This MCP server combines Google's Agent Development Kit (ADK) with the A2A framework and the Multi-Agent Control Protocol (MCP) to enable real-time, multi-agent coordination. The project is Python-based and expects a server entry point that initializes and runs the MCP-enabled agents. Once started, you can create and instantiate agents, register them with the MCP runtime, and enable inter-agent communication and control flows that MCP governs. The included concepts of A2A facilitate agent-to-agent messaging, while MCP provides orchestration and governance for interactions across the MAS.

To use the server tools effectively, start the MCP server, then deploy agents that extend a base Agent class. Agents can implement task-specific methods and leverage A2A messaging to request services from peers, coordinate with other agents, and respond to environmental events. The MCP layer helps you define protocols for task assignments, monitoring, and coordination policies, allowing scalable multi-agent workflows across the MAS.

Prerequisites:

• Python 3.8+ installed on your system
• Access to install Python packages via pip
• Optional: a zip bundle containing the ADK/MCP components as referenced in the repository

Installation steps:

1. Clone or download the repository bundle you plan to run (the ZIP release mentioned in the README): git clone https://github.com/Roji-val/A2A_ADK_MCP.git

2. Create and activate a virtual environment (recommended): python -m venv venv

   Windows

   venv\Scripts\activate

   macOS/Linux

   source venv/bin/activate

3. Install dependencies listed for the MCP server. If there is a requirements file in the bundle, use: pip install -r requirements.txt or install from the provided zip/release per the repository's instructions.

4. Prepare configuration and entry point. Ensure you have the server entry file (e.g., server.py) and any necessary config.yaml in place as referenced by your mcp_config.

5. Run the MCP server using the specified command (as described in mcp_config): python server.py

6. Verify the server starts correctly and the agents can be instantiated and communicate using A2A/MCP features.

Tips and potential issues:

• Ensure Python 3.x compatibility with all dependencies in the bundle; some ADR/ADK components may require specific versions.
• If the bundle requires linking to external releases, confirm the URLs are accessible and the ZIP release contains the expected server entry file (e.g., server.py).
• For environment variables, set A2A_MCP_CONFIG to point to your runtime configuration file if you have custom MCP policies.
• When debugging, run with PYTHONUNBUFFERED=1 to get real-time log output and check for import or path errors related to the server or ADK components.
• If you encounter network-related issues between agents, verify that any required ports are open and not blocked by a firewall.
• The README references a zipped release; ensure you are pointing to a valid entry script inside that release or adjust the mcp_config to the actual entry point.
• This configuration is a starting point. Modify the env and command arguments to match your specific deployment scenario and the actual entry module provided by your release.