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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Validate

作者:machinegrade版本 0.1.2i★ –i电脑或云端
注册名称io.github.machinegrade/validate

安装

概览

作者提供的说明(英文原文)

Deterministic validation for AI-generated artifacts: JSON Schema, OpenAPI response, SQL syntax.

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: 数据库与数据集
  • 你需要填写:SANDBOX_API_KEY

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在作者的服务器上运行:你向它提出的内容会经过他们的服务器。
  • 需要你自己填写: SANDBOX_URL, SANDBOX_API_KEY

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://api.machinegrade.dev/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": {
    "validate": {
      "command": "npx",
      "args": [
        "-y",
        "@machinegrade/validate"
      ],
      "env": {
        "SANDBOX_URL": "your-value",
        "SANDBOX_API_KEY": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add --transport http validate https://api.machinegrade.dev/mcp

或者在你的电脑上运行

claude mcp add validate --env SANDBOX_URL=your-value --env SANDBOX_API_KEY=your-value -- npx -y @machinegrade/validate

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": {
    "validate": {
      "url": "https://api.machinegrade.dev/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": {
    "validate": {
      "command": "npx",
      "args": [
        "-y",
        "@machinegrade/validate"
      ],
      "env": {
        "SANDBOX_URL": "your-value",
        "SANDBOX_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": {
    "validate": {
      "type": "http",
      "url": "https://api.machinegrade.dev/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": {
    "validate": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@machinegrade/validate"
      ],
      "env": {
        "SANDBOX_URL": "your-value",
        "SANDBOX_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://api.machinegrade.dev/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

  • SANDBOX_URL env
    Base URL of the validate API
  • SANDBOX_API_KEY 机密 必填 env
    API key issued via POST https://api.machinegrade.dev/keys (free tier: 500 calls/month)

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6日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 machinegrade 验证,该账户拥有此仓库

  • … 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“数据库与数据集”中的其他服务器比较i

  • 星标数多于此分类中其他 953 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 953 个服务器的 21% 更新
  • 基础检查结果等于或优于此分类中其他 953 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

Validate 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:SANDBOX_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(0.1.2)于3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:Supabase, MongoDB MCP Server, Elasticsearch MCP Server

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

Supabase

作者:supabase

MCP server for interacting with the Supabase platform

电脑或云端★ 2,993Apache-2.0昨天更新
安装

MongoDB MCP Server

作者:mongodb-js

MongoDB Model Context Protocol Server

在你的电脑上运行★ 1,157Apache-2.0前天更新
安装

MCP server for interacting with Elasticsearch

在你的电脑上运行★ 315Apache-2.014个月前更新
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。

machinegrade validate

Validate AI-generated artifacts against a contract before you act on them:

  • `json_schema` — validate artifact against a JSON Schema (all errors collected).
  • `openapi_response` — validate a response body against the response schema for a given path + method + status in an OpenAPI spec.
  • `sql` — check a SQL string for syntax errors in a given dialect.

Every check returns a verdict, not an error: {valid, errors, latency_ms}, HTTP 200 whether the artifact is valid or not. Only genuinely wrong requests (bad key, unsupported type, malformed body, over your limit) get typed HTTP errors.

Live at https://api.machinegrade.dev — free tier, self-service key, try it in 30 seconds (first example below). Built on Hono; the same codebase runs on Cloudflare Workers (production) and plain Node (local dev), and is MIT-licensed if you'd rather self-host.

Why

Agents that generate JSON, API responses, or SQL need a fast, cheap, machine-checkable pass/fail before they ship the result — cheaper than a full LLM-as-judge call, and deterministic.

