Library Usage¶

ToolRegistry Hub is first and foremost a Python library. Every tool can be imported and called directly in your code — no server, no HTTP, no configuration files. This is the simplest and most flexible way to use the hub.

Library vs Server

	Library	Server
Install	`pip install toolregistry-hub`	`pip install toolregistry-hub[server]`
Usage	`from toolregistry_hub import ...`	`toolregistry-hub openapi`
Best for	Scripts, notebooks, AI agents, embedding in your app	Remote access, multi-client, MCP integration
Latency	Direct function call	HTTP / stdio round-trip
Dependencies	Minimal (mostly stdlib)	FastAPI, uvicorn, or MCP SDK

New here?

See Installation and Quick Start first.

Available Tools¶

Calculation & Conversion¶

from toolregistry_hub import Calculator, UnitConverter

# Calculator — evaluate expressions with built-in math functions
Calculator.evaluate("log(100, 10) + sin(pi/2)")  # 3.0
Calculator.list_allowed_fns()  # list all available functions
Calculator.help("log")  # get help on a specific function

# UnitConverter — convert between units
UnitConverter.convert(100, "celsius_to_fahrenheit")  # 212.0
UnitConverter.list_conversions(category="temperature")

Date & Time¶

from toolregistry_hub import DateTime

# Current time (default: UTC)
DateTime.now()

# Current time in a specific timezone
DateTime.now("America/New_York")

# Convert between timezones
DateTime.convert_timezone("14:30", "America/Chicago", "Asia/Tokyo")

File Operations¶

from toolregistry_hub import FileOps, FileReader, FileSearch, PathInfo

# Edit a file with exact string replacement
diff = FileOps.edit("config.py", old_string="DEBUG = True", new_string="DEBUG = False")
print(diff)  # unified diff output

# Read a file with line numbers
content = FileReader.read("src/main.py", limit=50)

# Read a Jupyter notebook
nb = FileReader.read_notebook("analysis.ipynb")

# Search for files
py_files = FileSearch.glob("**/*.py", path="src/")
matches = FileSearch.grep(r"def test_", path="tests/")
tree = FileSearch.tree("src/", max_depth=3)

# Get file metadata in one call
info = PathInfo.info("/path/to/file")
# → {exists, type, size, last_modified, permissions}

Shell Execution¶

from toolregistry_hub import BashTool

result = BashTool.execute("python --version", timeout=30, cwd="/my/project")
print(result)
# {
#     "stdout": "Python 3.11.5\n",
#     "stderr": "",
#     "exit_code": 0,
#     "timed_out": False
# }

BashTool has a built-in deny list that blocks dangerous commands (rm -rf /, sudo, fork bombs, etc.). See the Bash Tool page for the full security model.

Web Search & Fetch¶

from toolregistry_hub import Fetch, BraveSearch, TavilySearch
from toolregistry_hub.websearch import WebSearch

# Fetch and extract content from a URL
content = Fetch().fetch_content("https://example.com")

# Fetch with Jina Reader API key (optional, for authenticated access)
fetcher = Fetch(api_keys=["jina_key1", "jina_key2"])
content = fetcher.fetch_content("https://example.com")

# Unified web search — auto-selects the best available engine
ws = WebSearch()
results = ws.search("Python 3.12 new features", max_results=5)
for r in results:
    print(f"{r.title}: {r.url}")

# Specify a particular engine
results = ws.search("Python async", engine="brave", max_results=5)

# List available engines and their configuration status
engines = ws.list_engines()

# Direct engine usage (requires API keys via environment variables)
results = BraveSearch().search("Python 3.12 new features", max_results=5)
for r in results:
    print(f"{r.title}: {r.url}")

Scheduling¶

from toolregistry_hub import CronTool

# Schedule a recurring prompt (every 5 minutes)
job = CronTool.create(cron="*/5 * * * *", prompt="Check server health")

# Schedule a one-shot reminder
job = CronTool.create(
    cron="30 14 28 4 *",
    prompt="Deploy release to staging",
    recurring=False,
)

# List and manage scheduled jobs
jobs = CronTool.list()
CronTool.delete(job_id="abc123")

Cognitive Tools¶

from toolregistry_hub import ThinkTool, TodoList

# Structured thinking (useful as an LLM tool)
ThinkTool.think(
    thinking_mode="planning",
    focus_area="database migration",
    thought_process="We need to migrate from SQLite to PostgreSQL..."
)

# Task management
TodoList.update([
    "[db-migrate] Plan schema changes (planned)",
    "[db-migrate] Write migration script (in-progress)",
])

Use in AI Agents¶

The library shines when embedded in AI agent pipelines. Since every tool is a plain Python class with static methods, you can register them with any agent framework:

from toolregistry import ToolRegistry
from toolregistry_hub import Calculator, FileOps, BashTool, FileSearch

# Build a registry with selected tools
registry = ToolRegistry()
registry.register_static_tools(Calculator, namespace="calculator")
registry.register_static_tools(FileOps, namespace="file_ops")
registry.register_static_tools(BashTool, namespace="bash")
registry.register_static_tools(FileSearch, namespace="file_search")

# Generate tool schemas for your LLM
tools_json = registry.get_tools_json(format="openai")

Or use the hub's built-in registry that loads all tools at once:

from toolregistry_hub.server.registry import get_registry

registry = get_registry()  # all tools registered and ready

Environment Variables¶

Some tools require API keys. Tools without key requirements (Calculator, DateTime, FileOps, BashTool, etc.) work out of the box.

See Environment Variables Reference for the full list.