Glossary

This glossary defines terms and concepts used throughout the Hatch documentation.

A

Auto-approve : CLI flag (--auto-approve) that automatically approves dependency installations without user prompts, useful for automation scenarios.

C

Cache TTL : Time-to-live for cached registry data, configurable via --cache-ttl flag. Default is 86400 seconds (24 hours).

Conda : Python package and environment management system used by Hatch for creating isolated Python environments.

Current Environment : The active Hatch environment that commands operate on by default. Set using hatch env use <name>.

D

Dependency : A package or resource required by another package. Hatch supports multiple dependency types: Hatch packages, Python packages, system packages, and Docker images.

Dependency Installation Orchestrator : Component in hatch/installers/dependency_installation_orchestrator.py that coordinates the installation of multiple dependency types.

Docker Dependency : A Docker image required by a Hatch package, managed by the Docker installer.

E

Entry Point : The main file that serves as the executable entry point for a Hatch package, typically hatch_mcp_server_entry.py.

Environment : An isolated workspace for managing packages and their dependencies. Hatch environments can optionally include Python environments.

Environment Manager : Core component in hatch/environment_manager.py that handles environment lifecycle and management operations.

F

FastMCP : A Python framework for building Model Context Protocol servers, used as the base for Hatch package MCP server implementations.

Force Download : CLI flag (--force-download) that forces package download even if the package is already cached locally.

G

Global Options : CLI options available for all commands, including --envs-dir, --cache-ttl, and --cache-dir.

H

Hatch : Package manager for Model Context Protocol (MCP) servers that provides environment isolation and dependency management.

Hatch Compliant : Indicates whether a package follows Hatch packaging standards and metadata requirements.

Hatch Dependency : Another Hatch package required as a dependency, managed by the Hatch installer.

Hatch Environment : An isolated environment managed by Hatch for organizing packages and dependencies.

Hatch MCP Server Wrapper : Integration component (hatch_mcp_server) that bridges Hatch packages with MCP server functionality.

Hatch Package : A package that follows Hatch conventions and includes hatch_metadata.json with required metadata fields.

Hatchling : Related project in the Hatch ecosystem that provides additional functionality and tooling.

I

Installation Context : Object that manages state and context information during package installation processes.

Installer Base : Abstract base class in hatch/installers/installer_base.py that defines the interface for all installer types.

M

Mamba : Fast, drop-in replacement for conda package manager. Hatch prefers mamba when available for better performance.

MCP : Model Context Protocol - a standard for building AI-powered tools and integrations.

MCP Server : A server implementation that follows the Model Context Protocol standard, typically providing tools and resources for AI applications.

Metadata : Package information stored in hatch_metadata.json that defines package properties, dependencies, and compatibility requirements.

P

Package : A distributable unit of code that provides MCP server functionality. In Hatch, packages follow specific structure and metadata requirements.

Package Loader : Component in hatch/package_loader.py that loads and validates packages from local directories.

Package Schema Version : Version of the metadata schema used by a package, currently "1.2.0".

Python Dependency : A Python package installed via pip, managed by the Python installer.

Python Environment : A conda/mamba environment containing a specific Python version and packages, optionally created within Hatch environments.

Python Environment Manager : Component in hatch/python_environment_manager.py that manages Python environments within Hatch environments wrapping around conda/mamba in order to associate python environments with Hatch environments.

R

Refresh Registry : CLI flag (--refresh-registry) that forces refresh of registry data, bypassing cache.

Registry : Central repository for discovering and downloading Hatch packages.

Registry Explorer : Component in hatch/registry_explorer.py that provides package discovery and search capabilities.

Registry Retriever : Component in hatch/registry_retriever.py that handles package downloads and caching from the registry.

S

Schema : JSON schema definition that validates package metadata structure. Cracking Shells defines and uses schemas for its package ecosystem. It is hosted on a dedicated repository.

Semantic Versioning : Version numbering scheme using MAJOR.MINOR.PATCH format (e.g., 1.2.0).

System Dependency : A system package installed via OS package managers like apt, managed by the system installer.

T

Template Generator : Component in hatch/template_generator.py that creates new package templates with standard structure and files.

Tool : A function provided by an MCP server package, defined in the package metadata and exposed through the MCP interface.

V

Validation : Process of checking package structure and metadata against Hatch requirements and schema definitions.

Version Constraint : Specification of acceptable version ranges for dependencies using operators like >=, ==, <=, !=.

W

Workspace : Development environment containing multiple related projects and packages, such as the Hatch multi-project workspace.