Developing watsonx Orchestrate Agents with Antigravity

2026-01-28 · Source: Niklas Heidloff · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering · Depth: Intermediate, quick

Summary

IBM's watsonx Orchestrate platform facilitates building and running agentic applications within enterprises, supporting agent creation via methods like the Agent Development Kit. This post details how to integrate Google Antigravity for agent development, leveraging open standards such as the Model Context Protocol (MCP). Watsonx Orchestrate offers a remote MCP server for documentation, which can be defined locally or globally. An example demonstrates Antigravity creating a "Weather Agent" with two tools using a prompt, followed by generating a README.md for agent and tool import instructions. The platform also supports "skills" to guide Antigravity in tool selection and provide customized instructions, though not strictly necessary for simple cases.

Key takeaway

For AI Engineers developing enterprise agentic applications, integrating Google Antigravity with IBM watsonx Orchestrate simplifies agent creation. You should explore using Antigravity's prompt-based generation for new agents and tools, leveraging the MCP documentation server for seamless integration. This approach can accelerate development cycles and streamline the deployment of custom agents.

Key insights

Google Antigravity can build IBM watsonx Orchestrate agents using open standards like MCP.

Principles

• Open standards enable cross-platform agent development.
• Skills can guide AI agents in tool selection.

Method

Define an MCP server for watsonx Orchestrate, then use prompts with Google Antigravity to generate agents and their associated tools, optionally guided by predefined skills.

In practice

• Use Antigravity to generate watsonx Orchestrate agents.
• Configure MCP servers for documentation access.
• Employ skills for complex agent development.

Topics

• watsonx Orchestrate
• Agentic Applications
• Google Antigravity
• Model Context Protocol
• AI Agent Development

Best for: AI Engineer, Machine Learning Engineer, Software Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by Niklas Heidloff.