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Neo MCP Logic Analyze

@giseldo

代码仓库

基本信息

分类

其他

传输方式

stdio

作者

giseldo

提交者

Giseldo Neo

关于 Neo MCP Logic Analyze

Python MCP server for controlled logic analysis from natural language, with an emphasis on auditable output and teaching-oriented explanations.

#logic#formal-logic#natural-language#argument-analysis#propositional-logic#predicate-logic#reasoning#inference#proof-checking#symbolic-reasoning#education

Neo MCP Logic Analyze 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "neo-mcp-logic-analyze": {
      "command": "neo-mcp-logic-analyze"
    }
  }
}

Neo MCP Logic Analyze 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is neo-mcp-logic-analyze?

neo-mcp-logic-analyze is a Python MCP server that provides controlled logic analysis from natural-language statements and arguments. It emphasizes auditable output and teaching-oriented explanations, making it suitable for educators, students, and developers who need structured logical formalization, ambiguity detection, consistency/entailment checking, and counterexample generation.

How to use neo-mcp-logic-analyze?

Install the package with pip install . after cloning the repository. The server is designed to be launched by an MCP client (e.g., Claude Desktop, Cursor) over stdio. Configure the client with the command neo-mcp-logic-analyze. Then invoke the exposed tools, resources, or prompts from your MCP host.

Key features of neo-mcp-logic-analyze

  • Tool nl_parse_logic for structured formalization into propositional or first-order logic.
  • Ambiguity detection via detect_ambiguities (e.g., quantifier‑scope issues).
  • Consistency checking (check_consistency) with unsat core support.
  • Entailment checking (check_entailment) with proof sketches.
  • Counterexample search (find_counterexample) when entailment fails.
  • Teaching‑oriented prompts (teach_logic_step_by_step, review_formalization).

Use cases of neo-mcp-logic-analyze

  • Automatically formalize natural‑language arguments for logic exercises or automated reasoning pipelines.
  • Help students understand logical structure by explaining formalization choices step‑by‑step.
  • Detect ambiguous phrasing in statements before rigorous analysis.
  • Verify the logical validity of short arguments (e.g., “If A then B; A, therefore B”).
  • Generate counterexamples to illustrate invalid inferences in classroom settings.

常见问题

1

What runtime does neo-mcp-logic-analyze require?

Python 3.11 or later.

2

How is the server launched?

It is launched by an MCP client over stdio. The command is `neo-mcp-logic-analyze` (the installed package entry point). The process waits for a client connection until interrupted.

3

Can this server handle long or complex texts?

No. The project is optimized for short inputs; natural‑language interpretation is heuristic and intentionally restricted. Long free‑form texts are not supported.

4

What types of logic are supported?

Propositional logic and a restricted fragment of first‑order logic (FOL).

5

Does the server provide explanations for its outputs?

Yes. The `explain_formalization` tool and the `teach_logic_step_by_step` prompt offer natural‑language explanations of the formalization process.

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