Production MCP server for Postgres, Oracle, Snowflake, BigQuery, Redshift, DuckDB, MotherDuck.
Warehouse MCP server exists for a simple reason — assistants are far more useful when they can act on Warehouse directly instead of describing what you should do. Production MCP server for Postgres, Oracle, Snowflake, BigQuery, Redshift, DuckDB, MotherDuck.
Production MCP (Model Context Protocol) server for your data warehouse. Read-only enforcement, five-tier role-based access, optional warehouse-role impersonation (for native RLS / CLS), JSONL audit log, optional output PII masking, optional semantic-metadata layer (glossary + table docs) with per-session toggle. Self-host the Docker image, install via npx, or wait for the upcoming managed cloud variant.
Once Warehouse is connected, these are the calls the assistant has available:
query — Execute a SELECT (validator-enforced read-only, dialect-aware)find_columns — Search column names across the warehouse with a LIKE patternget_foreign_keys — Discover declared FK relationships for safe joinsget_view_definition — Read the SQL body of a view (where business logic lives)time_series — Bucket by hour/day/week/month/quarter/year — dialect-correct everywheresearch_value — Find a literal across a table's text columnsglossary_lookup — Read business-glossary terms from the semantic layer (in-memory, no warehouse I/O)schema_lookup — Read schema-level docs — purpose, owner, refresh, table listtable_lookup — Read full semantic doc for one table — description + column metadataBeing a remote server, there is no local install. You register the endpoint with your client, authorise it once, and the tools appear.
You will need 3 environment variables: SNOWFLAKE_PRIVATE_KEY_PATH, DUCKDB_PATH, MOTHERDUCK_TOKEN. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.
Plenty of database access servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. Warehouse's toolset — query, find_columns, get_foreign_keys and 6 more — is a fair guide to whether it matches your workflow. It is maintained by kalehdoo; worth a glance at recent repository activity before you build anything load-bearing on it.
We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.
| Tool | What it does |
|---|---|
| query | Execute a SELECT (validator-enforced read-only, dialect-aware) |
| find_columns | Search column names across the warehouse with a LIKE pattern |
| get_foreign_keys | Discover declared FK relationships for safe joins |
| get_view_definition | Read the SQL body of a view (where business logic lives) |
| time_series | Bucket by hour/day/week/month/quarter/year — dialect-correct everywhere |
| search_value | Find a literal across a table's text columns |
| glossary_lookup | Read business-glossary terms from the semantic layer (in-memory, no warehouse I/O) |
| schema_lookup | Read schema-level docs — purpose, owner, refresh, table list |
| table_lookup | Read full semantic doc for one table — description + column metadata |
{
"mcpServers": {
"warehouse": {
"command": "npx",
"args": ["-y", "warehouse-mcp"],
"env": {
"SNOWFLAKE_PRIVATE_KEY_PATH": "your-value",
"DUCKDB_PATH": "your-value",
"MOTHERDUCK_TOKEN": "your-value"
}
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
| Variable | Description | Required |
|---|---|---|
| SNOWFLAKE_PRIVATE_KEY_PATH | Credential the server authenticates with. | Yes |
| DUCKDB_PATH | Filesystem location the server is allowed to use. | Optional |
| MOTHERDUCK_TOKEN | Credential the server authenticates with. | Yes |
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