原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
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Scorecard MCP

作者:scorecard-ai版本 2.1.1i★ –i电脑或云端
注册名称io.scorecard/mcp

安装

概览

作者提供的说明(英文原文)

MCP server providing access to the Scorecard API to evaluate and optimize LLM systems.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 电脑或云端
  • 传输方式: stdio, Streamable HTTP
  • 分类: 搜索与 AI 记忆
  • 你需要填写:SCORECARD_API_KEY

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。

你需要

  • 在云端运行无需安装任何东西,通过互联网连接
  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

适用于网页版、桌面版和手机版 Claude:

  1. 打开 Settings → Connectors
  2. 点击 Add custom connector
  3. 粘贴下面的地址,然后点击 Add
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Add2https://…3
https://mcp.scorecard.io/mcp

或者在你的电脑上运行

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "scorecard": {
      "command": "npx",
      "args": [
        "-y",
        "scorecard-ai-mcp"
      ],
      "env": {
        "SCORECARD_API_KEY": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add --transport http scorecard https://mcp.scorecard.io/mcp

或者在你的电脑上运行

claude mcp add scorecard --env SCORECARD_API_KEY=your-value -- npx -y scorecard-ai-mcp

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "scorecard": {
      "url": "https://mcp.scorecard.io/mcp"
    }
  }
}

或者在你的电脑上运行

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "scorecard": {
      "command": "npx",
      "args": [
        "-y",
        "scorecard-ai-mcp"
      ],
      "env": {
        "SCORECARD_API_KEY": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "scorecard": {
      "type": "http",
      "url": "https://mcp.scorecard.io/mcp"
    }
  }
}

或者在你的电脑上运行

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "scorecard": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "scorecard-ai-mcp"
      ],
      "env": {
        "SCORECARD_API_KEY": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

ChatGPT 只能连接互联网上的服务器:

  1. 打开网页版 ChatGPT → Settings → Connectors (Apps)
  2. 点击 Create 或 Add(部分套餐需要先在 Advanced 中开启 Developer mode)
  3. 粘贴下面的地址,起个名字,然后保存
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Create2https://…3
https://mcp.scorecard.io/mcp

菜单名称可能因套餐和版本不同而略有差异。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • SCORECARD_API_KEY 机密 必填 env
    Scorecard API key for authentication. Get your API key from https://app.scorecard.io/settings

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过域名 scorecard.io 验证(注册中心会核实域名所有权)

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    端点有响应

    尚未检查;我们会轮流检查各个端点

  • … 尚未检查

    使用 OAuth 登录

    尚未检查;我们会轮流检查各个端点

  • … 尚未检查

    工具描述中没有隐藏指令

    尚未检查;我们会在检查端点时读取工具列表

与“搜索与 AI 记忆”中的其他服务器比较i

  • 星标数多于此分类中其他 7256 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 7256 个服务器的 0% 更新
  • 基础检查结果等于或优于此分类中其他 7256 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Scorecard MCP 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

你需要填写:SCORECARD_API_KEY

它在我的电脑上运行还是在云端?

两种方式都可以:安装在你的电脑上,或者连接云端版本。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(2.1.1)于14个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。

有什么可以替代它?

同一分类中有:Context7, Codebase Memory, Exa

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Context7

作者:upstash

Up-to-date docs for AI agents

电脑或云端★ 64,224MIT今天更新
安装

Codebase Memory

作者:DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

在你的电脑上运行★ 48,148MIT20天前更新
安装

Exa

作者:exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

在云端运行★ 5,213MIT上个月更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

Scorecard TypeScript API Library

))](https://npmjs.org/package/scorecard-ai)

This library provides convenient access to the Scorecard REST API from server-side TypeScript or JavaScript.

The REST API documentation can be found on docs.scorecard.io. The full API of this library can be found in api.md.

It is generated with Stainless.

MCP Server

Use the Scorecard MCP Server to enable AI assistants to interact with this API, allowing them to explore endpoints, make test requests, and use documentation to help integrate this SDK into your application.

Note: You may need to set environment variables in your MCP client.

Installation

npm install scorecard-ai

Usage

The full API of this library can be found in api.md.

import Scorecard from 'scorecard-ai';

const client = new Scorecard({ apiKey: process.env['SCORECARD_API_KEY'], // This is the default and can be omitted environment: 'staging', // or 'production' | 'local'; defaults to 'production' });

const run = await client.runs.create('314', { metricIds: ['789', '101'], testsetId: '246' });

console.log(run.id);

Request & Response types

This library includes TypeScript definitions for all request params and response fields. You may import and use them like so:

import Scorecard from 'scorecard-ai';

const client = new Scorecard({ apiKey: process.env['SCORECARD_API_KEY'], // This is the default and can be omitted environment: 'staging', // or 'production' | 'local'; defaults to 'production' });

const testset: Scorecard.Testset = await client.testsets.get('246');

Documentation for each method, request param, and response field are available in docstrings and will appear on hover in most modern editors.

Handling errors

When the library is unable to connect to the API, or if the API returns a non-success status code (i.e., 4xx or 5xx response), a subclass of APIError will be thrown:

const testset = await client.testsets.get('246').catch(async (err) => {

if (err instanceof Scorecard.APIError) { console.log(err.status); // 400 console.log(err.name); // BadRequestError console.log(err.headers); // {server: 'nginx', ...} } else { throw err; } });

Error codes are as follows:

Status CodeError Type
400BadRequestError
401AuthenticationError
403PermissionDeniedError
404NotFoundError
422UnprocessableEntityError
429RateLimitError
>=500InternalServerError
N/AAPIConnectionError
Retries

Certain errors will be automatically retried 2 times by default, with a short exponential backoff. Connection errors (for example, due to a network connectivity problem), 408 Request Timeout, 409 Conflict, 429 Rate Limit, and >=500 Internal errors will all be retried by default.

