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Vinkius

Snowflake Connector for AI agents.

11 live capabilities

Query and map your Snowflake data cloud directly from your IDE.

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AI Agent

Why people use Snowflake

Snowflake Data Cloud Querying with the Snowflake

With this Connector, you just ask your agent to look it up. It pulls the live schema for you, so you can write your SQL with confidence. You get the data you need without the constant context switching.

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

What Vinkius changes

You get a direct line from your AI agent to your Snowflake data cloud.

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

One account · 5,900+ Connectors

  1. Real-world use case 01

    Verifying data ingestion

    A data engineer needs to check if a file landed in S3.

  2. Real-world use case 02

    Building SQL joins

    An analyst wants to know what columns are in the sales table.

  3. Real-world use case 03

    Monitoring compute costs

    A dev needs to see if a warehouse is running.

Complete set · 11capabilities

The complete Snowflake capability set.

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

Capability set01 / 03

01—04

4 capabilities in this set.

Part of 11 available through Snowflake.

  1. 01 Capability

    Cancel sql

    Cancel a running SQL statement

  2. 02 Capability

    Describe table

    Get table schema details

  3. 03 Capability

    Execute sql

    Executes a SQL query on Snowflake. This lets your agent perform read-only actions or test joins on the fly.

  4. 04 Capability

    Get session context

    Get current session context

Capability set02 / 03

05—08

4 capabilities in this set.

Part of 11 available through Snowflake.

  1. 05 Capability

    Get statement status

    Check the status of a SQL statement

  2. 06 Capability

    List databases

    Lists all databases in your Snowflake account. This provides the high-level view needed for schema discovery.

  3. 07 Capability

    List roles

    List security roles

  4. 08 Capability

    List schemas

    Lists all schemas within a specific database. Use it to drill down into the specific areas of your data.

Capability set03 / 03

09—11

3 capabilities in this set.

Part of 11 available through Snowflake.

  1. 09 Capability

    List tables

    Lists all tables within a specific schema. It helps you see the exact columns and types available for joining.

  2. 10 Capability

    List users

    List Snowflake users

  3. 11 Capability

    List warehouses

    Lists all virtual warehouses in your account. Use this to see what's running and avoid unnecessary costs.

Set up in minutes

One URL. Then ask Snowflake to work.

Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Snowflake 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_FZdNhx3MFhQbRsBvKlZ0olbBDFO6A5aMdUPyNnlO/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 Snowflake, and paste the URL above.

  3. Step 03

    Turn it on in chat

    Select +, open Connectors, and enable Snowflake for the conversation.

Where the request belongs

Work Snowflake can move forward.

Built around the request

Data engineers and analytics professionals who spend hours toggling between a terminal, a code editor, and a browser console to verify schemas or monitor costs.

01

Data Engineer

Validates that raw data landed in internal stages correctly from the IDE window.

02

Analytics Engineer

Builds dbt models by having the agent check live table definitions while writing SQL.

03

Software Architect

Pulls raw diagnostic query metrics without needing to download and manage heavy local SDKs.

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
Amazon Redshift logo
02 7 capabilities

Amazon Redshift

Equip your AI to directly query, analyze, and manage your petabyte-scale data warehouse via the serverless AWS Redshift Data API.

View Connector
Coalesce logo
03 8 capabilities

Coalesce

Enable your AI agent to manage Snowflake data pipelines, trigger transformations, and monitor jobs via the Coalesce API.

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
Google BigQuery logo
05 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
StarRocks logo
06 10 capabilities

StarRocks

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

View Connector

Bring your own AI

Change the model, client or framework. Keep Snowflake 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 Snowflake.

The practical details behind the request, access and result.

Can I use the Snowflake MCP to run queries in Cursor?

Yes, it works with any MCP-compatible client like Cursor, Claude, or Windsurf. You can run queries and check schemas directly in your editor.

Does the Snowflake MCP help with cost management?

Yes, you can use it to check which warehouses are currently active. This helps you keep a firm grip on your compute costs.

How do I connect my Snowflake account to this Connector?

You'll need your Snowflake Account identifier and an OAuth token or JWT key pair. Once provided, your agent can access your data.

Can the agent see my database schemas?

Yes, it can navigate through databases and schemas to map out your data structure. This helps you write more accurate SQL.

Does the Snowflake MCP work for dbt users?

It is excellent for dbt users who need to verify live table definitions and check data landing statuses while they are modeling.

Can I check the status of a long query?

Yes, the Connector can retrieve the status of any asynchronous query. You can monitor long-running data pipelines without refreshing your browser.

Can my AI actually read the raw table rows via an execute statement?

Yes. When the AI uses execute_sql with something like SELECT * FROM schema.users LIMIT 10, the Connector integration parses the exact row outputs. The LLM consumes the tabular data back into context so you can converse naturally about the dataset findings.

Is it completely safe to give AI power over a Data Warehouse?

Safety stems from principle of least privilege. Supply a Snowflake Token tied strictly to a read-only role or a heavily scoped down service account. This allows the AI to navigate schemas and extract data without risking destructive schema mutations like DROPs or DELETEs.

Can it search for a column name if I don't know the exact schema?

Yes! Tell your agent: 'Find which table in the SALES_DB database has a column named customer_churn_score'. Due to its autonomous workflow, the bot will pull schemas, subsequently loop over list_tables, query Snowflake’s internal information_schema if necessary, and deduce it entirely for you.

How do I find my Snowflake Account Identifier?

Your Account Identifier is the part of your Snowflake URL before '.snowflakecomputing.com'. It typically looks like xy12345.us-east-2.aws.

One connection away

Give your agent a direct line to Snowflake.

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

Explore every Connector No credit card required · Free tier available