mcp-logic
Fully functional AI Logic Calculator utilizing Prover9/Mace4 via Python based Model Context Protocol (MCP-Server)- tool for Windows, Linux, Claude App etc
Install / Use
claude mcp add angrysky56 -- npx -y github:angrysky56/mcp-logicIf the server publishes to npm under a different name, use that package instead — check the repo README.
MCP Server
Model Context Protocol server
Quality Score
Category
AI & Machine LearningSupported Platforms
Our assessment of mcp-logic
mcp-logic scores 86/100 on our quality scale, 535th of 963 AI & Machine Learning skills we index.
Its MCP Server is 6.8 KB long, well organised into 20 sections with 12 code examples: a thorough specification that gives an agent plenty to work with.
It has 47 GitHub stars, so there is little community track record yet; judge it on its content.
Maintenance, license and trust
- The repository was last updated about 3 months ago, so mcp-logic is actively maintained.
- Our last check on 2026-10-21 found the source still online.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 97/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.
AI review by kimi-k2.7-code on 2026-09-24. Automated pattern scan on 2026-09-24. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
mcp-logic compared with similar skills
All 4 of these similar skills score higher than mcp-logic; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| mcp-logic (this skill)by angrysky56 | 86 | 47 | 3mo ago | MCP Server |
| claude-memby thedotmack | 100 | 113.6k | today | CLAUDE.md |
| Agent-Reachby Panniantong | 100 | 109.3k | today | CLAUDE.md |
| Understand-Anythingby Egonex-AI | 100 | 91.0k | 11d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 79.0k | today | CLAUDE.md |
Frequently asked questions
- How do I install mcp-logic?
- Run
claude mcp add angrysky56 -- npx -y github:angrysky56/mcp-logic. The install tabs above show the steps for each supported agent. - Which AI agents does mcp-logic work with?
- It is written for Claude Code and Claude Desktop, as a MCP Server file. Other agents that read the same format can often use it too.
- Is mcp-logic safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It is MIT-licensed and scores 97/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is mcp-logic still maintained?
- The repository was last updated about 3 months ago, so mcp-logic is actively maintained.
Skill content
View source on GitHubMCP-Logic
An MCP server for automated first-order logic reasoning using Prover9 and Mace4.
Features
- Theorem Proving - Prove logical statements with Prover9
- Model Finding - Find finite models with Mace4
- Counterexample Finding - Show why statements don't follow
- Syntax Validation - Pre-validate formulas with helpful error messages
- Categorical Reasoning - Built-in support for category theory proofs
- Propositional Contingency - Purely analytical HCC prover for fast propositional checks
- Abductive Reasoning - Rank hypotheses using Variational Free Energy (VFE)
- Self-Contained - All dependencies install automatically
Quick Start
Installation
Linux/macOS:
git clone https://github.com/angrysky56/mcp-logic
cd mcp-logic
./linux-setup-script.sh
Windows:
git clone https://github.com/angrysky56/mcp-logic
cd mcp-logic
windows-setup-mcp-logic.bat
The setup script automatically:
- Downloads and builds LADR (Prover9 + Mace4)
- Creates Python virtual environment
- Installs all dependencies
- Generates Claude Desktop config
Claude Desktop Integration
Add to your Claude Desktop MCP config (auto-generated at claude-app-config.json):
{
"mcpServers": {
"mcp-logic": {
"command": "uv",
"args": [
"--directory",
"/absolute/path/to/mcp-logic",
"run",
"python",
"-m",
"mcp_logic",
"--prover-path",
"/absolute/path/to/mcp-logic/ladr/bin"
]
}
}
}
Important: Replace /absolute/path/to/mcp-logic with your actual repository path.
Available Tools
| Tool | Purpose | | ------------------------ | ------------------------------------------------------ | | prove | Prove statements using Prover9 | | check-well-formed | Validate formula syntax with detailed errors | | find_model | Find finite models satisfying premises | | find_counterexample | Find counterexamples showing statements don't follow | | verify_commutativity | Generate FOL for categorical diagram commutativity | | get_category_axioms | Get axioms for category/functor/group/monoid | | check_contingency | Check truth-functional contingency via HCC prover | | abductive_explain | Find the VFE-minimizing explanation for an observation |
Example Usage
Prove a Theorem
Use the mcp-logic prove tool with:
premises: ["all x (man(x) -> mortal(x))", "man(socrates)"]
conclusion: "mortal(socrates)"
Result: ✓ THEOREM PROVED
Analyze Propositional Contingency
Use the mcp-logic check_contingency tool with:
formula: "(p -> q) | (q -> p)"
Result: Identifies that the formula is a non-contingent tautology, returning the proof trace.
