  As AI Agents based on Large Language Models (LLMs) have shown potential in
practical applications across various fields, how to quickly deploy an AI agent
and how to conveniently expand the application scenario of AI agents has become
a challenge. Previous studies mainly focused on implementing all the reasoning
capabilities of AI agents within a single LLM, which often makes the model more
complex and also reduces the extensibility of AI agent functionality. In this
paper, we propose CACA Agent (Capability Collaboration based AI Agent), using
an open architecture inspired by service computing. CACA Agent integrates a set
of collaborative capabilities to implement AI Agents, not only reducing the
dependence on a single LLM, but also enhancing the extensibility of both the
planning abilities and the tools available to AI agents. Utilizing the proposed
system, we present a demo to illustrate the operation and the application
scenario extension of CACA Agent.
