magetools 1.3.0

Dynamic tool discovery for AI agents using the MCP-Zero Active Discovery pattern

Magetools

A Portable Grimorium for Agentic Tool Discovery.

Magetools gives autonomous AI agents scalable access to thousands of tools ("Spells") without overwhelming their context window. It uses a Hierarchical Active Discovery pattern to organize tools into collections/directories ("Grimoriums") and files ("Chapters") and functions ("Spells"), allowing agents to discover only what they need, when they need it.

Features

• 100% Test Coverage: Fully verified core logic for maximum reliability.
• Active Discovery Protocol: Agents search for capabilities, not specific function names.
• Safe by Default: Strict Mode requires explicit manifest.json to load any code.
• Auto-Summarization: Uses Google Gemini to automatically generate technical summaries for your tool collections (Performance optimized: non-blocking).
• Stale Summary Detection: Automatically detects code changes via folder hashing and triggers re-summarization via CLI.
• Google ADK Integration: Works with Google ADK agents with more framework integrations coming soon.
• Graceful Degradation: Works without API keys using MockProvider (limited functionality).

Installation

Using uv (Recommended):

# Core package (minimal dependencies)
uv add magetools

# Full installation with all features
uv add magetools[full]

Using pip:

pip install magetools[full]

Optional Dependencies

Extra	Description
[google]	Google GenAI provider for embeddings and summaries
[vectordb]	ChromaDB for vector storage
[adk]	Google ADK integration for agents
[full]	All of the above

Usage

Quick Start

# 1. Create a Grimorium(folder) in the .magetools directory
mkdir -p .magetools/file_ops

# 2. Creates the manifest.json for the provided Grimorium(required for Strict Mode)
uv run -m magetools init .magetools/file_ops

# 3. Scan the Grimorium for spells(functions)
# This creates a grimorium_summary.md file with the technical summary of the spells
# and stores the vector embeddings of the spells in a vector database
uv run -m magetools scan

Add Spells (Tools)

# .magetools/file_ops/files.py (A Grimorium chapter is just a .py file in a Grimorium.)
from magetools import spell

@spell
def list_files(path: str = "."):
    """Lists all files in the given directory."""
    import os
    return os.listdir(path)

@spell
def read_file(path: str):
    """Reads and returns the contents of a file."""
    with open(path, "r") as f:
        return f.read()

Use with an Agent

from google.adk.agents import LlmAgent
from magetools import Grimorium


# Initialize (scans .magetools folder and indexes spells)
grimorium = Grimorium()

# Initialize the root agent
root_agent = LlmAgent(
    name="magetools_agent",
    model="gemini-2.5-flash",
    description="Agent that uses magetools to discover and execute spells.",
    instruction=f"""You are an advanced AI assistant with access to magetools.
    Be helpful, concise, and focus on solving the user's request effectively.
    {grimorium.usage_guide}""",
    tools=[grimorium],
)

Agent Discovery Flow

A Magetools Grimorium exposes 3 tools to your agent:

1. discover_grimoriums(query) – Search for a grimorium using a query
2. discover_spells(grimorium_id, query) – Search for a spell within a grimorium
3. execute_spell(spell_name, arguments) – Run a spell

Example:

User: "Find and read the data.csv file."

Agent:

1. discover_grimoriums("file reading") → file_ops
2. discover_spells("file_ops", "read csv") → read_file
3. execute_spell("file_ops.read_file", {"path": "data.csv"})

Strict Mode (Security)

⚠️ Magetools runs in Strict Mode by default.

Grimoriums require a manifest.json file to load any Python code. This prevents accidental execution of arbitrary code.

# Enable a grimorium
uv run -m magetools init .magetools/my_grimorium

manifest.json example:

{
  "version": "1.0",
  "enabled": true,
  "whitelist": ["list_files", "read_file"]
}

To disable Strict Mode (development only):

grimorium = Grimorium(strict_mode=False)

Configuration

Environment Variables

Variable	Default	Description
GOOGLE_API_KEY	–	Required for Google GenAI (can be set in .env file)
MAGETOOLS_MODEL	gemini-2.5-flash	LLM model for technical summaries
MAGETOOLS_DEBUG	false	Enable debug logging

YAML Configuration

Create magetools.yaml in your project root:

model_name: gemini-2.5-flash
embedding_model: models/text-embedding-004
debug: false

CLI Reference

uv run -m magetools init <directory>  # Generate manifest.json for a grimorium
uv run -m magetools scan              # Scan spells and build metadata summaries
uv run -m magetools --help            # Show all commands and options

Support

• Documentation: Full documentation site
• Issues: GitHub Issues
• Discussions: Open an issue for questions

Roadmap

• Local embedding provider (no API key required)
• LangChain integration example
• Web UI for spell management

Contributing

Contributions are welcome! Please:

1. Fork the repository
2. Create a feature branch
3. Run tests: uv run pytest
4. Submit a pull request

For major changes, open an issue first to discuss.

Authors

• Malcom Godlike - Initial work

License

MIT

Project Status

🚀 Active Development – This project is actively maintained and accepting contributions.