Overview

The Revefi MCP server exposes the tools listed on this page to MCP-compatible clients such as Claude Code, Cursor, and Claude Desktop. To connect a client, follow MCP Setup.

Which tools your client sees depends on the warehouse connected to your Revefi account:

Tools that change data in your account carry a Modifies data note. Most MCP clients ask you to approve these calls before they run.

Times are in epoch seconds (UTC) unless stated otherwise.

Raden

Ask questions of Raden, Revefi's AI agent for data engineering.

ask_raden

Ask Raden a natural-language question about your data, warehouse, spend, usage, or data quality.

If Raden answers quickly, the answer is returned directly with status complete. For a longer question, the tool returns a session_id with status running. Call get_raden_session_status with that session_id to fetch the answer once it's ready.

get_raden_session_status

Check on a question started by ask_raden. Returns status running while Raden is still working, or complete with the answer once it's done.

Feed

get_feed_items

List items from your Revefi feed — data quality incidents, spend and usage alerts, digests, and newly discovered tables — newest first.

Returns { items[], offset, limit, has_more }. Each item has id, created_utc_seconds, title, summary, severity, status, url, and an entities map naming the databases, schemas, and warehouses it concerns. When has_more is true, call again with offset increased by limit.

Table SLA monitors

A table SLA monitor alerts when a table hasn't been updated within a set number of minutes. See Setting Table SLA for how these monitors work in the Revefi app.

list_sla_monitors

List table SLA monitors, optionally filtered by table location.

Returns { monitors[], truncated }. Each monitor has id, database, schema, table, dataSourceId, displayName, slaMinutes, collectionFrequency, and isMuted. When truncated is true, narrow the filters or raise limit.

get_sla_monitor

Get a single table SLA monitor by its ID.

Returns id, database, schema, table, dataSourceId, displayName, description, slaMinutes, collectionFrequency, and isMuted.

create_sla_monitor

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Modifies data

Creates a monitor that sends alerts. Confirm the table and threshold before running it.

Create a table SLA monitor that alerts when the table hasn't been updated within sla_minutes. Returns the ID of the new monitor.

update_sla_monitor

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Modifies data

Changes the alert threshold of an existing monitor.

Update an existing monitor's alert threshold, collection frequency, or both. The monitor's table, name, and description can't be changed with this tool.

This tool rejects:

• Muted monitors — unmute the monitor first.
• Monitors on a specific-times schedule — edit these in the Revefi app.

get_sla_monitor_evaluations

Get the evaluation history for one table SLA monitor: whether each check passed or breached, and when. Identify the monitor by monitor_id or by table (database_name, schema_name, table_name). If a table matches more than one monitor, the tool returns the candidates instead of guessing.

Returns at most 60 evaluations, oldest first. The latest_status field is one of:

get_all_sla_monitor_evaluations

Get the current SLA status of all your table SLA monitors — use this to find which tables are breaching their SLA. Returns latest_status and sla_minutes for each monitor, without history unless evaluations_per_monitor is set. For the full history of one monitor, use get_sla_monitor_evaluations.

A monitor marked unavailable can't be evaluated; unavailable_count gives the total. Returns at most 25 monitors; when truncated is true, narrow the filters.

Snowflake

These tools are available when your Revefi account is connected to Snowflake.

get_contract_usage

Get your Snowflake contract usage: total spend, spend over the last 30 days, a daily breakdown, and the contract number.

This tool takes no parameters.

get_query_insights

Get performance insights for a Snowflake query — why it's slow and how to optimize it. Returns insights such as cartesian joins, memory spills, and high execution time, each with a readable description.

get_top_warehouses_by_spend

Get the Snowflake warehouses that consumed the most credits, highest first.

Returns a list of warehouse_name, total_credits_used, total_credits_used_compute, and total_credits_used_cloud_services.

get_top_users_by_credits

Get the Snowflake users who consumed the most credits.

Returns a list of user_name, credits, and query_count.

get_top_queries

Get the top Snowflake queries by execution time or bytes scanned, optionally filtered by warehouse or user.

Returns a list of query_id, user_name, warehouse_name, query_type, total_elapsed_time_seconds, execution_time_seconds, and bytes_scanned.

get_warehouse_details

Get Snowflake warehouse names and sizes, and whether Revefi manages them. Returns all warehouses if no filter is given.

Returns totalWarehouses and a warehouses list with warehouseName, size, type, state, managedWarehouseStatus, and lastAutoManageOperation (when present).

get_warehouse_utilization

Get warehouse utilization — active time, idle time, and suspension patterns — to spot underutilized warehouses.

Returns a list of warehouseName, uptimeSeconds, activeSeconds, idleBeforeSuspensionSeconds, and warehouseStatus.

manage_warehouse_auto_optimization

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Modifies data

Changes your Snowflake warehouse configuration. Confirm the warehouses and action before running it.

Start, stop, pause, or resume Revefi auto-optimization on Snowflake warehouses. Returns success or failure for each warehouse.

Databricks

These tools are available when your Revefi account is connected to Databricks.

search_jobs

Search for Databricks jobs by name or keyword. The search is case-insensitive and matches partial names.

Returns a list of matching jobs with job_id, name, and workspace_id. Use the job_id with the other Databricks tools.

get_job_details

Get a Databricks job's tasks, configuration, and metadata — useful for understanding its task dependencies, compute, and owners.

Returns jobId, name, description, creatorUserName, runAsUserName, workspaceId, workspaceName, and a tasksList. Each task includes its taskKey, description, dependenciesList, computeType (JOB_CLUSTER, ALL_PURPOSE, or SQL_WAREHOUSE), sourceCode, and clusterConfig.

get_latest_job_run

Get details of the most recent run of a Databricks job — useful for checking performance or diagnosing failures.

Returns job_id, job_run_id, name, start_time, end_time, duration_seconds, state (e.g. TERMINATED, RUNNING), termination_code (e.g. SUCCESS, FAILED), termination_message, run_page_url, and task_runs with the timing and status of each task.

get_recommended_cluster_configs

Get recommended cluster configurations for a Databricks job from its most recent Revefi experiment. This tool doesn't run a new experiment — the job must already have a completed one. If none exists, the tool returns an error; create an experiment for the job in the Revefi app, wait for it to complete, and call the tool again.

Returns the experiment's experimentId, jobId, status, startTime, and endTime, along with:

• originalClusterConfig and originalJobExecutionMetrics — the job's original configuration and how it performed.
• experimentClusterConfigDetailsList — each configuration that was tested, with its execution metrics.
• recommendedClusterConfigId — the ID of the best-performing configuration.
• perClusterOriginalConfigsList and perClusterRestoreConfigsList — the baseline and current configuration of each cluster, for jobs analyzed per cluster.