snowflake-mcp
Integrate Snowflake with MCP clients. Manage Snowflake endpoints, validate connectivity, and leverage Cortex AI (Search, Analyst, Agent) services directly within your AI workflow.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
215 skills found
Integrate Snowflake with MCP clients. Manage Snowflake endpoints, validate connectivity, and leverage Cortex AI (Search, Analyst, Agent) services directly within your AI workflow.
Migrate standard PostgreSQL tables to TimescaleDB hypertables with optimized partitioning, chunking, and compression strategies for time-series data.
Structured reasoning tool for complex problem decomposition, step-by-step analysis, consistency verification, and evidence-based synthesis with confidence scoring.
Robot perception system design, configuration, and optimization for cameras, LiDAR, and sensor fusion pipelines. Includes camera calibration, 3D reconstruction, and production deployment best practices.
Automate the migration of Netflix Conductor workflows to Temporal Python, including server orchestration, worker management, and workflow troubleshooting.
Architect multi-agent systems to overcome context limits, using patterns like supervisor, swarm, and hierarchical models to manage complex workflows.
Queen-led multi-agent orchestration for Claude Code, featuring Byzantine consensus, persistent collective memory, and adaptive task distribution for complex software projects.
Expert guidance for configuring FeatBit observability via OpenTelemetry. Use for setting up metrics, logs, traces, and connecting OTEL backends like Seq, Jaeger, or Prometheus for FeatBit backend monitoring.
Implement ReasoningBank adaptive learning with AgentDB's ultra-fast vector backend. Features trajectory tracking, verdict judgment, memory distillation, and pattern recognition for self-learning autonomous agents.
Generate and edit images using the Gemini API via the nanaban CLI. Create illustrations, logos, and icons, or perform photo edits like background removal and style transfer.
Create, register, and manage custom agent tools and MCP servers to extend AI agent capabilities with external APIs and custom logic.
Automate pytest execution with built-in environment verification, failure analysis, coverage reporting, and intelligent test discovery.