TY  - JOUR
T1  - EREBOTS 4.0: A framework for conversational assistants with A2A agents and MCP tools
A1  - Pacioni, Elia
A1  - Calvaresi, Davide
A1  - Coman, Andrei C.
A1  - Jaggi, Ismael
A1  - Crocetti, Valerio
A1  - Manzo, Gaetano
A1  - Schumacher, Michael
JA  - arxiv
Y1  - 2026
UR  - https://arxiv.org/abs/2610.36221
M2  - doi: https://doi.org/10.48550/arXiv.2610.36221
KW  - agent interoperability
KW  - Agent2Agent protocol
KW  - Agentic AI
KW  - conversational assistants
KW  - Model Context Protocol
KW  - Multi-Agent Systems
N2  - In recent years, multi-agent systems have shifted from rule-based, symbolic agents to sub-symbolic agents built on language models. However, several limitations remain unresolved. The new frontier is neuro-symbolic agents, which pair language models with deterministic tools and explicit protocols. Without a common framework to standardize and compose them, each study rebuilds the same infrastructure, and results are hard to replicate. This paper presents EREBOTS 4.0, an open-source, hybrid-AI, multi-agent framework that fills this gap for conversational assistants. Language-model agents plan and route requests, while deterministic tools compute exact results over the Model Context Protocol (MCP). An orchestrator selects one or more specialist agents per turn and calls them over the Agent2Agent protocol (A2A). A new agent, local or remote, is added by listing its URL in a configuration file. The framework also manages identity, user context with consent flags, task states and traces. Its A2A server passed 97 tracked requirements in the official A2A Technology Compatibility Kit, with no failures.
ER  -