"author:RudrenduPaul" matching MCP servers:

MCP server exposing statistical regression testing for LLM agents as a "run" tool: p-value, effect size, and confidence interval on whether agent behavior actually changed.

MCP server exposing AI agent observability tools: list, inspect, and deterministically replay recorded agent execution traces for debugging failures.

MCP server exposing a "run" tool that benchmarks agent-memory backends and returns a reproducible JSON report.

Vendor-neutral CLI and MCP server that verifies the token and cost savings AI-coding-agent context-reduction proxies actually deliver, measured against a real labeled corpus.

MCP server wrapping the slop-eval CLI as a single generic run tool for genericness scoring of AI-generated UI output.

MCP server wrapping the evolveguard CLI as a single generic run tool for agent-skill file safety checks.

MCP server wrapping the ContinuityGuard CLI as a single generic run tool for video-clip continuity scans.

Enables comparison of responses from multiple LLMs (OpenAI, Anthropic, Gemini) to the same prompt, returning a validated divergence score based on sentence embeddings.

Exposes a run_suite tool to evaluate whether an AI agent is safe to operate internal web apps, scoring task completion and forbidden-action violations to gate CI/CD pipelines.