Can I query Amazon Redshift in plain English instead of writing SQL?

Yes. Dataki reads your Amazon Redshift schema, turns a plain-English question into a query, runs it against Amazon Redshift and returns a chart. The generated query is shown with every result, so you can verify or edit it.

Is there a hosted Amazon Redshift MCP server?

Dataki is one. Its remote MCP server reaches Amazon Redshift through a read-only connection you set up once in Dataki, so nothing is installed on your machine and no connection string goes into an assistant's config. It offers tools to list sources, read the schema and its documented meaning, run read-only SQL, draw charts in the conversation and save dashboards. Every query is logged with the key that ran it.

How do I build a dashboard from Amazon Redshift data without an ETL pipeline?

Connect Amazon Redshift to Dataki with a read-only connection, ask your question, and keep the answer as a dashboard widget. Dataki queries Amazon Redshift directly at read time, so there is no pipeline to build, no warehouse to sync into and no copy of your data to keep current.

Can Claude, ChatGPT or Cursor query my Amazon Redshift data?

Yes, through Dataki's hosted MCP server at https://dataki.ai/api/mcp. Connect Amazon Redshift to Dataki, add that URL as a connector in Claude or ChatGPT (or in Cursor, VS Code or Claude Code with a Dataki key), and the assistant can read the schema and run read-only queries. It gets the rows back; the credentials stay encrypted in Dataki and are never handed to the model.

Dataki for Amazon Redshift

Ask Amazon Redshift in plain English

Connect your Amazon Redshift cluster or Serverless workgroup to Dataki and ask your warehouse questions in plain English. Dataki writes Redshift SQL, reads every schema a read-only user can see, and keeps the answers as live dashboards.

Connects directly A read-only user, always over TLS, from one fixed IP.

Connect Amazon Redshift Read the setup guide

app.dataki.ai / chat Redshift · analytics

Which event categories brought in the most ticket revenue this quarter?

Reading the schema, writing the query…

SELECT c.catname AS category, SUM(s.pricepaid) AS revenue
FROM   sales s
JOIN   event e ON e.eventid = s.eventid
JOIN   category c ON c.catid = e.catid
WHERE  s.saletime >= DATE_TRUNC('quarter', GETDATE())
GROUP BY c.catname ORDER BY revenue DESC LIMIT 5;

Musicals brought in $413k this quarter, more than Pop, Opera and Jazz together.

01Questions

What people ask Amazon Redshift

Each one becomes a query against Amazon Redshift, run read-only, with the SQL shown beside the chart so anyone who reads SQL can check it. Anything worth keeping goes on a dashboard that refreshes on its own.

What were ticket sales by event category each month this year?
Which regions grew fastest quarter on quarter?
Which schemas hold order data, and how large is each table?
What share of revenue came from repeat buyers last quarter?

02From your assistant

Ask Amazon Redshift from Claude, ChatGPT or Cursor

Dataki runs a hosted MCP server. Add it to your assistant once and it can read your Amazon Redshift schema and run read-only queries through Dataki. The assistant gets the rows back; the Amazon Redshift credentials stay encrypted in Dataki and never reach the model.

Setup for your assistant:

Claude · dataki (MCP) Redshift · analytics

Compare this quarter's revenue by category with last quarter's in Redshift, and put the chart on a dashboard.

list_sources · finds Redshift · analytics
get_data_context · reads the tables and what the columns mean
query · runs the SQL read-only, returns the rows
render_ui · draws the chart from those rows, in the chat

server URL streamable http

https://dataki.ai/api/mcp

03Setting it up

Connecting Amazon Redshift

A read-only user, always over TLS, from one fixed IP. The setup guide covers it step by step.

Setup: About 10 minutes.
Connects from: 34.89.253.13, on port 5439 unless you changed it.
Encryption: Always TLS: Dataki never falls back to an unencrypted connection. On an endpoint AWS named, the certificate is verified.
What it reads: Tables, views (late-binding ones too) and Spectrum tables in every schema the user can use, or only the schemas you list.

Read the Amazon Redshift guide Open Dataki

The answer is still there tomorrow.

Ask in plain language. Dataki writes the SQL, runs it against your warehouse and draws the chart. Anything worth keeping becomes a dashboard with a link — not a message that scrolls away.

app.dataki.ai / chat

Which channels actually brought in revenue last quarter?

Queried bigquery · payments · 1.2 GB scanned

SELECT channel,
       SUM(amount) AS revenue
FROM   payments
WHERE  created_at >= DATE_TRUNC(CURRENT_DATE(), QUARTER)
GROUP BY channel
ORDER BY revenue DESC

Revenue by channel

Q3 · 5 rows

Organic search: $412,900
Partner referral: $268,400
Email: $151,200
Paid social: $96,700
Direct: $61,300

One click later, that chart is a dashboard of its own:

app.dataki.ai/d/revenue-by-channel

Live, not a screenshot. It re-runs the query on a schedule, so the number your team reads on Friday is Friday's number.

Share the link with anyone. Viewers are free on every plan.
Edit the SQL by hand whenever the model gets the logic almost right.
Drop the same dashboard into your own product with one line of HTML.

Start free See how it works

Using Dataki with Amazon Redshift

Can I query Amazon Redshift in plain English instead of writing SQL?: Yes. Dataki reads your Amazon Redshift schema, turns a plain-English question into a query, runs it against Amazon Redshift and returns a chart. The generated query is shown with every result, so you can verify or edit it.
Is there a hosted Amazon Redshift MCP server?: Dataki is one. Its remote MCP server reaches Amazon Redshift through a read-only connection you set up once in Dataki, so nothing is installed on your machine and no connection string goes into an assistant's config. It offers tools to list sources, read the schema and its documented meaning, run read-only SQL, draw charts in the conversation and save dashboards. Every query is logged with the key that ran it.
How do I build a dashboard from Amazon Redshift data without an ETL pipeline?: Connect Amazon Redshift to Dataki with a read-only connection, ask your question, and keep the answer as a dashboard widget. Dataki queries Amazon Redshift directly at read time, so there is no pipeline to build, no warehouse to sync into and no copy of your data to keep current.
Can Claude, ChatGPT or Cursor query my Amazon Redshift data?: Yes, through Dataki's hosted MCP server at https://dataki.ai/api/mcp. Connect Amazon Redshift to Dataki, add that URL as a connector in Claude or ChatGPT (or in Cursor, VS Code or Claude Code with a Dataki key), and the assistant can read the schema and run read-only queries. It gets the rows back; the credentials stay encrypted in Dataki and are never handed to the model.

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