Chat with your Google Cloud Storage data

AI to analyze Google Cloud Storage data with Claude and ChatGPT

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No credit card required | 14 days | 10 million records | 30 pipelines

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Google Cloud Storage
You
How many CSV files were added to the storage bucket yesterday?
CSV Tracking
Yesterday, your Google Cloud Storage received 47 new CSV files, with the latest upload recorded at 11:42 PM according to the modification timestamps.
Via Kondado MCP
You
What is the file path for last week's sales data CSV?
File Location
Last week's sales data is located at gs://bucket/sales/2024/week_47.csv and was last modified on Friday at 6:30 PM.
Via Kondado MCP
You
Which CSV files have not been updated in the last 30 days?
Data Freshness
There are 12 stale CSV files in your storage that haven't been modified in the last 30 days, primarily in the archive/2023 path.
Via Kondado MCP
You
What is the total count of CSV files currently tracked in the main bucket?
Storage Volume
Your main storage bucket currently contains 234 active CSV files, with 89 of them modified within the past week.
Via Kondado MCP
Works in Claude, ChatGPT and any MCP client

AI to Analyze Google Cloud Storage Data with Claude and ChatGPT

Business teams can now chat directly with Claude, ChatGPT, or any MCP client to explore their Google Cloud Storage data through natural language. Simply ask about recent file uploads, track specific CSV datasets, or inquire about storage organization patterns without writing SQL or code. The AI retrieves current information from your replicated pipelines to answer questions about file metadata, modification dates, and storage structure instantly.

Kondado exposes Google Cloud Storage data via an MCP server, enabling direct integration with Claude and ChatGPT for analytical chat. The platform replicates 1 pipeline (CSV file tracking with 8 fields including file paths and modification timestamps) on a configurable schedule, making structured storage data available for AI querying. The same data also powers ready reports in Power BI and Looker Studio for visual monitoring.

Operations managers use this to audit file ingestion workflows and verify data landing times, while data analysts query file basenames and paths to locate specific datasets without browsing folders manually. Finance teams track storage asset values and modification histories to reconcile reporting periods, and marketing analysts confirm campaign data files arrived on schedule by asking about recent upload timestamps directly in chat.

I prefer ready dashboards

Dashboard templates in Power BI and Looker Studio, connected to your Google Cloud Storage data by Kondado in minutes.

View Google Cloud Storage dashboards →

I want to ask the AI

Claude, ChatGPT and other MCP clients query your Google Cloud Storage data in natural language.

View MCP setup →

The pipeline listed below contains the structured metadata from your Google Cloud Storage buckets. The CSV pipeline captures essential file information including __file_basename for identifying specific datasets, __file_path for locating files within your storage hierarchy, and __kdd_insert_time for tracking when each file was processed. You can query these fields to determine which files were modified yesterday, compare current file naming conventions against previous periods, or identify orphaned datasets that haven’t been updated recently. While Google Cloud Storage currently offers 1 primary pipeline for file tracking, you can combine this storage metadata with other business data sources in your Kondado account to correlate file arrival times with downstream report updates or sales performance changes. Scheduled updates run on a configurable timetable, ensuring your AI assistant always references the freshest file metadata when answering questions about your storage environment.

How to connect Google Cloud Storage to Claude, ChatGPT and other AI clients

MCP is an open standard. Add the Kondado server to the connections of Claude (Web or Desktop), ChatGPT, or any other MCP client you use, and authorize via OAuth at app.kondado.com.br. Setup through the UI, no code.

Kondado MCP server: https://mcp.kondado.io/mcp
Detailed guide: Claude Detailed guide: ChatGPT
AI vocabulary

Google Cloud Storage tables and metrics available via Kondado

Each item below is something Claude, ChatGPT or another MCP client already knows how to query — no schema setup, no manual mapping.

1
Table
8
Fields
∞
Ad-hoc questions
CSV
Table includes information about CSV files, featuring fields such as __file_basename, __file_path, and __kdd_insert_time, enabling tracking of the modification date and value of each file.
Full docs on the wiki → Connect Google Cloud Storage now →

How to connect and use AI with your data

In 3 steps: connect on Kondado, pick dashboard or chat, analyze.

1
Connect Google Cloud Storage at app.kondado.com.br

Set up your Google Cloud Storage data source in Kondado and select a Via Kondado destination so your file metadata lands ready for AI access and powers the dashboard templates.

2
Add Kondado MCP in Claude or ChatGPT

Open the connection settings in Claude (Web or Desktop) or ChatGPT, add the Kondado MCP server, and complete the OAuth authorization at app.kondado.com.br once. Both clients use the same GUI-based setup with no CLI required.

3
Chat about storage or open dashboards

Ask questions in natural language about your Google Cloud Storage files, paths, and modification dates. For recurring visual monitoring, open a ready Power BI or Looker Studio dashboard template.

Other connectors with AI via MCP

Same Kondado data, in chat through Claude, ChatGPT and other MCP clients.

