Skip to main content

Agent Utilities for Pydantic AI Agents

Project description

Agent Utilities - Pydantic AI Utilities

PyPI - Version MCP Server PyPI - Downloads GitHub Repo stars GitHub forks GitHub contributors PyPI - License GitHub

GitHub last commit (by committer) GitHub pull requests GitHub closed pull requests GitHub issues

GitHub top language GitHub language count GitHub repo size GitHub repo file count (file type) PyPI - Wheel PyPI - Implementation

Version: 0.2.2

Overview

Agent Utilities provides a robust foundation for building production-ready Pydantic AI Agents. It simplifies agent creation, adds multi-agent supervisor patterns, and provides essential "operating system" tools for agents, including workspace management, scheduling, and discovery.

Key Features

  • Agent Creation: Streamlined create_agent function that handles MCP servers, skills, and model configuration automatically.
  • Multi-Agent Support: Native support for the supervisor pattern, allowing complex tasks to be delegated to specialized child agents.
  • Agent Server: Built-in FastAPI server (create_agent_server) with SSE support for easy integration into web UIs and A2A networks.
  • Workspace Management: Automated management of agent state through standard markdown files (IDENTITY.md, MEMORY.md, USER.md).
  • A2A Integration: Seamless discovery and communication between agents in a distributed network.
  • Periodic Scheduler: In-memory task scheduler for running background agent jobs.
  • Lightweight & Lazy: Core utilities are lightweight. Heavy dependencies like FastAPI or LlamaIndex are lazy-loaded only when requested via optional extras.

Installation

# Core utilities only
pip install agent-utilities

# With full agent support (recommended)
pip install agent-utilities[agent]

# With MCP server support
pip install agent-utilities[mcp]

# With embedding/vector support
pip install agent-utilities[embeddings]

Quick Start

from agent_utilities import create_agent

# Create a simple agent with workspace tools
agent = create_agent(name="MyAgent")

# Or create a multi-agent supervisor
agent = create_agent(
    name="Supervisor",
    agent_definitions=[{"name": "Researcher", "description": "Search the web"}]
)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

agent_utilities-0.2.2.tar.gz (31.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

agent_utilities-0.2.2-py3-none-any.whl (35.8 kB view details)

Uploaded Python 3

File details

Details for the file agent_utilities-0.2.2.tar.gz.

File metadata

  • Download URL: agent_utilities-0.2.2.tar.gz
  • Upload date:
  • Size: 31.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.3

File hashes

Hashes for agent_utilities-0.2.2.tar.gz
Algorithm Hash digest
SHA256 66a88554a1b44b83f515b52a7f83e22ee3d3058f8470013fd4a0d0cbfcc0ac0b
MD5 0d0cad6fa9ca132fe182266eaee859d9
BLAKE2b-256 148dc178ec33ba82483f5dc0d9377271d8b0484607b7f1ee4e8c3a77be04fc0c

See more details on using hashes here.

File details

Details for the file agent_utilities-0.2.2-py3-none-any.whl.

File metadata

File hashes

Hashes for agent_utilities-0.2.2-py3-none-any.whl
Algorithm Hash digest
SHA256 e2b9957d75e73e7e898e93a34fc0171b65f607a81fb3f451ad2df8101123fbaf
MD5 79696ad3b5ced4ab14051be2ce79fba0
BLAKE2b-256 e67211fdae2f33c522db98a251007ebfb215b6ab43808cb108636944e1d700ee

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page