Scorecard

io.scorecard由 scorecard.io 发布官方发布者v2.1.1更新于 Oct 24, 2026

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

已验证Streamable HTTP可网页运行开发者工具AI 与机器学习

概览

AI 生成的概览

Scorecard MCP 服务器,让助手通过 Scorecard API 评估和优化 LLM 系统。

可以做什么
  • 浏览 Scorecard API 端点并发送测试请求
  • 创建和查看评估运行、测试集与测试用例
  • 借助 Scorecard 文档协助将 Scorecard SDK 集成到应用中
  • 读取分页列表结果和 API 原始响应数据
适用场景
在使用 Scorecard 构建或调优 LLM 系统时,希望助手查看运行、测试集和测试用例,或在集成 SDK 时试调 API 并查阅文档。
运行要求
可使用 mcp.scorecard.io 远程端点(OAuth 认证),或通过 stdio 运行本地 npm 包 scorecard-ai-mcp。需要 Scorecard API 密钥,通过 SCORECARD_API_KEY 提供,可在 Scorecard 账户设置中获取。需要访问 Scorecard API 的网络连接。
安装前请注意
需要 Scorecard API 密钥,该密钥可访问你的 Scorecard 账户数据。服务器可发出创建或修改资源(如运行)的请求,批准前请确认写入操作。在 debug 日志级别下,请求和响应正文可能被记录,敏感数据可能可见。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Scorecard,将其添加到工作区。
  2. 连接 所需的 凭据。它们会被私密存储,绝不会在公开页面上展示。
  3. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/io.scorecard%2Fmcp/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。 客户端会在首次连接时完成 OAuth 登录。

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

README

Scorecard TypeScript API Library

[NPM version] [npm bundle size]

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.

[Add to Cursor] [Install in VS Code]

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

Installation

sh
npm install scorecard-ai

Usage

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

js
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:

ts
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:

ts
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:

js
// 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:

ts
// 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:

ts
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:

ts
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.

ts
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)
ts
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.

ts
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.

ts
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.

ts
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:

ts
import fetch from 'my-fetch';
globalThis.fetch = fetch;

Or pass it to the client:

ts
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.)

ts
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:

[图片] Node [docs]

ts
import Scorecard from 'scorecard-ai';import * as undici from 'undici';
const proxyAgent = new undici.ProxyAgent('http://localhost:8888');const client = new Scorecard({  fetchOptions: {    dispatcher: proxyAgent,  },});

[图片] Bun [docs]

ts
import Scorecard from 'scorecard-ai';
const client = new Scorecard({  fetchOptions: {    proxy: 'http://localhost:8888',  },});

[图片] Deno [docs]

ts
import Scorecard from 'npm:scorecard-ai';
const httpClient = Deno.createHttpClient({ proxy: { url: 'http://localhost:8888' } });const client = new Scorecard({  fetchOptions: {    client: httpClient,  },});

Frequently Asked Questions

Semantic versioning

This package generally follows SemVer conventions, though certain backwards-incompatible changes may be released as minor versions:

  1. Changes that only affect static types, without breaking runtime behavior.
  2. Changes to library internals which are technically public but not intended or documented for external use. (Please open a GitHub issue to let us know if you are relying on such internals.)
  3. Changes that we do not expect to impact the vast majority of users in practice.

We take backwards-compatibility seriously and work hard to ensure you can rely on a smooth upgrade experience.

We are keen for your feedback; please open an issue with questions, bugs, or suggestions.

Requirements

TypeScript >= 4.9 is supported.

The following runtimes are supported:

  • Web browsers (Up-to-date Chrome, Firefox, Safari, Edge, and more)
  • Node.js 20 LTS or later (non-EOL) versions.
  • Deno v1.28.0 or higher.
  • Bun 1.0 or later.
  • Cloudflare Workers.
  • Vercel Edge Runtime.
  • Jest 28 or greater with the "node" environment ("jsdom" is not supported at this time).
  • Nitro v2.6 or greater.

Note that React Native is not supported at this time.

If you are interested in other runtime environments, please open or upvote an issue on GitHub.

Contributing

See the contributing documentation.

来源:README.md,提交 f959fea

工具

0
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版本历史

1
  1. v2.1.1最新Sep 16, 2026

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