CRM and Sales

ActiveCampaign ActiveCampaign
Bitrix24 CRM Bitrix24 CRM
Exact Sales Exact Sales
Hubspot Hubspot
Infusionsoft (Keap) Infusionsoft (Keap)
Meetime Meetime
NectarCRM NectarCRM
Pipedrive Pipedrive
PipeRun PipeRun
Ploomes Ploomes
RDStation CRM RDStation CRM
Salesforce Salesforce

Marketing and Automation

Google Ads Google Ads
E-goi E-goi
Google Search Console Google Search Console
Hi Platform Hi Platform
Huggy Huggy
Linkedin Linkedin
MailChimp MailChimp
Mandrill Mandrill
Mautic Mautic
Pushwoosh Pushwoosh
RDStation RDStation
Salesforce Marketing Cloud (Exact Target) Salesforce Marketing Cloud (Exact Target)
SenseData SenseData
Taboola Taboola
Twilio Twilio
WordPress WordPress

Advertising and Media

Apple App Store Apple App Store
Bing Bing
Criteo Criteo
Facebook Facebook
Facebook Ads Facebook Ads
Google Play Store Google Play Store
Instagram Ads Instagram Ads
Meta Ads Meta Ads
Microsoft Ads Microsoft Ads
Microsoft Advertising Microsoft Advertising
Pinterest Ads Pinterest Ads
TikTok Ads TikTok Ads
X Ads X Ads
YouTube YouTube

E-commerce and Marketplaces

Bling! Bling!
Hotmart Hotmart
Loja Integrada Loja Integrada
Mercado Libre Mercado Libre
Nuvemshop (Tiendanube) Nuvemshop (Tiendanube)
Olist Tiny Olist Tiny
Omie Omie
Pagar.me Pagar.me
Shopify Shopify
Tiny ERP Tiny ERP
Tray Tray
VNDA VNDA
VTEX VTEX
Wake Commerce Wake Commerce

Financial and Payments

ASAAS ASAAS
ContaAzul ContaAzul
Fatura Simples Fatura Simples
Granatum Granatum
Superlogica Superlogica
Sympla Sympla

Support and Customer Service

55pbx 55pbx
api4com api4com
Blip (take) Blip (take)
Clockify Clockify
EADBOX EADBOX
Freshdesk Freshdesk
Movidesk Movidesk
Recruiterbox Recruiterbox
Stilingue Stilingue
Wootric Wootric
Zendesk Zendesk
Zendesk Chat (Zopim) Zendesk Chat (Zopim)

Databases

AWS CloudWatch Metrics AWS CloudWatch Metrics
Azure Table Storage Azure Table Storage
BigQuery BigQuery
InfluxDB v1 InfluxDB v1
MongoDB MongoDB
MySQL (& MariaDB) MySQL (& MariaDB)
Oracle Oracle
PostgreSQL PostgreSQL
SQLServer SQLServer
Webhook Webhook

Productivity and Collaboration

ClickUp ClickUp
Google Sheets Google Sheets
Jira Jira
monday.com monday.com
Notion Notion
Pipefy Pipefy
Tangerino Tangerino
Toggl Toggl
Trello Trello

Social Media

Instagram Instagram
TikTok Organic TikTok Organic

User Analytics

Google Analytics GA4 Google Analytics GA4
Mixpanel Mixpanel
Zeeng Zeeng

Storage and Transfer

Amazon S3 Amazon S3
FTP FTP
See all AI connectors →

Related on Kondado

Frequently asked questions about AI

How ready dashboards and chat via Claude / ChatGPT work together with your data via Kondado.

What kind of business questions can I ask Claude or ChatGPT about my Google Cloud Storage data? ▼
You can ask about recent file uploads, specific file locations, modification dates, file naming patterns, and data freshness. For example, inquire "Which CSV files were added to the bucket yesterday?" or "What is the path structure for last month's sales data?" to locate information instantly without manual browsing.
How do I configure Claude or ChatGPT to access my Google Cloud Storage data through Kondado? ▼
In Claude (Web or Desktop) or ChatGPT, navigate to the connection settings and add the Kondado MCP server. You will be prompted to authorize access once via OAuth at app.kondado.com.br. Both clients use the same GUI-based setup with no CLI commands or code snippets required.
Does the AI write data back to my Google Cloud Storage buckets or execute actions? ▼
No, the AI provides read-only analytical chat. It can retrieve and analyze your file metadata, answer questions about storage contents, and help you understand your data structure, but it cannot delete files, upload objects, or modify storage configurations.
How does authentication work when connecting my AI client to Kondado? ▼
Authentication uses OAuth through app.kondado.com.br. After adding the Kondado MCP server in your AI client settings, you authorize the connection once through the web interface, granting access to your replicated Google Cloud Storage pipelines without sharing API keys directly with the AI.
How frequently is the Google Cloud Storage data updated for AI querying? ▼
Data replicates on a configurable schedule that you set in Kondado, ensuring the AI references current file metadata and recent uploads rather than outdated information. Update frequency can be adjusted based on your business needs and data velocity.
What dashboard templates are available for visualizing Google Cloud Storage data? ▼
Kondado offers ready report templates in Power BI and Looker Studio that visualize the same Google Cloud Storage metadata available to the AI. These templates provide visual monitoring of file volumes, upload trends, and storage organization patterns.
What is the difference between asking the AI in chat and opening a ready dashboard? ▼
Chat allows spontaneous, specific questions about your storage data using natural language, such as locating a particular file or checking yesterday's uploads. Ready dashboards in Power BI or Looker Studio provide structured visual monitoring for recurring metrics and scheduled operational reviews.
Can I use other MCP clients besides Claude and ChatGPT? ▼
Yes, while Claude and ChatGPT are the primary supported clients, any MCP-compatible client can connect to Kondado's server to query your Google Cloud Storage data. Other MCP clients also work with the same OAuth authorization process.

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