Integrate Snowflake MCP server into your Slack workspace for instant access to your AI agent.
Tools that your AI agent can use through this MCP server to interact with Snowflake
Start a Snowflake session and return it in serialized form, so subsequent Snowflake actions can run in the same session (preserving temporary tables, USE context, and session parameters) by passing it to their Session prop. The returned value contains session auth tokens — treat it as sensitive. Sessions expire server-side after ~4 hours or your account's idle timeout. See the documentation
Retrieves available options for the Warehouse Name field.
Retrieves available options for the User Name field.
Retrieves available options for the Database field.
Insert a row into a table
Insert multiple rows into a table
Execute a custom Snowflake query. See our docs to learn more about working with SQL in Pipedream.
Execute a Snowflake query inside a session started by the Start SQL Session action, so it shares that session's state — temporary tables, USE context, and session parameters — with the other queries in the same session. Pass the serialized session from Start SQL Session to the Session prop. Note: to preserve the session this query runs on a direct connection and therefore does NOT egress from the shared static IP (use_pd_sql_proxy); if your Snowflake network policy allowlists only the static IP, use Execute SQL Query instead. See our docs to learn more about working with SQL in Pipedream.
Execute a SQL Query. See our docs to learn more about working with SQL in Pipedream.