Run it locally

npm install

npm run dev

machinegrade validate listening on http://localhost:8787

3 runnable examples

1. curl
# Get an API key (live service — works as-is)

curl -s -X POST https://api.machinegrade.dev/keys \ -H 'content-type: application/json' \ -d '{"email": "you@example.com"}'

=> {"key":"sk_..."}

Validate a JSON artifact against a JSON Schema

curl -s -X POST https://api.machinegrade.dev/v1/validate \ -H 'content-type: application/json' \ -H 'X-Api-Key: sk_...' \ -d '{ "type": "json_schema", "artifact": {"name": "Ada", "age": 30}, "contract": { "schema": { "type": "object", "required": ["name", "age"], "properties": {"name": {"type": "string"}, "age": {"type": "number"}} } } }'

=> {"valid":true,"errors":[],"latency_ms":1}

2. Python (requests)
import requests

base = "http://localhost:8787"

key = requests.post(f"{base}/keys", json={"email": "you@example.com"}).json()["key"]

resp = requests.post( f"{base}/v1/validate", headers={"X-Api-Key": key}, json={ "type": "sql", "artifact": "SELECT id, name FROM users WHERE id = 1", "contract": {"dialect": "mysql"}, }, ) print(resp.status_code, resp.headers.get("X-Calls-Remaining"), resp.json())

3. MCP config snippet

mcp/server.ts exposes a single tool, validate, that forwards to POST /v1/validate. Point an MCP-compatible client at it:

{

"mcpServers": { "machinegrade-validate": { "command": "npx", "args": ["tsx", "mcp/server.ts"], "cwd": "/path/to/validate", "env": { "SANDBOX_URL": "http://localhost:8787", "SANDBOX_API_KEY": "sk_..." } } } }

Connect remotely

The production service also exposes an MCP endpoint directly — no local process, no npm install — via streamable HTTP at:

POST https://api.machinegrade.dev/mcp

It's the same single validate tool as the stdio adapter above. initialize and tools/list work without a key (discovery is anonymous); tools/call requires X-Api-Key (issue one via POST /keys, same as the REST API — the free tier and limits are shared).

With Claude Code:

claude mcp add --transport http validate https://api.machinegrade.dev/mcp --header "X-Api-Key: sk_..."

The stdio adapter via npm (@machinegrade/validate, see above) remains available for local/offline use or clients without HTTP transport support.

Claude Desktop: one-click install

Download the latest .mcpb bundle from Releases and double-click it. Claude Desktop asks for an API key during install and stores it in the OS keychain (macOS Keychain, Windows Credential Manager) rather than in a config file — nothing lands in claude_desktop_config.json.

Issue a free key (500 calls/month) first:

curl -s -X POST https://api.machinegrade.dev/keys \

-H 'content-type: application/json' \ -d '{"email": "you@example.com"}'

The bundle is a thin stdio client over the hosted API: ~34 KB, zero bundled dependencies. If you self-host, point the extension's API base URL setting at your own deployment and the tool talks to that instead.

API

See public/openapi.yaml for the full contract, or /v1/manifest for a machine-readable summary (types, limits, pricing, error codes) once the service is running. /llms.txt is a short pointer for LLM agents.

EndpointInOut
POST /keys{email}{key}
POST /v1/validateheader X-Api-Key, body {type, artifact, contract?}verdict, header X-Calls-Remaining
GET /v1/manifest—capability manifest
GET /statsheader X-Admin-Tokenfunnel: keys_issued, active_callers, repeat_callers_7d, limit_hits, paid_requests
POST /v1/paid-requestheader X-Api-Keyrecords interest in paid access
GET /openapi.yaml, GET /llms.txt—static docs
POST /mcpMCP streamable HTTP, header X-Api-Key for tools/callsee "Connect remotely" above

Pricing

  • Free tier: 500 calls/month per key, 60 calls/minute rate limit.
  • Paid tier: EUR 0.002/call beyond the free tier — opens soon. Request paid access via POST /v1/paid-request (requires X-Api-Key); you'll be notified when it's live.

Errors

Every error is typed JSON — {code, message, hint, docs_url} — never a free-form string:

CodeHTTP statusWhen
INVALID_KEY401X-Api-Key missing or unknown
LIMIT_EXCEEDED402Free-tier monthly limit (500 calls) exceeded
UNSUPPORTED_TYPE400type is not json_schema, openapi_response, or sql
MALFORMED_INPUT400Request body doesn't match the documented shape
RATE_LIMITED429More than 60 calls/minute for a key

A verdict ({valid, errors, latency_ms}) is never an error — an invalid artifact is a normal, expected outcome and returns HTTP 200.

