Show HN: Maverik – Benchmark, compare and cost-predict your MCP agents (github.com)

MAVERIK, a new benchmarking tool for Model Context Protocol (MCP) agents, has been introduced, drawing parallels to JMeter's performance testing framework. This tool allows AI developers to benchmark, compare, and predict costs for their MCP agent configurations by measuring key parameters such as correctness, speed, and resource consumption. By establishing a workflow that first defines outcome benchmarks (acceptable answer accuracy, latency, token usage) before testing various configurations, MAVERIK eliminates guesswork in optimizing agent performance. The significance of MAVERIK lies in its ability to provide actionable insights and extensive data-driven evaluations for AI agents, a crucial step for improving efficiency in real-world applications. Users can define specific agent configurations, run extensive test suites, and view detailed results that include wall-clock duration, token consumption, and estimated operational costs. With features such as interactive chat for testing agent responses and Docker-based deployment, MAVERIK streamlines the process of optimizing AI agents, making it invaluable for the AI/ML community striving for accuracy and cost-effectiveness in deploying language models and their tools.