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Vinkius

Amazon Redshift Connector for AI agents.

7 live capabilities

Query and manage your petabyte-scale data warehouse using natural language.

Live agent request Amazon Redshift / Connector

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AI Agent

Why people use Amazon Redshift

Amazon Redshift Data Warehouse Analysis

This Connector puts the data where you're already working. You can just ask your agent to pull the metrics or describe the schema. It handles the SQL and the result retrieval, giving you the answer in your chat window immediately.

  • Claude
  • ChatGPT
  • Gemini
  • Cursor
  • Visual Studio Code
  • Windsurf

What Vinkius changes

You get a direct line from your chat interface to your Redshift data without the overhead of managing drivers or connections.

Use it from Claude, ChatGPT, Cursor or another AI client you already have.

One account · 5,900+ Connectors

  1. Real-world use case 01

    Schema Discovery for New Tables

    A data analyst needs to know the columns of a new reporting table.

  2. Real-world use case 02

    Migration Verification

    A developer wants to check if a migration worked.

  3. Real-world use case 03

    Ad-hoc Revenue Reporting

    A manager asks for total revenue from last week.

Complete set · 7capabilities

The complete Amazon Redshift capability set.

These are the exact actions your AI can choose when you ask it to work with Amazon Redshift.

Capability set01 / 02

01—04

4 capabilities in this set.

Part of 7 available through Amazon Redshift.

  1. 01 Capability

    Get results

    Fetch the rows from a completed SQL statement. This delivers the final data results directly to your chat window.

  2. 02 Capability

    Describe table

    Retrieve column names and data types for a specific table. This helps your agent understand the data structure before it writes a query.

  3. 03 Capability

    Execute sql

    Run standard SQL commands like SELECT or DDL in the background. This is ideal for long-running queries that would otherwise hang your UI.

  4. 04 Capability

    Statement status

    Check if a long-running query is still processing or finished. This allows your agent to monitor background tasks accurately.

Capability set02 / 02

05—07

3 capabilities in this set.

Part of 7 available through Amazon Redshift.

  1. 05 Capability

    List schemas

    List all database schemas in your Redshift instance. Use this to explore the high-level organization of your data.

  2. 06 Capability

    List statements

    View a history of recent SQL queries executed on your cluster. This is great for auditing recent workloads and query types.

  3. 07 Capability

    List tables

    List every table inside a specific schema. This helps you quickly find the right table for your next query.

Set up in minutes

One URL. Then ask Amazon Redshift to work.

Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Amazon Redshift from the conversation.

Choose your client

Live preview
Advanced clients IDE · CLI

Claude · Web + desktop

Official guide ↗

Connector URL · ready to paste

Streamable HTTP
https://edge.vinkius.com/vk_preview_QDzQjDxNMJC2VmZh3q1JKRAmKezB8DhMd2clGxBp/mcp
  1. Step 01

    Open Connectors

    In Claude Web or Claude Desktop, open Settings and choose Connectors.

  2. Step 02

    Add the URL

    Choose Add custom connector, name it Amazon Redshift, and paste the URL above.

  3. Step 03

    Turn it on in chat

    Select +, open Connectors, and enable Amazon Redshift for the conversation.

Where the request belongs

Work Amazon Redshift can move forward.

Built around the request

This is for the data professional who is tired of context-switching between their chat interface and a SQL editor to find simple answers.

01

Data Analyst

Pulls ad-hoc metrics and schema details during meetings to answer quick questions without opening a separate capability.

02

Backend Developer

Checks table states and tests migrations during the development cycle to verify data integrity.

03

Data Engineer

Audits cluster loads and monitors long-running queries for reporting workloads directly from their workspace.

Build the capability set

Add more capabilities.

Each Connector adds new actions and data without changing how you work.

Browse Connectors
Snowflake logo
01 11 capabilities

Snowflake

Execute SQL queries, manage databases, and analyze data on Snowflake with AI agents.

View Connector
StarRocks logo
02 10 capabilities

StarRocks

High-performance analytical database. manage clusters, tables, and query data via AI.

View Connector
Google BigQuery logo
03 7 capabilities

Google BigQuery

Empower your AI agent to query massive datasets via BigQuery. execute Standard SQL, track active jobs, and inspect table schemas natively.

View Connector
Starburst logo
04 6 capabilities

Starburst

Connect your AI to Starburst Enterprise. Query federated data lakes, manage access roles, and orchestrate complex data environments seamlessly.

View Connector
Materialize (Streaming SQL DB) logo
05 4 capabilities

Materialize (Streaming SQL DB)

Execute streaming SQL, manage compute clusters, and monitor real-time data pipelines directly from your AI agent.

View Connector
ClickHouse (Vector Search) logo
06 7 capabilities

ClickHouse (Vector Search)

Manage vector embeddings and SQL via ClickHouse. list databases, execute SQL, and perform high-speed vector searches directly from any AI agent.

View Connector

Bring your own AI

Change the model, client or framework. Keep Amazon Redshift connected.

  • Claude
  • ChatGPT
  • Gemini
  • Cursor
  • VS Code
  • Windsurf
  • ZCode
  • Cline
  • Zed
  • Continue
  • Kiro
  • Roo Code
  • Zencoder
  • Goose
  • Void
  • Augment Code
  • Amp
  • Qodo
  • Tabnine
  • Pieces
  • Sourcegraph Cody
  • JetBrains
  • Warp
  • Amazon Q
  • Antigravity
  • BoltAI
  • Raycast
  • Jan
  • LM Studio
  • AnythingLLM
  • Open WebUI
  • Msty
  • Cherry Studio
  • LibreChat
  • TypingMind
  • Chorus
  • 5ire
  • n8n
  • LangChain
  • LlamaIndex
  • CrewAI
  • Vercel AI SDK

Before you connect

Questions about Amazon Redshift.

The practical details behind the request, access and result.

Can I use the Amazon Redshift MCP with my existing AWS account?

Yes, you just need to provide your standard AWS credentials and the specific endpoint details for your cluster.

Does this Connector support complex SQL joins?

Yes, it handles standard SQL commands including complex aggregations and DDL operations.

How do I handle long-running queries with this Connector?

The Connector uses a background process for SQL execution, so you can check the status and get results whenever they're ready.

Is my data secure with the Amazon Redshift MCP?

This Connector uses the standard AWS Redshift Data API, which follows your existing IAM security principles.

Can I use this Connector to delete data?

Yes, you can run DML commands like DELETE or UPDATE through the execute_sql capability.

Do I need to install JDBC drivers to use this?

No, this Connector uses the Data API, which removes the need for local drivers or persistent connection pools.

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 Connector 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.

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.

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.

One connection away

Give your agent a direct line to Amazon Redshift.

Connect Amazon Redshift once. Keep it beside 5,900+ managed Connectors when the next task needs more.

Explore every Connector No credit card required · Free tier available