rikarazome/prolog-reasoner
by Various
SWI-Prolog as a logic calculator for LLMs — MCP server and Python library
MCP
rikarazome/prolog-reasoner
Added 1 June 2026
Overview
A tool that provides an MCP server and Python library to use SWI-Prolog as a logic calculator for large language models. It enables LLMs to perform logical reasoning by invoking Prolog queries through a standardized interface.
Best for
Best for
Developers building LLM agents that need reliable, rule-based logical inference
Use cases
- Running rule-based inference tasks within an LLM workflow
- Validating logical constraints generated by an LLM
- Combining natural language output with Prolog's deterministic deduction
Notes
A tool that provides an MCP server and Python library to use SWI-Prolog as a logic calculator for large language models. It enables LLMs to perform logical reasoning by invoking Prolog queries through a standardized interface.
8 stars on GitHub. Last updated 2026-05-01. Licensed MIT.
Use cases
- Running rule-based inference tasks within an LLM workflow
- Validating logical constraints generated by an LLM
- Combining natural language output with Prolog’s deterministic deduction
Pros
- Leverages Prolog’s mature reasoning engine for consistent logical output
- Exposes logic calculus as an MCP server, compatible with LLM tool-use patterns
- Simple Python library for embedding Prolog query execution
Cons
- Small community and limited production usage (8 GitHub stars)
- Requires familiarity with Prolog syntax and logic programming
- Narrow focus only useful if LLM task needs formal deductive reasoning
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Leverages Prolog's mature reasoning engine for consistent logical output
- Exposes logic calculus as an MCP server, compatible with LLM tool-use patterns
- Simple Python library for embedding Prolog query execution
Cons
- Small community and limited production usage (8 GitHub stars)
- Requires familiarity with Prolog syntax and logic programming
- Narrow focus only useful if LLM task needs formal deductive reasoning
Pairs with
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