Sending the artifact

artifact must be a JSON value, not a JSON-encoded string:

{"type": "json_schema", "artifact": {"name": "Ada"}, "contract": {"schema": {"type": "object"}}}   // correct

{"type": "json_schema", "artifact": "{\"name\": \"Ada\"}", "contract": {"schema": {"type": "object"}}} // wrong

For type: "sql" the artifact *is* a string — the statement itself.

Because MCP callers stringify values often enough (and did so through Claude Desktop until the tool schema declared artifact's types), the service tolerates the wrong form narrowly: if artifact is a string, the type is json_schema or openapi_response, and the contract's top-level schema declares types that exclude `string`, the string is JSON-decoded before validation and the verdict carries "decoded_from_string": true. The field is additive; {valid, errors, latency_ms} is unchanged.

It deliberately does not decode otherwise, because a string artifact is often legitimate:

SentContract schemaResult
"42"{"type": "number"}decoded to 42, valid: true, decoded_from_string: true
"42"{"type": "string"}left alone, valid: true
"{\"a\":1}"{"type": "string"}left alone, valid: true
"{\"a\":1}"{"required": ["a"]}left alone — no top-level type, intent unknown

Storage

src/storage.ts defines a Storage interface with two implementations:

  • MemoryStorage — full in-memory implementation, used for npm run dev and the test suite.
  • D1Storage — real Cloudflare D1 binding, backed by schema.sql (keys, events tables). Used in production; the Workers entry point in src/index.ts builds it from the DB binding on first request.

Apply schema.sql to a new D1 database with:

wrangler d1 execute machinegrade-validate-db --file=schema.sql          # local

wrangler d1 execute machinegrade-validate-db --file=schema.sql --remote # production

Testing

npm test          # vitest run, in-process via app.request(), MemoryStorage

npm run typecheck # tsc --noEmit

Tests cover: key issuance, happy + fail cases for each validator, typed 401/400/402/429 errors, the metering limits (both injectable in tests so they don't require looping hundreds of real requests), and /stats funnel counts.

Deploy

The service runs on Cloudflare Workers (Hono + D1 + Workers Static Assets). To self-host on a fresh Cloudflare account:

wrangler d1 create machinegrade-validate-db   # copy the returned database_id into wrangler.toml

wrangler d1 execute machinegrade-validate-db --file=schema.sql --remote wrangler secret put ADMIN_TOKEN wrangler deploy

Then bind a custom domain (e.g. api.machinegrade.dev) to the Worker via the Cloudflare dashboard or wrangler. CI can deploy on push to main once CLOUDFLARE_API_TOKEN and CLOUDFLARE_ACCOUNT_ID repo secrets are set and the deploy job in .github/workflows/ci.yml is uncommented.

Two things worth knowing about the Workers port:

  • GET /openapi.yaml and GET /llms.txt are served by the ASSETS binding ([assets] in wrangler.toml, pointing at public/) — Cloudflare serves them directly, without invoking the Worker. The routes in src/index.ts are a fallback for local Node dev/tests, where there's no ASSETS binding.
  • The json_schema and openapi_response validators use @cfworker/json-schema, not ajv: ajv compiles schemas via new Function(...), which the Workers runtime disallows, and schemas here arrive dynamically per request (from the caller), so they can't be precompiled at build time either.

Status

Early stage, honestly so: this service is live and free-tier usage is real, and we're measuring whether it earns a paid tier. What you can rely on:

  • The API contract (/v1/validate request/response shapes, typed error codes, verdict semantics) is stable — breaking changes only with a versioned path (/v2/...), never silently.
  • The free tier (500 calls/month) stays.
  • If we ever sunset the service, keys keep working for 90 days after the announcement, and the validators are open source in this repo — you can self-host the same behavior.

Feedback and integration stories are the most valuable thing you can give us right now: open an issue or use POST /v1/paid-request if you need more than the free tier.

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