The evolution of AI brokers has led to highly effective, specialised fashions able to complicated duties. The Google Agent Improvement Package (ADK) – a toolkit designed to simplify the development and administration of language model-based functions – makes it straightforward for builders to construct brokers, often geared up with instruments through the Mannequin Context Protocol (MCP) for duties like net scraping. Nevertheless, to unlock their full potential, these brokers should be capable to collaborate. The Agent-to-Agent (A2A) framework – a standardized communication protocol that enables disparate brokers to find one another, perceive their capabilities, and work together securely – offers the usual for this interoperability.
This information offers a step-by-step course of for changing a standalone ADK agent that makes use of an MCP software into a completely A2A-compatible element, able to take part in a bigger, multi-agent ecosystem. We are going to use a MultiURLBrowser agent, designed to scrape net content material, as a sensible instance
Step 1: Outline the core agent and its MCP software (agent.py)
The inspiration of your agent stays its core logic. The secret is to correctly initialize the ADK LlmAgent and configure its MCPToolset to attach with its exterior software.
In agent.py, the _build_agent technique is the place you specify the LLM and its instruments. The MCPToolset is configured to launch the firecrawl-mcp software, passing the required API key by its setting variables
