hoxcore 0.1.0

HoxCore - A meta-manager for organizational objects (projects, missions, activities, programs)

HoxCore

What is HoxCore?

HoxCore is a meta-manager — a low-level tool that centralizes the core metadata of organizational objects into a single, unified registry. Rather than managing execution or visualization directly, HoxCore acts as the foundational layer that independent software can build upon.

Organizational Object Types

HoxCore handles four categories of objects:

Type	Orientation	Description
Projects	Goal-oriented	Has a defined finalization point; decoupled from execution
Missions	Event-oriented	Linked to execution; tied to a specific occurrence or execution window
Activities	Action-oriented	No definite end; represents indefinite, ongoing progression
Programs	Container	Groups and organizes Projects, Missions, and/or Activities

Design Philosophy

HoxCore is intentionally minimal and low-level. It owns the metadata — everything else is up to you. Independent tools can be built on top of HoxCore for visualization, reporting, dashboards, or richer management interfaces, all reading from the same single source of truth.

Installation

From PyPI

pip install hxc

For Development

# Clone the repository
git clone https://github.com/SDEscobedo/hoxcore
cd hoxcore

# Create a virtual environment (optional but recommended)
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install in development mode
pip install -e .

Usage

$ hxc [command] [options]

Available Commands

• command1: Example command
• command2: Another example command

Examples

# Get help
$ hxc --help

# Get version information
$ hxc --version

# Get command-specific help
$ hxc command1 --help

# Execute commands
$ hxc command1 --option value
$ hxc command2 --flag input-value

---

MCP Server (Model Context Protocol)

HoxCore includes a built-in MCP server that exposes registry functionality to LLMs through a standardized interface. This allows AI assistants (like Claude) to interact with your HoxCore registries directly.

Starting the Server

# Start with the default or configured registry
hxc-mcp

# Start with a specific registry path
hxc-mcp --registry /path/to/your/registry

# Specify transport (currently only stdio is supported)
hxc-mcp --transport stdio

You can also start the server programmatically:

from hxc.mcp.server import create_server

server = create_server(registry_path="/path/to/registry")
server.run_stdio()

Connecting to Claude (or other MCP-compatible clients)

Add HoxCore to your MCP client configuration. For Claude Desktop, update your claude_desktop_config.json:

{
  "mcpServers": {
    "hoxcore": {
      "command": "hxc-mcp",
      "args": ["--registry", "/path/to/your/registry"]
    }
  }
}

Available Tools

The MCP server exposes four tools that an LLM can call:

Tool	Description
list_entities	List entities in the registry, with optional filters for type, status, tags, category, and parent
get_entity	Retrieve a specific entity by its ID or UID
search_entities	Full-text search across entity titles and descriptions
get_entity_property	Fetch a specific property from an entity, with support for list indexing and key filtering

Available Resources

Resources are accessible via hxc:// URIs:

URI	Description
hxc://entity/{identifier}	A specific entity by ID or UID (YAML)
hxc://entities/{type}	All entities of a given type (JSON)
hxc://hierarchy/{identifier}	Entity hierarchy and relationships (JSON)
hxc://registry/stats	Registry statistics and overview (JSON)
hxc://search?q={query}	Search results for a query (JSON)

Extending the Server

You can register custom tools, resources, and prompts at runtime:

from hxc.mcp.server import create_server

server = create_server()

# Register a custom tool
def my_tool(registry_path=None, **kwargs):
    """My custom tool description."""
    return {"result": "..."}

server.register_tool("my_tool", my_tool)

# Register a custom prompt
server.register_prompt({
    "name": "my_prompt",
    "description": "A helpful prompt template",
    "arguments": [
        {"name": "context", "description": "Context for the prompt", "required": True}
    ]
})

server.run_stdio()

---

Development

Project Structure

project/
├── LICENSE
├── README.md
├── pyproject.toml
├── setup.py
├── src/
│   └── hxc/
│       ├── __init__.py
│       ├── cli.py
│       ├── commands/
│       │   ├── __init__.py
│       │   ├── base.py
│       │   ├── command1.py
│       │   └── command2.py
│       ├── core/
│       │   ├── __init__.py
│       │   └── config.py
│       ├── mcp/
│       │   ├── __init__.py
│       │   ├── server.py
│       │   ├── tools.py
│       │   ├── resources.py
│       │   └── prompts.py
│       └── utils/
│           ├── __init__.py
│           └── helpers.py
└── tests/
    ├── __init__.py
    ├── conftest.py
    ├── test_cli.py
    └── commands/
        ├── __init__.py
        ├── test_command1.py
        └── test_command2.py

Adding New Commands

To add a new command to the CLI:

1. Create a new file in src/hxc/commands/ (e.g., mycommand.py)
2. Define a class that inherits from BaseCommand
3. Use the @register_command decorator to register it
4. Implement register_subparser and execute methods

Example:

from hxc.commands import register_command
from hxc.commands.base import BaseCommand

@register_command
class MyCommand(BaseCommand):
    name = "mycommand"
    help = "My custom command"
    
    @classmethod
    def register_subparser(cls, subparsers):
        parser = super().register_subparser(subparsers)
        parser.add_argument('--myflag', help='My flag')
        return parser
    
    @classmethod
    def execute(cls, args):
        # Implement command logic here
        return 0

Running Tests

Make sure you have development dependencies installed:

pip install -e ".[dev]"

Run the tests:

# Run all tests
pytest

# Run with coverage
pytest --cov=hxc

# Run specific tests
pytest tests/test_cli.py

Important Test Setup

The project uses a src/ layout for better package organization. Make sure you have a conftest.py file in your tests directory with the following content to ensure tests can import the package correctly:

# tests/conftest.py
import os
import sys
from pathlib import Path

# Add the src directory to the Python path
src_path = Path(__file__).parent.parent / "src"
sys.path.insert(0, str(src_path))

Distribution

Building the package

python -m build

Publishing to PyPI

python -m twine upload dist/*

License

MIT