OP.GG MCP Server Integration

What does “OP.GG” MCP Server do?

The OP.GG MCP Server is a Model Context Protocol (MCP) implementation that provides seamless integration between OP.GG data and AI agents or platforms. By exposing OP.GG’s data endpoints via function calling, this server allows AI assistants to access diverse gaming data, such as player statistics, leaderboards, and other game-related analytics. It enhances development workflows by enabling AI-driven interactions with OP.GG’s resources, making it easier to build tools that can analyze player performance, surface live game data, or integrate gaming statistics into other applications. The OP.GG MCP Server is ideal for developers and AI integrators looking to enrich their applications with real-time or historical OP.GG data, facilitating advanced use cases in gaming analytics, automated reporting, and intelligent game coaching.

List of Prompts

No prompt templates are listed in the available documentation or files.

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List of Resources

No explicit resources are listed in the available documentation or files.

List of Tools

No explicit tools are described in the documentation or within server.py as accessible from the provided data.

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Use Cases of this MCP Server

• Game Data Retrieval: AI agents can access OP.GG’s comprehensive data about players, matches, and leaderboards to provide insights or build dashboards for users.
• Real-time Analytics: Integrate real-time OP.GG statistics into AI platforms for live monitoring, performance tracking, or streaming overlays.
• Automated Reporting: Generate automated reports on player progress, rankings, or match outcomes using OP.GG data accessed via the MCP server.
• Intelligent Coaching: AI assistants can analyze player data from OP.GG to offer tailored coaching advice or strategic recommendations.
• Community Engagement: Build bots or tools that interact with gaming communities by sharing up-to-date OP.GG stats and leaderboards.

How to set it up

Windsurf

1. Ensure Node.js and Windsurf are installed.
2. Open your Windsurf configuration file.
3. Add the OP.GG MCP Server to your mcpServers section with the following JSON snippet:

   {
     "mcpServers": {
       "opgg-mcp": {
         "command": "npx",
         "args": ["@opgginc/opgg-mcp@latest"]
       }
     }
   }
   

4. Save the configuration and restart Windsurf.
5. Verify the setup by checking server logs or running a test query.

Securing API Keys Example:

{
  "mcpServers": {
    "opgg-mcp": {
      "command": "npx",
      "args": ["@opgginc/opgg-mcp@latest"],
      "env": {
        "OPGG_API_KEY": "${OPGG_API_KEY}"
      },
      "inputs": {
        "apiKey": "${OPGG_API_KEY}"
      }
    }
  }
}

Claude

1. Install Node.js and Claude if needed.
2. Edit the Claude configuration file.
3. Insert the OP.GG MCP Server in the mcpServers object:

   {
     "mcpServers": {
       "opgg-mcp": {
         "command": "npx",
         "args": ["@opgginc/opgg-mcp@latest"]
       }
     }
   }
   

4. Restart Claude to load the new MCP server.
5. Confirm connectivity by querying OP.GG data.

Cursor

1. Install Node.js and Cursor.
2. Open the Cursor configuration file.
3. Add the OP.GG MCP Server to the mcpServers object:

   {
     "mcpServers": {
       "opgg-mcp": {
         "command": "npx",
         "args": ["@opgginc/opgg-mcp@latest"]
       }
     }
   }
   

4. Save changes and restart Cursor.
5. Test the connection by accessing OP.GG endpoints.

Cline

1. Confirm Node.js and Cline are installed.
2. Access the configuration file for Cline.
3. Add the OP.GG MCP Server:

   {
     "mcpServers": {
       "opgg-mcp": {
         "command": "npx",
         "args": ["@opgginc/opgg-mcp@latest"]
       }
     }
   }
   

4. Save and restart Cline.
5. Ensure the MCP server is running and accessible.

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "opgg-mcp": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “opgg-mcp” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

A LICENSE file is present, and the repository has a small but active user base (16 stars, 6 forks). The server is focused on OP.GG data integration but lacks public documentation on prompts, resources, or tools.

Based on the information and the completeness of the documented features, this MCP scores moderately, mainly due to a lack of detail on resources, prompts, and tools.

Our opinion

The OP.GG MCP Server offers a valuable integration point for gaming data, but the lack of public detail about its prompt templates, resources, and tools limits its immediate usability and extensibility for developers. Documentation improvements and more transparent feature listings would raise its score.

MCP Score