# OP.GG MCP server (`agentify/op-gg-mcp-server`) Actor OP.GG Model Context Protocol server providing access to League of Legends, Teamfight Tactics, Valorant, and Esports data from OP.GG. - **URL**: https://apify.com/agentify/op-gg-mcp-server.md - **Developed by:** [agentify](https://apify.com/agentify) (community) - **Categories:** MCP servers, Open source, AI - **Stats:** 6 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per event + usage This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ### OP.GG MCP Server An Apify Actor that provides access to OP.GG gaming data through the Model Context Protocol (MCP). This server enables AI agents to retrieve League of Legends, Teamfight Tactics, Valorant, and Esports data from OP.GG. **About this MCP Server:** To understand how to connect to and utilize this MCP server, please refer to the official Model Context Protocol documentation at [mcp.apify.com](https://mcp.apify.com). ### Connection URL MCP clients can connect to this server at: ```text https://mcp-servers--op-gg-mcp-server.apify.actor/mcp ```` ### Client Configuration To connect to this MCP server, use the following configuration in your MCP client: ```json { "mcpServers": { "opgg": { "url": "https://mcp-servers--op-gg-mcp-server.apify.actor/mcp", "headers": { "Authorization": "Bearer YOUR_APIFY_TOKEN" } } } } ``` **Note:** Replace `YOUR_APIFY_TOKEN` with your actual Apify API token. You can find your token in the [Apify Console](https://console.apify.com/account/integrations). ### Available Tools The OP.GG MCP Server provides access to 20+ tools across multiple gaming platforms: #### League of Legends - **lol-champion-leader-board**: Get ranking board data for League of Legends champions - **lol-champion-analysis**: Provides analysis data for League of Legends champions (counter and ban/pick data available in the "weakCounters" field) - **lol-champion-meta-data**: Retrieves meta data for a specific champion, including statistics and performance metrics - **lol-champion-skin-sale**: Retrieves information about champion skins that are currently on sale - **lol-summoner-search**: Search for League of Legends summoner information and stats - **lol-champion-positions-data**: Retrieves position statistics data for League of Legends champions, including win rates and pick rates by position - **lol-summoner-game-history**: Retrieve recent game history for a League of Legends summoner - **lol-summoner-renewal**: Refresh and update League of Legends summoner match history and stats #### Esports (League of Legends) - **esports-lol-schedules**: Get upcoming LoL match schedules - **esports-lol-team-standings**: Get team standings for a LoL league #### Teamfight Tactics (TFT) - **tft-meta-trend-deck-list**: TFT deck list tool for retrieving current meta decks - **tft-meta-item-combinations**: TFT tool for retrieving information about item combinations and recipes - **tft-champion-item-build**: TFT tool for retrieving champion item build information - **tft-recommend-champion-for-item**: TFT tool for retrieving champion recommendations for a specific item - **tft-play-style-comment**: This tool provides comments on the playstyle of TFT champions #### Valorant - **valorant-meta-maps**: Valorant map meta data - **valorant-meta-characters**: Valorant character meta data - **valorant-leaderboard**: Fetch Valorant leaderboard by region - **valorant-agents-composition-with-map**: Retrieve agent composition data for a Valorant map - **valorant-characters-statistics**: Retrieve character statistics data for Valorant, optionally filtered by map - **valorant-player-match-history**: Retrieve match history for a Valorant player using their game name and tag line ### Features - **Real-time Gaming Data**: Access current game statistics, leaderboards, and meta information - **Multi-Game Support**: Covers League of Legends, Teamfight Tactics, Valorant, and Esports - **Player Analytics**: Get detailed player statistics and match histories - **Meta Analysis**: Retrieve current meta trends, champion builds, and strategic data - **Competitive Insights**: Access professional esports schedules and team standings ### 🚩 Claim this MCP server All credits to the original authors of ### References To learn more about Apify and Actors, take a look at the following resources: - [Apify SDK for JavaScript documentation](https://docs.apify.com/sdk/js) - [Apify SDK for Python documentation](https://docs.apify.com/sdk/python) - [Apify Platform documentation](https://docs.apify.com/platform) - [Apify MCP Server](https://docs.apify.com/platform/integrations/mcp) - [Webinar: Building and Monetizing MCP Servers on Apify](https://www.youtube.com/watch?v=w3AH3jIrXXo) - [Join our developer community on Discord](https://discord.com/invite/jyEM2PRvMU) #### Push project on your local machine to Apify You can also deploy the project on your local machine to Apify without the need for the Git repository. 1. Log in to Apify. You will need to provide your [Apify API Token](https://console.apify.com/account/integrations) to complete this action. ```bash apify login ``` 2. Deploy your Actor. This command will deploy and build the Actor on the Apify Platform. You can find your newly created Actor under [Actors -> My Actors](https://console.apify.com/actors?tab=my). ```bash apify push ``` ### Documentation reference To learn more about Apify and Actors, take a look at the following resources: - [Apify SDK for JavaScript documentation](https://docs.apify.com/sdk/js) - [Apify SDK for Python documentation](https://docs.apify.com/sdk/python) - [Apify Platform documentation](https://docs.apify.com/platform) - [Join our developer community on Discord](https://discord.com/invite/jyEM2PRvMU) # Actor input Schema ## Actor input object example ```json {} ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("agentify/op-gg-mcp-server").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("agentify/op-gg-mcp-server").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call agentify/op-gg-mcp-server --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=agentify/op-gg-mcp-server", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "OP.GG MCP server", "description": "OP.GG Model Context Protocol server providing access to League of Legends, Teamfight Tactics, Valorant, and Esports data from OP.GG.", "version": "0.0", "x-build-id": "uQMDxsbSJ9XKBVOKE" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/agentify~op-gg-mcp-server/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-agentify-op-gg-mcp-server", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/agentify~op-gg-mcp-server/runs": { "post": { "operationId": "runs-sync-agentify-op-gg-mcp-server", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/agentify~op-gg-mcp-server/run-sync": { "post": { "operationId": "run-sync-agentify-op-gg-mcp-server", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": {} }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```