We describe a prototype of trading system platform populated by agents who autonomously decide to buy and/or sell items according to a set of local needs which arise dynamically (also by possibly accessing information provided by pervasive devices) by in the process of fulfilling a given overall utility. The market has combinatorial nature in a way that items to be traded are combined into packages, in accordance with a principle that drives the nature of many current markets. However, differently from these, items belong to a number of distinct sellers distributed in the platform, and are chosen singularly on the basis of buyers preferences and needs. Agents are thus situation-aware, with sellers coming acquainted of the market demand, and buyers price offers, through a Knowledge Network. This latter drives the way market offers balance the demand by gathering the needed information in an autonomous way and taking advantage of pervasive devices. Packaging is realized by agent aggregation into Virtual Sellers, in an autonomous fashion, and we propose an opportunistic policy whereby aggregation is governed by a Combinatorial Auction. The market is studied through proof-of-concept simulation, where the efficiency deriving from the opportunistic aggregation based on Combinatorial Auctions and the influence of contextual self-awareness are studied. © 2008 IEEE.