints for AI agents, allowing them to utilize OpenGraph.io’s capabilities without exposing raw API keys.

Use cases

Use cases include enabling AI agents to unfurl links, extract article text, capture screenshots of webpages, and provide enriched content for applications without direct API key exposure.

How to use

To use opengraph-io-mcp, AI clients can make tool calls to the available MCP functions, which then interact with the OpenGraph.io API to retrieve data or perform actions like scraping and screenshotting.

Key features

Key features include access to OpenGraph data extraction, scraping capabilities, and webpage screenshot generation through a standardized MCP interface.

Where to use

opengraph-io-mcp can be used in various fields such as AI development, web scraping, content management, and any application that requires interaction with OpenGraph data.

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.

Available 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

How it works

┌─────────────┐          MCP (JSON‑RPC)           ┌──────────────┐
│  AI Client  │ ───────────────────────────────▶ │   og‑mcp     │
└─────────────┘                                  │  (this repo) │
        ▲                                        └──────┬───────┘
        │                                               │ REST
        │                                               ▼
        │                                    ┌────────────────────┐
        └─────────────────────────────────── │  api.opengraph.io  │
                                             └────────────────────┘

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

1. AI client makes a tool call to one of the available MCP functions
2. og-mcp server receives the request and formats it for the OpenGraph.io API
3. OpenGraph.io processes the request and returns data
4. og-mcp transforms the response into a format suitable for the AI client
5. 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

1. Clone this repository
2. Install dependencies:

   npm install
   

3. Build the TypeScript code:

   npm run build
   

4. Start the server:

   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:

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

Example .env file:

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:

npm run start:stdio

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

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

When installed globally:

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:

npm start

Global Installation

You can install this package globally via npm:

npm install -g opengraph-io-mcp

After installation, you can use it from anywhere:

opengraph-io-mcp

This will start the server with stdio transport, which can be configured in MCP applications.

Integrating with Cursor/Claude

Prerequisites

• Have Cursor installed on your machine
• Ensure this MCP server is running locally or deployed to a publicly accessible endpoint

Integration Steps

Running with stdio transport in Cursor (Recommended)

If you’ve installed the package globally, you can use it in Cursor like this:

{
  "mcpServers": {
    "og-mcp": {
      "command": "opengraph-io-mcp"
    }
  }
}

For passing the OpenGraph API key directly in the configuration, you have two options:

As command-line arguments:

{
  "mcpServers": {
    "og-mcp": {
      "command": "opengraph-io-mcp",
      "args": [
        "--app-id",
        "YOUR_APP_ID"
      ]
    }
  }
}

Or as an environment variable (recommended):

{
  "mcpServers": {
    "og-mcp": {
      "command": "opengraph-io-mcp",
      "env": {
        "APP_ID": "YOUR_APP_ID"
      }
    }
  }
}

You can also use npx to run

{
  "mcpServers": {
    "og-mcp": {
      "command": "npx",
      "args": [
        "opengraph-io-mcp"
      ],
      "env": {
        "APP_ID": "YOUR_APP_ID"
      }
    }
  }
}

Using HTTP/SSE Transport

Start the MCP server:

npm start

Add the following to your Cursor mcp.json:

{
  "mcpServers": {
    "og-mcp": {
      "url": "http://localhost:3010/sse?app_id={YOUR_APP_ID}"
    }
  }
}

Running on Windsurf

Using stdio transport (Recommended)

Add this to your ./codeium/windsurf/model_config.json:

{
  "mcpServers": {
    "og-mcp": {
      "command": "opengraph-io-mcp",
      "env": {
        "APP_ID": "YOUR_APP_ID"
      }
    }
  }
}

Using npx:

{
  "mcpServers": {
    "og-mcp": {
      "command": "npx",
      "args": [
        "opengraph-io-mcp"
      ],
      "env": {
        "APP_ID": "YOUR_APP_ID"
      }
    }
  }
}

Using HTTP/SSE Transport

Add this to your ./codeium/windsurf/model_config.json:

{
  "mcpServers": {
    "og-mcp": {
      "serverUrl": "http://localhost:3010/sse?app_id=YOUR_APP_ID"
    }
  }
}

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