Enables building and running custom LLM benchmarks with multi-judge evaluation, supporting GUI, MCP client, and CLI usage for ranked, auditable results.
A neutral verification court for AI tools that ranks MCP servers by executing them against ground truth and recording results. Enables agents to consult execution records, contribute verdicts, and challenge claims.
Enables LLM-as-judge text quality evaluation via MCP, scoring original-revised pairs with multi-axis weighted rubrics, testing scorer models against labeled golden sets, and cross-validating agreement between two scorers.
A local, evidence-driven MCP runtime and control plane for open-source maintainers that provides workspace-bounded tools including controlled file operations, command execution, validation primitives, durable execution records, and human review workflows via stdio and Streamable HTTP transports.