Scorecard

io.scorecard由 scorecard.io 發布官方發布者v2.1.1更新於 Oct 24, 2026

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

已驗證Streamable HTTP可網頁執行開發者工具AI 與機器學習

概覽

AI 產生的概覽

Scorecard MCP 伺服器,讓助理透過 Scorecard API 評估與最佳化 LLM 系統。

可以做什麼
  • 瀏覽 Scorecard API 端點並送出測試請求
  • 建立與檢視評估執行、測試集與測試案例
  • 借助 Scorecard 文件協助將 Scorecard SDK 整合進應用程式
  • 讀取分頁清單結果與 API 原始回應資料
適用情境
在使用 Scorecard 建置或調校 LLM 系統時,希望助理檢視執行、測試集與測試案例,或在整合 SDK 時試打 API 並查閱文件。
執行需求
可使用 mcp.scorecard.io 遠端端點(OAuth 驗證),或透過 stdio 執行本機 npm 套件 scorecard-ai-mcp。需要 Scorecard API 金鑰,以 SCORECARD_API_KEY 提供,可於 Scorecard 帳戶設定中取得。需要連線至 Scorecard API 的網路存取。
安裝前請注意
需要 Scorecard API 金鑰,該金鑰可存取你的 Scorecard 帳戶資料。伺服器可送出建立或修改資源(例如執行)的請求,核准前請確認寫入操作。在 debug 日誌層級下,請求與回應內容可能被記錄,敏感資料可能外洩。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Scorecard,將其新增到工作區。
  2. 連接 所需的 憑證。它們會被私密儲存,絕不會在公開頁面上展示。
  3. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/io.scorecard%2Fmcp/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。 客戶端會在首次連接時完成 OAuth 登入。

{
  "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:

[圖片] 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,  },});

[圖片] Bun [docs]

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

[圖片] 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.

來源:README.md,提交 f959fea

工具

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版本歷史

1
  1. v2.1.1最新Sep 16, 2026

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其他 Scorecard 整合