Validate

io.github.machinegrade由 GitHub 账号 machinegrade 发布v0.1.2更新于 Nov 2, 2026

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

已验证Streamable HTTP可网页运行开发者工具数据与分析

概览

AI 生成的概览

校验 AI 生成的产物——按 JSON Schema 校验 JSON、校验 OpenAPI 响应体、检查 SQL 语法——并返回确定性的通过/失败结论。

可以做什么
  • 按 JSON Schema 校验 JSON 产物并汇总全部错误
  • 按 OpenAPI 规范中指定路径、方法和状态码的响应 schema 校验响应体
  • 按指定方言检查 SQL 字符串的语法错误
  • 返回包含是否有效、错误列表和耗时的结论,以及剩余调用次数
适用场景
当助手生成 JSON、API 响应或 SQL,并希望在据此行动或交付前做一次廉价、确定性的检查,而不是调用完整的 LLM 评审时适用。
运行要求
可使用托管的远程端点,或通过 stdio 运行本地 npm 包 @machinegrade/validate。调用工具需要 API 密钥,通过 SANDBOX_API_KEY 或 X-Api-Key 请求头提供;免费密钥需用邮箱向服务的密钥接口申请。本地使用时用 SANDBOX_URL 指定 API 基础地址。需要能访问该服务的网络。
安装前请注意
调用工具需要与邮箱绑定的 API 密钥;免费额度为每月 500 次、每分钟 60 次,超出月度上限会返回需要付费的错误。超出免费额度后的按次付费方案尚在计划中。产物和契约会发送到第三方托管服务,请勿发送密钥或敏感数据。服务处于早期阶段,可能停止运营,但承诺公告后密钥仍可使用 90 天。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Validate,将其添加到工作区。
  2. 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.github.machinegrade%2Fvalidate/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。

{
  "mcpServers": {
    "validate": {
      "type": "http",
      "url": "https://api.machinegrade.dev/mcp"
    }
  }
}

README

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

bash
npm installnpm run dev# machinegrade validate listening on http://localhost:8787

3 runnable examples

1. curl

bash
# 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": "[email protected]"}'# => {"key":"sk_..."}
# Validate a JSON artifact against a JSON Schemacurl -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)

python
import requests
base = "http://localhost:8787"
key = requests.post(f"{base}/keys", json={"email": "[email protected]"}).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:

json
{  "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:

bash
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:

bash
curl -s -X POST https://api.machinegrade.dev/keys \  -H 'content-type: application/json' \  -d '{"email": "[email protected]"}'

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:

jsonc
{"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:

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

Testing

bash
npm test          # vitest run, in-process via app.request(), MemoryStoragenpm 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:

bash
wrangler d1 create machinegrade-validate-db   # copy the returned database_id into wrangler.tomlwrangler d1 execute machinegrade-validate-db --file=schema.sql --remotewrangler secret put ADMIN_TOKENwrangler 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.

来源:README.md,提交 5dbe141

工具

1

validate

Validate an artifact against a contract (json_schema | openapi_response | sql) via the machinegrade validate API.

输入参数type必填artifact必填contract

版本历史

1
  1. v0.1.2最新Sep 16, 2026

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