AI Agent for Snowflake MCP Server
Integrate advanced AI-driven database interaction with Snowflake using the Model Context Protocol (MCP) Server. Effortlessly run SQL queries, access up-to-date data insights, and manage schema information with seamless tools. Unlock real-time data-driven decisions and streamline Snowflake database operations with secure, scalable automation.
Automated SQL Query Execution
Empower your workflows with automated read and write SQL queries in Snowflake. The MCP Server enables both SELECT and modification queries, table creation, and granular data access—all controlled by simple AI prompts and secure authentication.
- Read & Write Queries.
- Run SELECT, INSERT, UPDATE, and DELETE operations securely with fine-grained control.
- Create Tables.
- Easily create tables in Snowflake using AI-assisted workflows and automation.
- Role-Based Security.
- All actions are gated by Snowflake roles and can be restricted with `--allow-write`.
- Safe Defaults.
- Write operations are disabled by default, ensuring safe deployments.
Schema & Metadata Extraction
Instantly access up-to-date schema summaries, column definitions, and database metadata. The MCP Server's schema tools enable fast navigation of complex database structures and effortless resource discovery.
- List Databases & Schemas.
- Quickly enumerate available databases, schemas, and tables for instant data discovery.
- Describe Tables.
- View full table schemas including columns, types, comments, and more.
- Context Resources.
- Expose per-table context as resources for detailed data analysis.
Dynamic Insights & Resource Memoization
Harness real-time data insights and maintain an always-updated memo of analytical findings. The append_insight tool and automatic insight memoization help teams track, share, and act on new discoveries instantly.
- Append Insights.
- Add new analytical insights to a persistent memo, always accessible to your team.
- Automated Updates.
- Memo resources update automatically when new insights are discovered.
MCP INTEGRATION
Available Snowflake MCP Integration Tools
The following tools are available as part of the Snowflake MCP integration:
- read_query
Execute SELECT queries to read data from the Snowflake database and return the results.
- write_query
Execute INSERT, UPDATE, or DELETE queries to modify data, returning affected row counts or confirmation.
- create_table
Create new tables in the Snowflake database using a CREATE TABLE SQL statement.
- list_databases
List all databases available in the Snowflake instance.
- list_schemas
List all schemas within a specified Snowflake database.
- list_tables
List all tables within a specified database and schema, including table metadata.
- describe_table
View detailed column information for a specific table, including names, types, and comments.
- append_insight
Add new data insights to the insights memo resource and trigger its update.
Connect Your Snowflake with FlowHunt AI
Connect your Snowflake to a FlowHunt AI Agent. Book a personalized demo or try FlowHunt free today!
What is Snowflake
Snowflake is a leading cloud-based data platform that enables organizations to store, manage, and analyze vast amounts of data with ease and security. Founded in 2012, Snowflake offers a unified platform called the Data Cloud, which allows enterprises to break down data silos and connect data across multiple clouds and regions. The platform supports data warehousing, data lakes, data engineering, data science, and data application development. Its architecture separates storage and compute, enabling scalable, on-demand usage and cost efficiency. Snowflake is trusted by thousands of global organizations for real-time analytics, secure data sharing, and powering data-driven business intelligence and AI initiatives.
Capabilities
What we can do with Snowflake
Snowflake empowers users and organizations with a suite of powerful data management and analytics capabilities. With Snowflake, you can manage, share, and analyze data at scale, unlocking new possibilities for innovation and business growth.
- Unified Data Warehousing
- Combine structured and semi-structured data for scalable analytics in the cloud.
- Secure Data Sharing
- Easily and securely share live data across business units and with partners or customers.
- Real-time Analytics
- Perform high-speed, real-time analytics on large datasets to drive faster decision-making.
- AI & Machine Learning Integration
- Build and deploy AI/ML models directly on your data without data movement.
- Multi-cloud Support
- Operate seamlessly across AWS, Azure, and Google Cloud, enabling flexibility and resilience.
- Application Development
- Develop and launch data-driven applications leveraging Snowflake's scalable infrastructure.
How AI Agents Benefit from Snowflake
AI agents can leverage Snowflake to access high-quality, real-time data for training and inference, automate data engineering workflows, and enable secure, scalable collaboration. Snowflake’s robust APIs and support for modern data formats streamline AI integration, while its elastic compute resources ensure efficient processing at any scale.