OP.GG Esports MCP 服务器是一个模型上下文协议 (MCP) 实现，可将 OP.GG Esports 数据与 AI 代理和平台无缝连接。该服务器使 AI 代理能够通过函数调用检索即将进行的英雄联盟比赛日程和信息。
该 MCP 服务器通过标准化接口为 AI 代理提供访问 OP.GG Esports 数据的权限。它基于 TypeScript 和 Node.js 构建，可直接连接到 OP.GG Esports GraphQL API，并将数据格式化为 AI 模型和代理框架易于理解的格式。
Related MCP server: OP.GG MCP Server
OP.GG Esports MCP 服务器目前支持以下工具：
get-lol-matches ：从 OP.GG Esports 获取并格式化即将举行的英雄联盟比赛日程
返回比赛名称、联赛、状态、比分、预定时间以及比赛的直接链接
将数据格式化为干净、结构化的格式，以供 AI 使用
要通过Smithery自动为 Claude Desktop 安装 OP.GG Esports MCP：
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-mcp要将此服务器添加到您的 MCP 配置（例如，Windsurf 的 mcp_config.json），请添加以下条目：
{
"mcpServers": {
"opgg-esports": {
"command": "node",
"args": ["/path/to/esports-mcp/dist/index.js"]
}
}
}或者，如果已发布，您可以使用 npm 包：
{
"mcpServers": {
"opgg-esports": {
"command": "npx",
"args": ["-y", "@opgg/esports-mcp"]
}
}
}OP.GG Esports MCP 服务器可与任何兼容 MCP 的客户端配合使用。以下是一些示例：
{ "type": "list_tools" }回复：
{
"tools": [
{
"name": "get-lol-matches",
"description": "Get upcoming LoL match schedules from OP.GG Esports"
}
]
}{
"type": "tool_call",
"tool_call": {
"name": "get-lol-matches"
}
}回复：
{
"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..."
}
]
}该项目根据 MIT 许可证获得许可 - 有关详细信息，请参阅 LICENSE 文件。
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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