[](https://glama.ai/mcp/servers/rikarazome/prolog-reasoner) - SWI-Prolog execution for LLMs with CLP(FD), negation-as-failure, and recursion. Benchmarked 90% vs 73% LLM-only accura…
Everything here was measured by our prober or read from a registry. Nothing is self-reported.
Not distributed through a package registry we index.
Attributed to the source that supplied each field. Treated as claims, not facts.
[](https://glama.ai/mcp/servers/rikarazome/prolog-reasoner) - SWI-Prolog execution for LLMs with CLP(FD), negation-as-failure, and recursion. Benchmarked 90% vs 73% LLM-only accuracy on 30 logic problems.
Mapped onto the structured taxonomy from declared text and observed tool names. Confidence shown for derived entries.
Every source is kept verbatim. Field changes are logged as events.