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Connect Amazon Redshift to ChatGPT, Claude and Gemini

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Run complex SQL queries without complex setup.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

A futuristic MCP client docking bay
V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 7 capabilities

We ship only the actions that matter.

Capability set01 / 02

01-04

4 capabilities in this set.

Part of 7 available through Amazon Redshift.

  1. 01

    Describe table

    Retrieves column metadata for a table

  2. 02

    Execute SQL

    This is an asynchronous operation that returns a statement ID. Executes a SQL statement using the Redshift Data API

  3. 03

    List statements

    Lists recent SQL statements executed in the cluster

  4. 04

    Get results

    Retrieves the results of a completed SQL statement

Capability set02 / 02

05-07

3 capabilities in this set.

Part of 7 available through Amazon Redshift.

  1. 05

    List tables

    Lists all tables in a specific schema

  2. 06

    Statement status

    Checks the execution status of a SQL statement

  3. 07

    List schemas

    Lists all database schemas in Redshift

Real work

What teams actually run

01

Quarterly Revenue Analysis

You need the sum of sales for a specific region. You prompt the AI, which executes the aggregation and waits for the results to appear.

02

Schema Validation

Before writing a query, you ask the AI to describe a table, confirming the correct column names and data types.

03

Troubleshooting Data Pipelines

A report failed. You ask the AI to list recent statements and check the status of the failed job to pinpoint the error.

04

Data Exploration

You want to see what data is available in a new area. You ask the AI to list all schemas and tables in that area.

Automate a task

Put Amazon Redshift to work on one thing.

Step-by-step automations your AI runs through this Connector: the workflow, the prompts to start with, and the exact capabilities behind each move.

One connector, every AI

Amazon Redshift works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

ClaudeClaudeChatGPTChatGPTGeminiGeminiPerplexityPerplexityGrokGrokMicrosoft CopilotMicrosoft CopilotCursorCursorVS CodeVS CodeWindsurfWindsurfJetBrainsJetBrainsClineClineLangChainLangChainVercel AI SDKVercel AI SDKLovableLovableZ.aiZ.aiRaycastRaycastQwen CodeQwen CodeKimi CodeKimi CodeLe ChatLe Chat

Building your own app? The connector is yours to use.

You don't need a client to put Amazon Redshift to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

928ms average. Fast in production.

Amazon Redshift is checked daily against the live service.

Daily averagePeak 1111ms
Oct 3Today
Fastest day
762ms
Slowest day
1111ms
14-day trend
Slowing+15%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 7 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Amazon Redshift, so you can see the experience inside your AI.

It does not authenticate your account with Amazon Redshift. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Amazon Redshift Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_QDzQjDxNMJC2VmZh3q1JKRAmKezB8DhMd2clGxBp/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Amazon Redshift capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "amazon-redshift-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_QDzQjDxNMJC2VmZh3q1JKRAmKezB8DhMd2clGxBp/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up Amazon Redshift in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Amazon Redshift owners hand off.

This MCP is built for technical roles that spend time querying large, structured datasets. It lets you interact with petabyte-scale data warehouses using natural language prompts, eliminating the need to jump between your AI client and a separate SQL IDE.

  • 01

    Data Analysts

    Run ad-hoc exploratory aggregations and pull specific dataset metrics instantly into the chat.

  • 02

    Data Scientists

    Test hypotheses by executing complex SELECT statements and analyzing schemas without manual setup.

  • 03

    Data Engineers

    Audit cluster loads and verify execution lifecycles for large reporting workloads directly from your agent.

  • 04

    Backend Developers

    Test schema migrations and troubleshoot data integrity interactively during development.

FAQ

Questions Amazon Redshift owners ask.

  • 01

    Do I need to manage complex database connections?

    No. This MCP uses the AWS Redshift Data API. It handles the connection process without requiring you to manage persistent connection pools or JDBC drivers.

  • 02

    What happens if my query is very long?

    Long-running queries process asynchronously. The AI sends the query, gets a statement ID, and then you use the status capability to poll the result until it's ready.

  • 03

    Can I run write operations (like creating tables)?

    Yes. You can execute standard SQL commands, including Data Definition Language (DDL) for creating tables or Data Manipulation Language (DML) for changing data.

  • 04

    Is this only for reading data?

    Not at all. Beyond reading, you can audit the cluster by listing recent statements and checking the metadata of any table.

  • 05

    What kind of data does it handle?

    It connects to Amazon Redshift, which is designed for petabyte-scale data warehousing, meaning it handles massive amounts of structured data.

  • 06

    Are query results limited by size?

    Yes. The underlying Redshift Data API imposes soft constraints; for enormous responses, you might receive a paginated NextToken. While this MCP server auto-handles some response collection, queries returning over a few megabytes of raw JSON should be pre-filtered using LIMIT or aggregated to avoid token constraints in the LLM.

  • 07

    Can I use standard IAM credentials or do I need specific AWS roles?

    The integration accepts standard static IAM keys (AWS_ACCESS_KEY_ID & AWS_SECRET_ACCESS_KEY), provided they hold sufficient IAM inline or attached policies allowing use of redshift-data:* operations targeting your exact Cluster ARN.

  • 08

    Why does execute_sql only return a statement ID instead of the data?

    Because the Amazon Redshift Data API is strictly asynchronous. Queries often take seconds to minutes. Returning the statement_id instantly allows the AI to continue parsing conversations or interacting with other systems without locking up, executing get_results at a later time when the query officially succeeds.

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