The Model Context Protocol is an open standard created by Anthropic that enables AI assistants to securely access data and tools from various sources. MCP servers expose resources, prompts, and tools through a standardized interface.
mcpbr evaluates these servers through automated testing, benchmark scenarios, performance metrics, reliability testing, and compliance checking. It runs comprehensive test suites, measures response times and throughput, validates error handling, and ensures servers follow the MCP specification.
I drew inspiration from benchmarking frameworks like SWE-bench and CyberGym to provide rigorous evaluation capabilities for the MCP ecosystem.