Blogs›ScyllaDB›AI Agent Database Integration
This post introduces ScyllaDB Agent Skills, a set of best practices and usage patterns for AI agents interacting with ScyllaDB Cloud clusters. These skills are delivered as markdown files and aim to improve AI agent reliability and performance by providing domain-specific knowledge. Key areas covered include scylladb-cloud-setup for proper connection flows and driver selection, scylladb-data-modeling for designing efficient NoSQL schemas and queries, and scylladb-vector-search for optimizing vector index creation and queries. This builds upon the existing integration of ScyllaDB with AI agents by providing structured guidance for their development and deployment.
7/8/2026
Introduces ScyllaDB support in MCP Toolbox for Databases, adding 'scylladb' source and 'scylladb-cql' tool resource types. Details installation and configuration for connecting to ScyllaDB clusters (self-hosted and cloud) using the ScyllaDB Go driver and CQL protocol. Provides examples for using the integration with AI agents and frameworks.
5/13/2026
Introduces ScyllaDB Agent Skills, a new mechanism for providing AI agents with best practices and domain-specific knowledge for interacting with ScyllaDB Cloud. Details three specific skill sets: scylladb-cloud-setup (connection flow, shard-aware drivers), scylladb-data-modeling (NoSQL schema design, partition key patterns, anti-patterns), and scylladb-vector-search (vector index creation, ANN queries, filtering). Highlights the importance of using correct shard-aware drivers to avoid performance degradation and security risks.