Run SQL against Snowflake — execute statements, poll async results, and manage them via the Snowflake SQL API v2.
Snowflake ships in the w6w first-party pack. It declares 5 actions, 2 health checks, and the host runs its code in a sandbox that never sees the credential.
io.w6w.snowflakeSnowflake is a cloud data warehouse, and this app runs SQL against it over Snowflake’s own SQL API — submitting a statement, polling for its result once it finishes, and cancelling one still running. It is the app to reach for when a workflow needs to query or write to a warehouse directly, whether that is pulling a report, loading data, or triggering a stored procedure, without standing up a database driver.
Because a query can take longer than a single request allows, results are fetched asynchronously and support pagination for large result sets. Two read-only conveniences round it out: listing the databases and warehouses visible to the connected account, both of which work without needing an active warehouse selected, since they are metadata operations rather than data queries. The app deliberately stays narrow — a statement-execution surface rather than a full CRUD layer — leaving schema and object management to SQL itself.
Three routes to the same 5 actions. The Workflow tab is generated from Snowflake's own manifest and carries its real ids, so it is copy-pasteable; the Code and CLI examples are the same call for any action on any app, so every app-specific value in them is a blank you fill in.
statement-execute Run a SQL statement via the Snowflake SQL API v2. Snowflake executes synchronously for up to ~45 seconds; a statement still running past that (or submitted with Run Asynchronously) comes back with status "running" and a statementHandle — poll it with Get Statement.
statement-get Poll a statement submitted with Execute SQL Statement (or a Run Asynchronously one) by its handle. Still "running" until Snowflake finishes; large result sets are split into partitions Snowflake tells you about in resultSetMetaData.partitionInfo.
A workflow step names the app and the action, and the editor fills in the
connection when you pick one. This is the Step shape from the
workflow spec, carrying Snowflake's real ids.
{
"manifestVersion": "2",
"name": "snowflake-example",
"steps": [
{
"id": "statement-execute",
"uses": {
"app": "io.w6w.snowflake",
"action": "statement-execute",
"connection": "conn_YOUR_CONNECTION_ID"
},
"with": {
"statement": "<statement>"
}
}
]
}statement-execute database-list statement-get warehouse-list +1 more action available
Every app-specific value here is a blank you have to fill in. An
app action is reached through the connection that authenticates it, so the
address is a connection id, not the app id — and connections belong to your account,
so a public page cannot know yours. Create one for Snowflake, then fill in
the three blanks: conn_YOUR_CONNECTION_ID, the action key, and the
parameters that action declares. The call itself is real — the shape is transcribed
from the studio's own snippet builder, which prints the same kind of blanks — but
nothing in it is specific to Snowflake. The Workflow tab is where this app's
real ids are.
npm install @w6w/sdkyarn add @w6w/sdkpnpm add @w6w/sdkdeno add npm:@w6w/sdkimport { W6wClient, isActionRun } from "@w6w/sdk";
// Reads W6W_BASE_URL and W6W_TOKEN from the environment when omitted.
const client = new W6wClient();
const envelope = await client.run({
urn: "conn_YOUR_CONNECTION_ID",
action: "statement-execute",
payload: {
statement: "<value>",
// warehouse: "<value>",
// database: "<value>",
// schema: "<value>",
// role: "<value>",
// timeout: "<value>",
// runAsync: "<value>",
// bindings: "<value>",
},
});
if (isActionRun(envelope)) console.log(envelope.value); npm install -g @w6w/cli w6w run conn_YOUR_CONNECTION_ID --action statement-execute --payload '{"statement":"<value>"}' Give an AI agent Snowflake — without giving it Snowflake's credentials. One MCP endpoint exposes every app, function and workflow the caller is entitled to, as tools it can discover and run. Access is granted per team while we onboard.
One tool call{
"name": "w6w_invoke",
"arguments": {
"ref": "app:io.w6w.snowflake#statement-execute",
"input": {
"statement": "<statement>"
}
}
}
Every tool names its target with a single ref. The
app: form above doesn't name a connection at all — the
host resolves which of the caller's Snowflake connections to sign
with, and refuses rather than guesses when the answer is ambiguous.
The token is attached host-side, at the moment of the call. It is never a tool argument, never in the model's context, and never in a transcript — so a prompt injection has nothing to exfiltrate.
Tools are derived per end user from what that person has actually connected and is entitled to — not one shared bot identity carrying the union of everyone's access.
Multi-step work runs on the workflow engine and returns a run handle the agent can poll — retries, branching and state survive the conversation that started them.
Snowflake's declared health checks are on the surface too, so an agent can tell "the vendor is down" from "your credential expired" before it burns a retry on either.
The MCP surface is part of the hosted platform. Snowflake itself is MIT, and the runtime that executes it is source-available (FSL).
Snowflake declares its own checks, so its health is a property of the app rather than something the host guesses at.
Reads status.snowflake.com's Atom history feed for open (non-Resolved) incidents.
Unauthenticated POST to this connection's Snowflake account host. A 401/403 passes — it proves the account resolves and the SQL API is answering; credential validity is the auth:key-pair check's job.