validate
Validate an artifact against a contract (json_schema | openapi_response | sql) via the machinegrade validate API.
type必填artifact必填contract
io.github.machinegrade由 GitHub 帳號 machinegrade 發布v0.1.2更新於 Nov 2, 2026
Deterministic validation for AI-generated artifacts: JSON Schema, OpenAPI response, SQL syntax.
驗證 AI 產生的產物——依 JSON Schema 驗證 JSON、驗證 OpenAPI 回應內容、檢查 SQL 語法——並回傳確定性的通過/失敗結論。
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。
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.github.machinegrade%2Fvalidate/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。把它新增到你客戶端的 mcpServers 設定中。
{
"mcpServers": {
"validate": {
"type": "http",
"url": "https://api.machinegrade.dev/mcp"
}
}
}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.
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.
mcp/server.ts exposes a single tool, validate, that forwards to
POST /v1/validate. Point an MCP-compatible client at it:
The production service also exposes an MCP endpoint directly — no local process, no npm install — via streamable HTTP at:
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:
The stdio adapter via npm (@machinegrade/validate, see above) remains
available for local/offline use or clients without HTTP transport
support.
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:
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.
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.
POST /v1/paid-request (requires X-Api-Key);
you'll be notified when it's live.Every error is typed JSON — {code, message, hint, docs_url} — never a
free-form string:
A verdict ({valid, errors, latency_ms}) is never an error — an
invalid artifact is a normal, expected outcome and returns HTTP 200.
artifact must be a JSON value, not a JSON-encoded string:
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:
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:
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.
The service runs on Cloudflare Workers (Hono + D1 + Workers Static Assets). To self-host on a fresh Cloudflare account:
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.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.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:
/v1/validate request/response shapes, typed error
codes, verdict semantics) is stable — breaking changes only with a
versioned path (/v2/...), never silently.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.
來源:README.md,提交 5dbe141
Validate an artifact against a contract (json_schema | openapi_response | sql) via the machinegrade validate API.
type必填artifact必填contract已滿足適用檢查項的 100%
該評分衡量此收錄條目的完整程度,依據註冊中心條目、端點與公開來源計算得出。它不是對伺服器本身的評價,也不表示伺服器安全或目前可用:可連通性是帶日期的檢查結果,評分也不包含安裝量或使用者評價。
npm installnpm run dev# machinegrade validate listening on http://localhost:8787# 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}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()){ "mcpServers": { "machinegrade-validate": { "command": "npx", "args": ["tsx", "mcp/server.ts"], "cwd": "/path/to/validate", "env": { "SANDBOX_URL": "http://localhost:8787", "SANDBOX_API_KEY": "sk_..." } } }}POST https://api.machinegrade.dev/mcpclaude mcp add --transport http validate https://api.machinegrade.dev/mcp --header "X-Api-Key: sk_..."curl -s -X POST https://api.machinegrade.dev/keys \ -H 'content-type: application/json' \ -d '{"email": "[email protected]"}'{"type": "json_schema", "artifact": {"name": "Ada"}, "contract": {"schema": {"type": "object"}}} // correct{"type": "json_schema", "artifact": "{\"name\": \"Ada\"}", "contract": {"schema": {"type": "object"}}} // wrongwrangler d1 execute machinegrade-validate-db --file=schema.sql # localwrangler d1 execute machinegrade-validate-db --file=schema.sql --remote # productionnpm test # vitest run, in-process via app.request(), MemoryStoragenpm run typecheck # tsc --noEmitwrangler 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