MCPEval is an automated MCP-based framework that generates, verifies, and scores LLM agent tool-use tasks; its experiments reveal a consistent gap between how well agents execute tool calls and how well they synthesize final answers.
Peak Age of Information under Tandem of Queues
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abstract
This paper considers a communication system where a source sends time-sensitive information to its destination via queues in tandem. We assume that the arrival process as well as the service process (of each server) are memoryless, and each of the servers has no buffer. For this setup, we develop a recursive framework to characterize the mean peak age of information (PAoI) under preemptive and non-preemptive policies with $N$ servers having different service rates. For the preemptive case, the proposed framework also allows to obtain mean age of information (AoI).
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MCPEval: Automatic MCP-based Deep Evaluation for AI Agent Models
MCPEval is an automated MCP-based framework that generates, verifies, and scores LLM agent tool-use tasks; its experiments reveal a consistent gap between how well agents execute tool calls and how well they synthesize final answers.