"author:rui08984-dot" matching MCP servers:

Enables users to record probabilistic judgments in an immutable ledger, automatically score them against outcomes, and analyze systematic biases across six classification layers. It supports natural-language interaction for logging predictions, checking randomness, and auditing data integrity while avoiding advice or replacing user judgment.

Exposes Pi execution nodes to any MCP client so it can dispatch sub-tasks to local or cloud models, poll and cancel them, and get command-based acceptance, diff-based evidence chains and automatic escalation to stronger models on failure.