MCP Server Skills#
The ibm_watsonx_data_integration_mcp server provides skill resources that contain domain-specific best practices, workflows, and patterns. These skills are installed server-side and automatically loaded by AI assistants when working on relevant tasks to ensure correct SDK usage.
Skills Overview#
platform - Entry point for all IBM watsonx Data Integration tasks
batch-flows - Building, configuring, and running batch flows
streaming-flows - Building, configuring, and running streaming flows
Available Skills#
platform#
URI: skill://platform/
When Used: This is the entry point skill that AI assistants load first for any IBM watsonx Data Integration task.
What It Helps With:
Understanding the correct startup sequence (reading documentation before generating code)
Using the right collection methods for projects, flows, jobs, engines, and environments
Authenticating properly for SaaS and on-premises deployments
Managing job lifecycles (creating, running, monitoring, and canceling jobs)
Persisting changes correctly
Handling errors and configuring error stages
Key Guidance: After reading this skill, the AI assistant will load the appropriate specialized skill (batch-flows or streaming-flows) based on your specific task.
batch-flows#
URI: skill://batch-flows/
When Used: AI assistants load this skill when you need to build, configure, or run batch flows.
What It Helps With:
Understanding key differences between batch and streaming flows
Following the correct workflow from authentication through job execution
Finding the right stage models and configuration enums
Working with schemas and column types
Knowing which of the 150+ available batch stages to use
Configuring stages correctly with accepted values
Compiling flows before creating jobs
Typical Workflow: Authenticate → Get project → Create/get flow → Add stages → Configure stages → Connect stages → Define schemas → Update flow → Compile flow → Create job → Start job
streaming-flows#
URI: skill://streaming-flows/
When Used: AI assistants load this skill when you need to build, configure, or run streaming flows.
What It Helps With:
Checking engine health before starting work
Understanding when environments are needed (optional for streaming)
Discovering available stages using MCP tools
Getting stage configurations in manageable batches
Connecting stages in various patterns (basic, chaining, fan-out, Stream Selector)
Validating flows before creating jobs
Working in engineless mode when no engine is available
Typical Workflow: Authenticate → Get project → Check engine/environment → Create/get flow → Discover stages → Get configurations → Add stages → Configure stages → Connect stages → Update flow → Validate flow → Create job → Start job
How Skills Work#
Skills are installed server-side and automatically loaded by AI assistants based on the task you’re working on. You don’t need to install or configure skills manually - the AI assistant will:
Start with the platform skill to understand general SDK patterns
Load the appropriate specialized skill (batch-flows or streaming-flows) based on your task
Use the guidance in these skills to generate correct SDK code
Follow the recommended workflows and best practices
This ensures that the AI assistant uses the SDK correctly and follows established patterns, reducing errors and improving code quality.