You can use the maxRetries option to configure or disable this:

// Configure the default for all requests:

const client = new Scorecard({ maxRetries: 0, // default is 2 });

// Or, configure per-request: await client.testsets.get('246', { maxRetries: 5, });

Timeouts

Requests time out after 1 minute by default. You can configure this with a timeout option:

// Configure the default for all requests:

const client = new Scorecard({ timeout: 20 * 1000, // 20 seconds (default is 1 minute) });

// Override per-request: await client.testsets.get('246', { timeout: 5 * 1000, });

On timeout, an APIConnectionTimeoutError is thrown.

Note that requests which time out will be retried twice by default.

Auto-pagination

List methods in the Scorecard API are paginated. You can use the for await … of syntax to iterate through items across all pages:

async function fetchAllTestcases(params) {

const allTestcases = []; // Automatically fetches more pages as needed. for await (const testcase of client.testcases.list('246', { limit: 30 })) { allTestcases.push(testcase); } return allTestcases; }

Alternatively, you can request a single page at a time:

let page = await client.testcases.list('246', { limit: 30 });

for (const testcase of page.data) { console.log(testcase); }

// Convenience methods are provided for manually paginating: while (page.hasNextPage()) { page = await page.getNextPage(); // ... }

Advanced Usage

Accessing raw Response data (e.g., headers)

The "raw" Response returned by fetch() can be accessed through the .asResponse() method on the APIPromise type that all methods return. This method returns as soon as the headers for a successful response are received and does not consume the response body, so you are free to write custom parsing or streaming logic.

You can also use the .withResponse() method to get the raw Response along with the parsed data. Unlike .asResponse() this method consumes the body, returning once it is parsed.

const client = new Scorecard();

const response = await client.testsets.get('246').asResponse(); console.log(response.headers.get('X-My-Header')); console.log(response.statusText); // access the underlying Response object

const { data: testset, response: raw } = await client.testsets.get('246').withResponse(); console.log(raw.headers.get('X-My-Header')); console.log(testset.id);

Logging

[!IMPORTANT]

All log messages are intended for debugging only. The format and content of log messages

may change between releases.

Log levels

The log level can be configured in two ways:

  1. Via the SCORECARD_LOG environment variable
  2. Using the logLevel client option (overrides the environment variable if set)
import Scorecard from 'scorecard-ai';

const client = new Scorecard({ logLevel: 'debug', // Show all log messages });

Available log levels, from most to least verbose:

  • 'debug' - Show debug messages, info, warnings, and errors
  • 'info' - Show info messages, warnings, and errors
  • 'warn' - Show warnings and errors (default)
  • 'error' - Show only errors
  • 'off' - Disable all logging

At the 'debug' level, all HTTP requests and responses are logged, including headers and bodies. Some authentication-related headers are redacted, but sensitive data in request and response bodies may still be visible.

Custom logger

By default, this library logs to globalThis.console. You can also provide a custom logger. Most logging libraries are supported, including pino, winston, bunyan, consola, signale, and @std/log. If your logger doesn't work, please open an issue.

When providing a custom logger, the logLevel option still controls which messages are emitted, messages below the configured level will not be sent to your logger.

import Scorecard from 'scorecard-ai';

import pino from 'pino';

const logger = pino();

const client = new Scorecard({ logger: logger.child({ name: 'Scorecard' }), logLevel: 'debug', // Send all messages to pino, allowing it to filter });

Making custom/undocumented requests

This library is typed for convenient access to the documented API. If you need to access undocumented endpoints, params, or response properties, the library can still be used.

Undocumented endpoints

To make requests to undocumented endpoints, you can use client.get, client.post, and other HTTP verbs. Options on the client, such as retries, will be respected when making these requests.

await client.post('/some/path', {

body: { some_prop: 'foo' }, query: { some_query_arg: 'bar' }, });

Undocumented request params

To make requests using undocumented parameters, you may use // @ts-expect-error on the undocumented parameter. This library doesn't validate at runtime that the request matches the type, so any extra values you send will be sent as-is.

client.runs.create({

// ... // @ts-expect-error baz is not yet public baz: 'undocumented option', });

For requests with the GET verb, any extra params will be in the query, all other requests will send the extra param in the body.

If you want to explicitly send an extra argument, you can do so with the query, body, and headers request options.

Undocumented response properties

To access undocumented response properties, you may access the response object with // @ts-expect-error on the response object, or cast the response object to the requisite type. Like the request params, we do not validate or strip extra properties from the response from the API.

Customizing the fetch client

By default, this library expects a global fetch function is defined.

If you want to use a different fetch function, you can either polyfill the global:

import fetch from 'my-fetch';

globalThis.fetch = fetch;

Or pass it to the client:

import Scorecard from 'scorecard-ai';

import fetch from 'my-fetch';

const client = new Scorecard({ fetch });

Fetch options

If you want to set custom fetch options without overriding the fetch function, you can provide a fetchOptions object when instantiating the client or making a request. (Request-specific options override client options.)

import Scorecard from 'scorecard-ai';

const client = new Scorecard({ fetchOptions: { // RequestInit options }, });

Configuring proxies

To modify proxy behavior, you can provide custom fetchOptions that add runtime-specific proxy options to requests:

Node [docs]

im

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