Supabase
MCP server for interacting with the Supabase platform
Descripción del creador (original en inglés)
Deterministic validation for AI-generated artifacts: JSON Schema, OpenAPI response, SQL syntax.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
SANDBOX_URL, SANDBOX_API_KEYLos valores marcados como secretos son llaves de tu cuenta. Nunca los compartas ni los pegues en un chat.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Funciona en Claude para web, escritorio y móvil:
https://api.machinegrade.dev/mcpAbre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"validate": {
"command": "npx",
"args": [
"-y",
"@machinegrade/validate"
],
"env": {
"SANDBOX_URL": "your-value",
"SANDBOX_API_KEY": "your-value"
}
}
}
}Ejecuta esto en tu terminal
claude mcp add --transport http validate https://api.machinegrade.dev/mcpclaude mcp add validate --env SANDBOX_URL=your-value --env SANDBOX_API_KEY=your-value -- npx -y @machinegrade/validateCompleta los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"validate": {
"url": "https://api.machinegrade.dev/mcp"
}
}
}Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"validate": {
"command": "npx",
"args": [
"-y",
"@machinegrade/validate"
],
"env": {
"SANDBOX_URL": "your-value",
"SANDBOX_API_KEY": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"validate": {
"type": "http",
"url": "https://api.machinegrade.dev/mcp"
}
}
}Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"validate": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@machinegrade/validate"
],
"env": {
"SANDBOX_URL": "your-value",
"SANDBOX_API_KEY": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
ChatGPT solo se conecta a servidores en internet:
https://api.machinegrade.dev/mcpLos nombres de los menús pueden variar un poco según el plan y con el tiempo.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
SANDBOX_URL envEsta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Todavía no hemos leído la lista de herramientas de este servidor; revisamos los endpoints por turnos.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub machinegrade, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Aún sin revisar; revisamos los endpoints por turnos
Aún sin revisar; revisamos los endpoints por turnos
Aún sin revisar; leemos la lista de herramientas cuando revisamos el endpoint
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
Debes completar: SANDBOX_API_KEY
Funciona de las dos formas: instálalo en tu computadora o conéctate a la versión en la nube.
El repo de GitHub cambió por última vez –, y la última versión (0.1.2) llegó al registro hace 3 meses.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. Se conecta por URL, así que también funcionan las apps que aceptan servidores MCP remotos, como ChatGPT en modo desarrollador.
En la misma categoría: Supabase, MongoDB MCP Server, Elasticsearch MCP Server
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
MCP server for interacting with the Supabase platform
MongoDB Model Context Protocol Server
MCP server for interacting with Elasticsearch
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
Validate AI-generated artifacts against a contract before you act on them:
artifact against a JSON Schema (all errors collected).path + method + status in an OpenAPI spec.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.
npm install
npm run dev
# 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"}'
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"}} } } }'
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())
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_..." } } } }
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.
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.
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.
| Endpoint | In | Out |
|---|---|---|
POST /keys | {email} | {key} |
POST /v1/validate | header X-Api-Key, body {type, artifact, contract?} | verdict, header X-Calls-Remaining |
GET /v1/manifest | — | capability manifest |
GET /stats | header X-Admin-Token | funnel: keys_issued, active_callers, repeat_callers_7d, limit_hits, paid_requests |
POST /v1/paid-request | header X-Api-Key | records interest in paid access |
GET /openapi.yaml, GET /llms.txt | — | static docs |
POST /mcp | MCP streamable HTTP, header X-Api-Key for tools/call | see "Connect remotely" above |
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:
| Code | HTTP status | When |
|---|---|---|
INVALID_KEY | 401 | X-Api-Key missing or unknown |
LIMIT_EXCEEDED | 402 | Free-tier monthly limit (500 calls) exceeded |
UNSUPPORTED_TYPE | 400 | type is not json_schema, openapi_response, or sql |
MALFORMED_INPUT | 400 | Request body doesn't match the documented shape |
RATE_LIMITED | 429 | More 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.
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:
| Sent | Contract schema | Result |
|---|---|---|
"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 |
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
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.
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.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.