Scorecard

io.scorecardPublished by scorecard.ioOfficial publisherv2.1.1Updated Oct 24, 2026

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

VerifiedStreamable HTTPWeb executableDeveloper ToolsAI & ML

Overview

AI-generated overview

Scorecard MCP server that lets an assistant work with the Scorecard API to evaluate and optimize LLM systems.

What you can do
  • Explore Scorecard API endpoints and make test requests against them
  • Create and inspect evaluation runs, testsets and testcases
  • Use Scorecard documentation to help integrate the Scorecard SDK into an application
  • Read paginated list results and raw response data from the API
When to use it
Useful when you are building or tuning LLM systems with Scorecard and want an assistant to inspect runs, testsets and testcases, or to try API calls and look up documentation while integrating the SDK.
Requirements
Either the remote endpoint at mcp.scorecard.io with OAuth, or the local npm package scorecard-ai-mcp over stdio. A Scorecard API key supplied as SCORECARD_API_KEY, obtained from the Scorecard account settings. Network access to the Scorecard API.
Before you install
Requires a Scorecard API key, which grants access to your Scorecard account data. The server can make requests that create or change resources such as runs, so review write actions before approving them. At debug log level, request and response bodies may be logged with sensitive data visible.

Installation

In SourceWeft

  1. Open Scorecard in the dashboard and add it to a workspace.
  2. Connect the required credentials. They are stored privately and never shown on public pages.
  3. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/io.scorecard%2Fmcp/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config. The client completes OAuth sign-in on first connect.

{
  "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:

[Image] 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,  },});

[Image] Bun [docs]

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

[Image] 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.

Source: README.md at commit f959fea

Tools

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Version history

1
  1. v2.1.1LatestSep 16, 2026

Score

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