Find a Counterexample
Use the mcp-logic find-counterexample tool with:
premises: ["P(a)"]
conclusion: "P(b)"
Result: Model found where P(a) is true but P(b) is false, proving the conclusion doesn't follow.
Verify Categorical Diagram
Use the mcp-logic verify-commutativity tool with:
path_a: ["f", "g"]
path_b: ["h"]
object_start: "A"
object_end: "C"
Result: FOL premises and conclusion to prove that f∘g = h.
Running Locally
Instead of Claude Desktop, run the server directly:
Linux/macOS:
./run_mcp_logic.sh
Windows:
run_mcp_logic.bat
Project Structure
mcp-logic/
├── src/mcp_logic/
│ ├── server.py # Main MCP server (8 tools)
│ ├── mace4_wrapper.py # Mace4 model finder
│ ├── syntax_validator.py # Formula syntax validation
│ ├── categorical_helpers.py # Category theory utilities
│ ├── hcc_prover.py # Hypersequent Contingency Calculus prover
│ ├── vfe_engine.py # Variational Free Energy abductive engine
│ └── formula_ast.py # Propositional logic AST and parser
├── ladr/ # Auto-installed Prover9/Mace4 binaries
│ └── bin/
│ ├── prover9
│ └── mace4
├── tests/ # Test suite
├── linux-setup-script.sh # Linux/macOS setup
├── windows-setup-mcp-logic.bat # Windows setup
├── run_mcp_logic.sh # Linux/macOS run script
└── run_mcp_logic.bat # Windows run script
What's New in v0.3.0
Cognitive Architecture Enhancements:
- ✅ Hypersequent Contingency Calculus (HCC): Added a rigorous deductive checker for evaluating propositional formula contingencies instantly without brute-force modeling.
- ✅ Variational Free Energy (VFE) Engine: Implemented abductive reasoning that ranks hypotheses using a non-dogmatic Cournot-Gaifman prior to elegantly satisfy Ockham's Razor.
- ✅ Smart Prover Routing:
provetool automatically routes pure propositional queries to the HCC engine, and first-order queries to Prover9. - ✅ Configurable Model Finder:
find_modelandfind_counterexamplenow support custom timeouts and structured predicate/function extraction.
What's New in v0.2.0
Enhanced Features:
- ✅ Mace4 model finding and counterexample detection
- ✅ Detailed syntax validation with position-specific errors
- ✅ Categorical reasoning support (category theory axioms, commutativity verification)
- ✅ Structured JSON output from all tools
- ✅ Self-contained installation (no manual path configuration)
Development
Run tests:
source .venv/bin/activate
pytest tests/ -v
Test components directly:
python tests/test_enhancements.py
Documentation
ENHANCEMENTS.md- Quick reference for v0.2.0 featuresDocuments/- Detailed analysis and exampleswalkthrough.md- Implementation details (in artifacts)
Troubleshooting
"Prover9 not found" error:
- Run the setup script:
./linux-setup-script.shorwindows-setup-mcp-logic.bat - Check that
ladr/bin/prover9andladr/bin/mace4exist
Server not updating:
- Restart server after code changes
- Check logs for syntax errors
Syntax validation warnings:
- Use lowercase for predicates/functions (e.g.,
man(x)notMan(x)) - Add spaces around operators for clarity
- Balance all parentheses
License
MIT
Credits
- Prover9/Mace4: William McCune's LADR library
- LADR Repository: laitep/ladr
- Hypersequent Contingency Calculus (HCC): Based on the logical framework from "A Hypersequent Calculus for Classical Contingencies" by Eugenio Orlandelli, Giannandrea Pulcini, and Achille C. Varzi (2024).
Related Skills
claude-mem
113.6kPersistent Context Across Sessions for Every Agent – Captures everything your agent does during sessions, compresses it with AI, and injects relevant context back into future sessions. Works with Claude Code, OpenClaw, Codex, Gemini, Hermes, Copilot, OpenCode + More
Agent-Reach
109.3kGive your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.
Understand-Anything
91.0kGraphs that teach > graphs that impress. Turn any code into an interactive knowledge graph you can explore, search, and ask questions about. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.
headroom
79.0kCompress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Library, proxy, MCP server.
Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
