Warehouse MCP

Production MCP server for Postgres, Oracle, Snowflake, BigQuery, Redshift, DuckDB, MotherDuck.

Connector by kalehdoo · GitHub account verified by the MCP Registry

IndexedApache-2.0Local (stdio)

Install

Works with Claude Code, Codex, VS Code, Cursor, Windsurf, Claude Desktop. Read the repository before you give any tool access to your data.

npx agentmarket install connector/kalehdoo-warehouse-mcp

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

Production MCP server for Postgres, Oracle, Snowflake, BigQuery, Redshift, DuckDB, MotherDuck.

Reviews

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Permissions

What this server can do and what it asks for, from its tool list and install config. Checked Oct 25, 2026.

Tools: 14 read · 0 write · 0 delete · 2 not yet classified
Secrets: 5 (API keys, tokens or passwords)
Install scripts: Not scanned yet
Runs as: Node.js package

Tools by what they do 16

Read from the source code; the running server may list different tools.

Read 14 · Look things up without changing anything.

column_stats
count_rows
describe_table
find_columns
get_foreign_keys
get_view_definition
glossary_lookup
list_schemas
list_tables
sample_table
schema_lookup
search_value

Show 2 more tools

table_lookup
top_values

Not yet classified 2 · We could not tell from the name and description.

query
time_series

Secrets and settings it asks for

Secrets: values you paste in that let it act as you.

GOOGLE_APPLICATION_CREDENTIALS
MCP_API_KEYS
MOTHERDUCK_TOKEN
ORACLE_PASSWORD
PG_PASSWORD

Other settings (environment variables or headers).

BIGQUERY_PROJECT
DUCKDB_PATH
GUARDRAIL_PII_MASK
MCP_RATE_LIMIT_RPM
MCP_TRANSPORT
ORACLE_CONNECT_STRING
ORACLE_USER
PG_DATABASE
PG_HOST
PG_USER
SNOWFLAKE_ACCOUNT
SNOWFLAKE_PRIVATE_KEY_PATH

Show 2 more settings

SNOWFLAKE_USER
WAREHOUSE_TYPE

Tools (16)

Read from the source code; the running server may differ. Descriptions are the server’s own words; hidden characters are shown as [U+…].

column_stats
Return min, max, null count, distinct count, and (for numeric columns) average for one column.
count_rows
Return the row count for a table. Cheap (single COUNT(*)), and answers 'how big is this?' before the agent decides whether to scan it. Especially useful on cloud warehouses where bytes scanned costs money.
describe_table
Return column names, types, and nullability for a table or view.
find_columns
Search column names across the warehouse using a SQL LIKE pattern (use % for wildcards). Returns matching (schema, table, column, type) tuples. Optionally scope to one schema. On BigQuery, schema is required because INFORMATION_SCHEMA is per-dataset.
get_foreign_keys
Return declared foreign-key relationships (from_schema/from_table/from_column → to_schema/to_table/to_column). Optionally scope to a schema or a single table. BigQuery only returns informational FKs that were explicitly declared.
get_view_definition
Return the SQL body of a view. Useful when business logic lives in views — the model can reason about a view's semantics by reading its definition.
glossary_lookup
Look up business-glossary terms from the semantic layer. Call with no argument to list every term with a short definition. Call with `term` to get the full definition, optional SQL, related terms, and tags. Use this BEFORE writing SQL for domain questions — it disambiguates words like 'active customer', 'revenue', 'MRR'.
list_schemas
List all schemas (or BigQuery datasets) visible to the configured warehouse role.
list_tables
List tables and views in a given schema.
query
Execute a single read-only SELECT against the configured warehouse. Returns columns and rows. A LIMIT (or FETCH FIRST on Oracle) is auto-applied if the SQL omits one.
sample_table
Return up to N sample rows from a table (capped at 100).
schema_lookup
Look up schema-level documentation from the semantic layer. Call with no argument for a summary of every documented schema (purpose, owner, refresh cadence, sensitivity, table count). Call with `schema` for that schema's doc plus the list of documented tables in it. Use this to pick the right schema for a question before drilling into specific tables.
search_value
Find a literal value across the text columns of a table (exact match). Scans up to 10 text columns and returns up to 100 hits.
table_lookup
Look up a documented table's full semantic profile — description, owner, refresh cadence, sensitivity, and per-column descriptions / metadata. Read this BEFORE constructing a query against the table. Both `schema` and `table` are required.
time_series
Group a table by a date/timestamp column into buckets (hour/day/week/month/quarter/year) and return a count or aggregate per bucket. Saves the agent from constructing dialect-specific date truncation. Returns rows ordered chronologically.

Show 1 more tools

top_values
Return the top-K most frequent non-null values in a column with their counts.

Signals

Stars: 0
Forks: 0
Open issues: 0
Last commit: Jun 18, 2026 (4 months ago)
Last release: May 6, 2026 (5 months ago)

From GitHub (fetched Oct 24, 2026).

Details

Registry name: io.github.kalehdoo/warehouse-mcp
Version: 0.4.2
Auth: API key
Packages: npm warehouse-mcp
License: Apache-2.0
Repository: github.com/kalehdoo/warehouse-mcp
Website: github.com/kalehdoo/warehouse-mcp
First seen: Oct 24, 2026
Last checked: Oct 24, 2026
Source: Official MCP Registry github-graphql

Cite this page

Warehouse MCP. Agent Mart. https://agentmart.dev/connectors/kalehdoo-warehouse-mcp (last updated 2026-10-24)