Metadata-Version: 2.4
Name: cailculator-mcp
Version: 1.0.0
Summary: CAILculator MCP Server - High-dimensional data analysis with dual algebra frameworks for Claude
Author-email: Paul Chavez <paul@chavezailabs.com>
License: MIT
Project-URL: Homepage, https://github.com/pchavez2029/cailculator-mcp
Project-URL: Documentation, https://github.com/pchavez2029/cailculator-mcp#readme
Project-URL: Repository, https://github.com/pchavez2029/cailculator-mcp
Project-URL: Issues, https://github.com/pchavez2029/cailculator-mcp/issues
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Physics
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: mcp>=0.9.0
Requires-Dist: numpy>=1.24.0
Requires-Dist: scipy>=1.10.0
Requires-Dist: pydantic>=2.0.0
Requires-Dist: pydantic-settings>=2.0.0
Requires-Dist: python-dotenv>=1.0.0
Requires-Dist: httpx>=0.27.0
Requires-Dist: matplotlib>=3.7.0
Requires-Dist: networkx>=3.0
Requires-Dist: hypercomplex>=0.3.4
Requires-Dist: clifford>=1.5.0
Provides-Extra: dev
Requires-Dist: pytest>=7.0.0; extra == "dev"
Requires-Dist: pytest-asyncio>=0.21.0; extra == "dev"
Requires-Dist: black>=23.0.0; extra == "dev"
Requires-Dist: ruff>=0.1.0; extra == "dev"
Provides-Extra: premium
Requires-Dist: plotly>=5.18.0; extra == "premium"
Requires-Dist: kaleido>=0.2.1; extra == "premium"
Provides-Extra: web
Requires-Dist: gradio>=4.0.0; extra == "web"
Dynamic: license-file

# CAILculator MCP Server

High-dimensional data analysis via Model Context Protocol.

Powered by proprietary Chavez Transform technology with proven mathematical foundations.

## Features

- **Advanced Pattern Detection**: Find hidden structures in high-dimensional data
- **Framework-Independent Analysis**: Works across different mathematical representations
- **Proven Reliability**: Built on verified mathematical theorems
- **Scales from 16D to 256D**: Handles complexity traditional methods can't

## Installation

```bash
pip install cailculator-mcp
```

## Setup

Add to your MCP client configuration (example for Claude Desktop):

**Mac/Linux:** `~/Library/Application Support/Claude/claude_desktop_config.json`
**Windows:** `%APPDATA%\Claude\claude_desktop_config.json`

```json
{
  "mcpServers": {
    "cailculator": {
      "command": "cailculator-mcp",
      "env": {
        "CAILCULATOR_API_KEY": "your_api_key_here"
      }
    }
  }
}
```

Contact paul@chavezailabs.com for API key access.

**Free for educators and students!**

## Usage

```
"Apply Chavez Transform to this dataset"
"Detect patterns in my high-dimensional data"
"Analyze this data for hidden structures"
```

## Available Tools

### chavez_transform
Apply proprietary transform for high-dimensional analysis.

### detect_patterns
Find conjugation symmetries and structural patterns.

### analyze_dataset
Complete end-to-end analysis pipeline.

## Pricing

- **Individual**: $79.99/month
- **Academ**: $199/month
- **Commercial**: $299/month per seat
- **Enterprise**: Multiple API keys, contact for pricing


## Research Foundation

Built on research published at DOI: [10.5281/zenodo.17402496](https://zenodo.org/records/17402496)

Incorporates recent mathematical discoveries connecting to E8 exceptional Lie algebra (October 2025).

## Contact

Email: iknowpi@gmail.com
GitHub: https://github.com/pchavez2029/cailculator-mcp

---

**Chavez AI Labs** - *"Better math, less suffering"*
