The OP.GG Esports MCP Server enables AI agents to retrieve and process League of Legends esports match data seamlessly.
Fetch Upcoming Matches: Access upcoming League of Legends match schedules including match name, league, status, score, scheduled time, and direct links
Structured Data Format: Receive match data in a clean, structured format optimized for AI consumption
MCP Compatibility: Integrates with any MCP-compatible client or agent framework
Connects directly to the OP.GG Esports GraphQL API to retrieve upcoming League of Legends match schedules and information
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@opgg-esports show me upcoming League of Legends matches"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
The OP.GG Esports MCP Server is a Model Context Protocol implementation that seamlessly connects OP.GG Esports data with AI agents and platforms. This server enables AI agents to retrieve upcoming League of Legends match schedules and information via function calling.
This MCP server provides AI agents with access to OP.GG Esports data through a standardized interface. Built on TypeScript and Node.js, it connects directly to the OP.GG Esports GraphQL API and formats the data in a way that's easily consumable by AI models and agent frameworks.
Related MCP server: OP.GG MCP Server
The OP.GG Esports MCP Server currently supports the following tools:
get-lol-matches: Fetch and format upcoming League of Legends match schedules from OP.GG Esports
Returns match name, league, status, score, scheduled time, and a direct link to the match
Formats the data in a clean, structured format for AI consumption
To install OP.GG Esports MCP for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @opgginc/esports-mcp --client claude# Install dependencies
pnpm install
# Build the project
pnpm build# Start the MCP server on stdio
pnpm start# Start using Node.js
node dist/index.js# Run directly with npx
npx -y @opgg/esports-mcpTo add this server to your MCP configuration (e.g., Windsurf's mcp_config.json), add the following entry:
{
"mcpServers": {
"opgg-esports": {
"command": "node",
"args": ["/path/to/esports-mcp/dist/index.js"]
}
}
}Alternatively, you can use the npm package if published:
{
"mcpServers": {
"opgg-esports": {
"command": "npx",
"args": ["-y", "@opgg/esports-mcp"]
}
}
}The OP.GG Esports MCP Server can be used with any MCP-compatible client. Here are some examples:
{ "type": "list_tools" }Response:
{
"tools": [
{
"name": "get-lol-matches",
"description": "Get upcoming LoL match schedules from OP.GG Esports"
}
]
}{
"type": "tool_call",
"tool_call": {
"name": "get-lol-matches"
}
}Response:
{
"content": [
{
"type": "text",
"text": "Upcoming match schedules:\n\nMatch: Team A vs Team B\nLeague: LCK\nStatus: SCHEDULED\nScore: 0 - 0\nScheduled at: 4/6/2025, 7:00:00 PM\nDetails: https://esports.op.gg/matches/12345\n---\n..."
}
]
}This project is licensed under the MIT License - see the LICENSE file for details.
Get upcoming LoL match schedules from OP.GG Esports
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions retrieving data ('Get') but lacks details on rate limits, authentication needs, error handling, or response format. This leaves significant gaps in understanding how the tool behaves operationally.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without any redundant or unnecessary information. It is perfectly front-loaded and wastes no words, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no output schema, the description adequately covers the basic purpose. However, it lacks details on behavioral aspects like data freshness, pagination, or error cases, which would be helpful given the absence of annotations and output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing instead on the tool's purpose, which aligns well with the empty input schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('upcoming LoL match schedules from OP.GG Esports'), providing a specific purpose. It distinguishes the tool by specifying the data source (OP.GG Esports) and content type (match schedules). However, without sibling tools, full differentiation isn't demonstrated, preventing a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, prerequisites, or contextual constraints. It merely states what the tool does without indicating appropriate scenarios or limitations, leaving usage entirely implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
get-lol-matchesWith only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly distinct as it is the sole operation available.
A single tool inherently has perfect naming consistency, as there are no other tools to compare against. The name 'get-lol-matches' follows a clear verb-noun pattern.
One tool is too few for a server named 'opgg-esports', which suggests a broader domain of esports data. This minimal set severely limits functionality and feels incomplete for the apparent scope.
The tool set is severely incomplete for an esports data server. It only provides match schedules, with no coverage for other essential data like results, team info, player stats, or tournament details, leaving significant gaps.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
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