Workflow tools
Workflow tools let your agent author analytical Workflows (DAGs of components), validate and compile them, run them in sync or async mode, schedule them, and inspect the component catalog. They also cover the Workflows your team publishes as reusable MCP tools.
create_workflow
Title: Create Workflow
Creates a new Workflow from a full definition. The agent validates the DAG's components and parameters against the connection before creating it.
bundle
object
Yes
The Workflow definition: title, connection, privacy, and a config with nodes and edges.
connection
string
No
Connection to validate against, overriding the bundle's.
Can modify data: creates a new Workflow.
update_workflow
Title: Update Workflow
Changes an existing Workflow, sets sharing, or publishes it as a callable MCP tool.
Method: update · share · unshare · publish · unpublish
id
string
Yes
The Workflow to change.
bundle
object
For update
A partial definition; unmentioned fields are kept.
org / emails / canEdit
boolean / array / boolean
For share, unshare
Who to share with, and whether they can edit.
name / description
string
For publish
Override the published tool's name and description.
Can modify data.
schedule_workflow
Title: Schedule Workflow
Adds, replaces, or removes a Workflow's schedule. Compiles the DAG to SQL and registers a warehouse cron.
Method: add · update · remove
id
string
Yes
The Workflow to schedule.
expression
string
For add, update
The schedule expression (provider-specific: BigQuery natural language; Snowflake, Postgres, Redshift cron; Databricks Quartz).
Can modify data.
validate_workflow
Title: Validate Workflow
Checks a Workflow without creating or running it. Validates structure and components, deep-verifies against the live connection, or compiles the DAG to SQL for inspection.
Method: validate · verify · to_sql
bundle
object
Yes
The Workflow definition to check.
connection
string
No
Connection to validate against, overriding the bundle's.
Read-only.
read_workflows
Title: Browse Workflows
Finds and inspects Workflows and the Workflows published as MCP tools.
Method: list · get · list_mcp_tools · get_mcp_tool
id
string
For get, get_mcp_tool
The Workflow to read.
search
string
No
Title substring search (for list).
Read-only.
run_workflow
Title: Run Workflow
Runs a Workflow and collects its output. Compiles the DAG to SQL, submits it, reports status, and fetches result rows.
Method: run · status · results
id
string
For run, results
The Workflow to run.
connection / jobId
string
For status
The connection the run was submitted on, and the job to check.
node
string
For results
Which node's output to return.
limit
number
No
Max rows to return (default 100).
Can modify data: a run executes the compiled SQL.
read_workflow_components
Title: Browse Workflow Components
Lists the available Workflow components on a connection, or gets one component's full detail — inputs, outputs, and parameters.
Method: list · get
connection
string
Yes
The connection whose component catalog to read.
search
string
No
Free-text filter (for list).
names
string
For get
Component name(s), comma-separated.
Read-only.
Your published workflows
Any Workflow your organization publishes as an MCP tool registers alongside the built-in tools, exposing organization-specific logic (site selection, trade-area analysis, demand modeling) in a form the agent can call directly. Published tools run in two modes:
Sync. The tool returns results immediately. Best for lightweight, fast queries.
Async. The tool launches a job and returns a
jobId. The agent then polls the async job tools below and retrieves the output when the job completes. Best for long-running pipelines.
For step-by-step guidance on publishing, see Workflows as MCP Tools.
Best practices
Keep tool descriptions clear and specific, so the agent chooses the right tool.
Define inputs precisely — descriptive names and types for every parameter.
Test the way an agent will call it. Use Run MCP Tool test in the workflow editor to preview the exact response, including sync/async timing. See Test your MCP Tool.
Choose the right output mode — Sync for fast queries, Async for long-running processes.
Version and update carefully. Sync updates promptly and communicate changes to users.
Async job tools
When you run a workflow with the built-in run_workflow tool, its own status and results methods handle polling — you don't need anything else. The two tools below are for published workflow tools running in async mode: they register automatically alongside your published workflows (only when your account has them), so the agent can poll a published async job. You don't configure them.
async_workflow_job_get_status_v1_0_0
Gets the status of an async workflow job. The agent calls this after an async workflow tool returns a job ID, and polls until the status is success or failure.
jobId
string
Yes
The async workflow job ID returned by the tool that launched it.
connectionName
string
Yes
The connection used by the workflow.
Possible status values: pending, running, success, failure, cancelled.
async_workflow_job_get_results_v1_0_0
Retrieves the results of an async workflow job after it completes with success status. The agent calls this only after the status tool confirms the job is done.
jobId
string
Yes
The async workflow job ID.
providerId
string
Yes
The data warehouse provider: bigquery, snowflake, databricks, postgres, redshift, or oracle.
connectionName
string
Yes
The connection used by the workflow.
workflowOutputTableName
string
Yes
The fully-qualified name of the workflow output table.
The result is a JSON object with a rows array of the output data and a schema describing the column types.
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