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Neo MCP Logic Analyze

@giseldo

Repository

Basic information

Category

Other

Transports

stdio

Author

giseldo

Submitted by

Giseldo Neo

About 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 config

Add this server to your MCP-compatible client using the configuration below.

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

Neo MCP Logic Analyze tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

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.

Frequently asked questions

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.

Comments

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