This blog post details the author's exploration of IBM Bob while building an MCP server for Astra DB. It emphasizes learning through experimentation in Code Mode, focusing on automation and iterative development. The author shares insights on prompt creation, workflow challenges, and the importance of documentation throughout the process, ultimately achieving a functional server setup.
Access watsonx Orchestrate functionality over an MCP server
The Model Context Protocol (MCP) is being increasingly utilized in AI applications, particularly with the watsonx Orchestrate ADK. This setup allows users to develop and manage agents and tools through a seamless integration of the MCP server and the Development Edition, enhancing user interaction and functionality in coding environments.
Create Your First AI Agent with Langflow and watsonx
This post shows how to use Langflow with watsonx.ai and a custom component for a “Temperature Service” that fetches and ranks live city temperatures. It covers installation, flow setup, agent prompting, tool integration, and interactive testing. Langflow’s visual design, MCP support, and extensibility offer rapid prototyping; future focus includes DevOps and version control.
