AI-Parrot Tools
ai-parrot-tools is a collection of tools and toolkits for AI-Parrot agents. Each tool wraps an external API or service behind a unified interface that agents can discover and invoke automatically.
Installation
pip install ai-parrot-tools
Install only the extras you need:
# Individual extras
pip install ai-parrot-tools[aws]
pip install ai-parrot-tools[slack]
pip install ai-parrot-tools[jira]
pip install ai-parrot-tools[google]
pip install ai-parrot-tools[finance]
pip install ai-parrot-tools[db]
# Everything
pip install ai-parrot-tools[all]
Available Extras
| Extra | Description |
|---|---|
jira |
Jira issue tracking |
slack |
Slack messaging |
aws |
AWS services (EC2, S3, RDS, Lambda, ECS, IAM, etc.) |
docker |
Docker container management |
git |
Git repository operations |
analysis |
Data analysis with pandas, numpy, autoviz |
excel |
Excel and ODF spreadsheet support |
sandbox |
Sandboxed code execution via Docker |
codeinterpreter |
Interactive code interpreter |
pulumi |
Pulumi infrastructure-as-code |
sitesearch |
Website crawling and search |
office365 |
Microsoft 365 / Graph API integration |
scraping |
Web scraping with Selenium |
finance |
Financial analysis (TA-Lib, yfinance, Alpaca) |
db |
Database querying via QuerySource |
flowtask |
FlowTask workflow integration |
google |
Google APIs (Search, Maps, Routes) |
arxiv |
arXiv paper search |
wikipedia |
Wikipedia lookups |
weather |
OpenWeatherMap |
messaging |
MQTT and IMAP messaging |
workday |
Workday SOAP/REST interfaces (zeep, pandas, aiohttp) — see parrot_tools.interfaces.workday |
Quick Start
from parrot.bots import Agent
agent = Agent(
name="assistant",
instructions="You are a helpful assistant.",
tools=["google_search", "weather", "calculator"],
)
response = await agent.chat("What's the weather in New York?")
Tools are registered by name. Pass a list of tool names to any AI-Parrot agent and they are loaded on demand.
Creating Custom Tools
Use the @tool decorator for simple functions:
from parrot.tools import tool
@tool
def get_stock_price(symbol: str) -> str:
"""Get the current stock price for a ticker symbol."""
...
Use AbstractToolkit for multi-tool collections:
from parrot.tools import AbstractToolkit
class MyToolkit(AbstractToolkit):
name = "my_toolkit"
description = "A collection of related tools."
def get_tools(self):
...
Requirements
- Python >= 3.11
- ai-parrot >= 0.23.18
License
MIT
1 maintainer
Metadata
1 maintainer
Release files for ai-parrot-tools 1.0.7
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| ai_parrot_tools-1.0.7.tar.gz | 1.7 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| ai_parrot_tools-1.0.7-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 3.5 MB
Release files / ai_parrot_tools-1.0.7.tar.gz
| Download URL | ai_parrot_tools-1.0.7.tar.gz |
|---|---|
| Size | 1.7 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Transparency logRelease files / ai_parrot_tools-1.0.7-py3-none-any.whl
| Download URL | ai_parrot_tools-1.0.7-py3-none-any.whl |
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| Size | 1.8 MB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
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PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 1, 2026.
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