clari-deploy-integration

name	clari-deploy-integration
description	Deploy Clari export pipelines to production with Airflow, Cloud Functions, or Lambda. Use when scheduling automated exports, deploying to cloud platforms, or setting up serverless Clari sync. Trigger with phrases like "deploy clari", "clari airflow", "clari lambda", "clari cloud function", "clari scheduled export".
allowed-tools	Read, Write, Edit, Bash(gcloud:*), Bash(aws:*)
version	1.6.0
license	MIT
author	Jeremy Longshore <[e-mail]>
tags	["saas","revenue-intelligence","forecasting","clari"]
compatibility	Designed for Claude Code

Clari Deploy Integration

Overview

Deploy Clari export pipelines to production environments: Airflow DAGs, AWS Lambda, or Google Cloud Functions for scheduled, serverless execution.

Instructions

Airflow DAG

# dags/clari_export_dag.py
from airflow import DAG
from airflow.operators.python import PythonOperator
from airflow.models import Variable
from datetime import datetime, timedelta

def export_clari_forecast(**context):
    from clari_client import ClariClient, ClariConfig

    client = ClariClient(ClariConfig(
        api_key=Variable.get("clari_api_key"),
    ))

    period = context["params"].get("period", "2026_Q1")
    data = client.export_and_download("company_forecast", period)

    entries = data.get("entries", [])
    context["ti"].xcom_push(key="entry_count", value=len(entries))
    # Load to warehouse here

dag = DAG(
    "clari_daily_export",
    schedule_interval="0 6 * * *",
    start_date=datetime(2026, 1, 1),
    catchup=False,
    default_args={"retries": 2, "retry_delay": timedelta(minutes=5)},
)

export_task = PythonOperator(
    task_id="export_forecast",
    python_callable=export_clari_forecast,
    dag=dag,
)

AWS Lambda

# lambda_handler.py
import json
 boto3
 clari_client  ClariClient, ClariConfig

 ():
    ssm = boto3.client()
    api_key = ssm.get_parameter(
        Name=, WithDecryption=
    )[][]

    client = ClariClient(ClariConfig(api_key=api_key))
    data = client.export_and_download(
        event.get(, ),
        event.get(, ),
    )

     {
        : ,
        : json.dumps({: (data.get(, []))}),
    }