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Hatchling

@CrackingShells

About Hatchling

The CLI-based chat interface optimized for the Hatch! packages (i.e. MCP server packages).

Basic information

Category

Other

License

AGPL-3.0

Runtime

python

Transports

stdio

Publisher

CrackingShells

Config

No standard config provided

This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.

Repository

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Hatchling?

Hatchling is an interactive CLI-based chat application that integrates local Large Language Models (LLMs) through Ollama and OpenAI with the Model Context Protocol (MCP) for tool calling capabilities. It serves as the frontend for using all MCP servers in the Hatch ecosystem.

How to use Hatchling?

Installation and running are guided through Docker setup and configuration steps provided in the documentation. Users can extend Hatchling with custom MCP tools by creating Hatch packages using the hatch:create command and defining tools with the @hatch_mcp.tool() decorator, then adding the package with hatch:pkg:add and connecting via mcp:server:connect.

Key features of Hatchling

  • CLI-based chat interface with syntax highlighting and command auto-completion
  • Integrates Ollama and OpenAI LLMs with MCP tool calling
  • Tool execution wrapping to support longer tool calling chains
  • Extensible via custom Hatch packages for new MCP servers
  • Displays token usage, MCP server lifecycle, and tool chaining information

Use cases of Hatchling

  • Building custom AI assistants that leverage MCP tools for specialized tasks
  • Integrating local LLMs with biological data analysis and modeling software
  • Managing collections of MCP servers with environment and package management
  • Developing and testing new MCP tools using the Python SDK decorator patterns

FAQ from Hatchling

What LLM providers does Hatchling support?

Hatchling integrates with Ollama for local LLMs and OpenAI for cloud-based models, with a standardized interface to add more providers in the future.

How can I extend Hatchling with custom MCP tools?

Create a Hatch package using the hatch:create command, then define tools with the @hatch_mcp.tool() decorator inside server.py, following the patterns from the MCP Python SDK.

What is the Hatch ecosystem?

Hatchling is part of a larger ecosystem including Hatch (package manager), Hatch-Schemas, Hatch-Validator, and Hatch-Registry, providing comprehensive MCP server creation, management, and discovery.

Can I manage multiple MCP server environments?

Yes, Hatchling integrates the Hatch package manager with built-in commands for environment management, package installation, and switching MCP server collections.

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