# Logic (Prover9/Mace4)

> Use this tool when you need to automate reasoning, validate knowledge, or perform logical proofs in AI systems. It solves problems in theorem proving, model verification, and syntax validation, accepting logical statements as input and producing proofs or countermodels as output. Ideal for use in AI assistants, knowledge validation, and formal verification of logical arguments, particularly when dealing with complex logical implications or nested quantifiers.

Canonical page: https://skillsregistry.net/skills/angrysky56-logic  
JSON: https://api.skillsregistry.net/v1/skills/angrysky56-logic

## Description

This MCP-Logic server, developed by an AI researcher, provides automated reasoning capabilities using Prover9/Mace4 for AI systems. Built with Python 3.12+ and leveraging the MCP library, it offers tools for theorem proving, model verification, and syntax validation of logical statements. The implementation focuses on bridging formal logic with AI, enabling knowledge validation and complex reasoning. It's particularly useful for AI assistants or applications needing to perform logical proofs, verify knowledge representations, or analyze logical implications. The server supports nested quantifiers and multiple premises, making it suitable for tasks like validating AI knowledge models, reasoning about system behaviors, or formal verification of logical arguments.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** productivity
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/angrysky56-logic)
- **Repository:** <https://github.com/angrysky56/mcp-logic>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "angrysky56-logic"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/angrysky56-logic` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/angrysky56-logic/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt