Chat with your Amazon S3 data

AI to analyze Amazon S3 data with Claude and ChatGPT

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

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Amazon S3
You
How many CSV files were processed in our S3 bucket yesterday?
Amazon S3
1,247 files were ingested yesterday with an average processing time of 4.2 minutes per batch.
Via Kondado MCP
You
Which file prefix represents the largest volume this month?
File Prefixes
The "sales_data_" prefix accounts for 68% of all processed files, totaling 45.3 GB of data.
Via Kondado MCP
You
What percentage of our files use semicolon delimiters?
CSV Structure
Only 12% use semicolons while 88% use commas, indicating strong standardization across datasets.
Via Kondado MCP
You
What is the average delay between file upload and start reading?
Processing Speed
Current average latency is 8.5 minutes from S3 upload to processing initiation across all prefixes.
Via Kondado MCP
Works in Claude, ChatGPT and any MCP client

AI to analyze Amazon S3 data with Claude and ChatGPT

Chat with Claude, ChatGPT, or any MCP client about your Amazon S3 storage data using natural language. Ask how many CSV files were processed yesterday, which file prefixes are growing fastest, or whether your column delimiters are consistent across datasets. The AI reads your replicated S3 metadata and returns answers instantly, turning complex cloud storage logs into simple business insights without requiring SQL knowledge or AWS console navigation.

Kondado exposes Amazon S3 CSV file metadata through an MCP server compatible with Claude, ChatGPT, and other clients, offering 1 pipeline with fields for start reading dates, column delimiters, and file prefixes. The same replicated data also fuels ready reports in Power BI and Looker Studio for visual monitoring.

Operations teams use this to track file ingestion schedules and identify processing delays, while data engineers monitor delimiter consistency to prevent parsing errors. Finance analysts query storage patterns to optimize transfer costs, and marketing operations teams verify that campaign data files arrive on schedule. Everyone gets answers by typing questions in plain English, making S3 data accessible to business users regardless of technical background.

I prefer ready dashboards

Dashboard templates in Power BI and Looker Studio, connected to your Amazon S3 data by Kondado in minutes.

View Amazon S3 dashboards →

I want to ask the AI

Claude, ChatGPT and other MCP clients query your Amazon S3 data in natural language.

View MCP setup →

The pipeline detailed below organizes your Amazon S3 CSV metadata for immediate conversational analysis through Claude or ChatGPT. Query the CSV Files endpoint to uncover file volume trends over time, identify which file prefixes dominate your storage structure, or spot delimiter inconsistencies that could break downstream ETL processes. Analyze start reading dates to detect processing delays or optimize ingestion schedules, and compare column delimiter usage across different file categories to ensure consistent data quality standards. You can cross-reference file prefixes with reading dates to identify seasonal upload patterns or troubleshoot missing data batches. Since Kondado structures this metadata on a configurable schedule, your natural language queries always reflect the latest file organization patterns and reading timestamps without manual CSV exports from the AWS console.

How to connect Amazon S3 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

Amazon S3 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
∞
Ad-hoc questions
CSV Files
Includes fields such as Start reading date, Column delimiter, and File prefix, enabling efficient data reading and organization.
Full docs on the wiki → Connect Amazon S3 now →

How to connect and use AI with your data

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

1
Connect Amazon S3 and select your destination

Connect your Amazon S3 data source on Kondado at app.kondado.com.br and choose a 'Via Kondado' destination so your CSV file metadata lands ready for AI access and powers the dashboard templates.

2
Add Kondado MCP in Claude or ChatGPT

In Claude Web or Desktop, or in ChatGPT, open the connection settings to add the Kondado MCP server and authorize once via OAuth at app.kondado.com.br. The same simple GUI setup works in both clients with no command line required.

3
Chat about S3 data or open dashboards

Ask questions in natural language about your Amazon S3 file metadata, reading dates, and storage patterns. For visual recurring monitoring, open a ready Power BI or Looker Studio dashboard template using the same replicated data.

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

FTP FTP
Google Cloud Storage Google Cloud Storage
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 types of business questions can I ask Claude about my Amazon S3 CSV file data? ▼
You can ask about file volume trends such as how many CSV files were processed this week, identify the most active file prefixes in your buckets, or check for delimiter consistency across your datasets. The AI analyzes your replicated metadata including start reading dates and column delimiters to answer operational questions about data ingestion schedules and file organization patterns.
How do I configure ChatGPT to access my Amazon S3 data through Kondado? ▼
Open the ChatGPT interface and navigate to the connection settings to add the Kondado MCP server. Authorize the connection once via OAuth at app.kondado.com.br using your existing credentials. The same GUI-based setup works for Claude Web and Desktop, requiring no command line tools or JSON configuration files.
Can Claude or ChatGPT write data back to my Amazon S3 buckets or modify stored files? ▼
No, the MCP connection provides read-only access for analytical chat purposes only. The AI can answer questions about your file metadata, reading dates, and delimiter patterns, but cannot upload, delete, or modify files in your S3 storage. For data replication, Kondado handles the sync on a configurable schedule while the AI remains strictly for querying and analysis.
How frequently does the Amazon S3 data update for AI chat analysis? ▼
Kondado replicates your S3 file metadata on a configurable schedule that you set during pipeline configuration, which could be hourly or daily depending on your operational needs. This ensures that when you ask Claude or ChatGPT about recent file uploads or current storage patterns, the answers reflect your latest data without manual refreshes.
What is the difference between asking the AI about Amazon S3 data and using the ready dashboards? ▼
Chatting with Claude or ChatGPT is ideal for ad-hoc exploration, specific troubleshooting questions, or investigating unusual patterns in your file prefixes and reading dates. The ready Power BI and Looker Studio report templates provide visual monitoring with recurring charts and KPIs for tracking long-term storage trends and operational metrics without typing questions each time.
Do I need technical coding skills to set up the MCP connection for Amazon S3 analysis? ▼
No coding is required. The setup uses a graphical interface where you add the Kondado MCP server in Claude or ChatGPT settings and complete a single OAuth authorization at app.kondado.com.br. There are no CLI commands, JSON files to edit, or API keys to manage manually.
Which specific Amazon S3 metadata fields can I query in natural language? ▼
You can ask questions about the Start reading date to track processing timelines, analyze Column delimiter usage to ensure parsing compatibility, or explore File prefix patterns to understand your storage organization. These fields from the CSV Files pipeline enable operational insights about file ingestion schedules and data structure consistency.

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