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: 0.2.21

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.
  • Elicitation Support: Built-in flow for handling structured user input requests from MCP servers, seamlessly integrated with the Web UI.
  • 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-0.2.21.tar.gz (45.2 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-0.2.21-py3-none-any.whl (49.6 kB view details)

Uploaded Python 3

File details

Details for the file agent_utilities-0.2.21.tar.gz.

File metadata

  • Download URL: agent_utilities-0.2.21.tar.gz
  • Upload date:
  • Size: 45.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.3

File hashes

Hashes for agent_utilities-0.2.21.tar.gz
Algorithm Hash digest
SHA256 a7e9e0c1e2b1b6503311f71c7629dca1adcf43967014c0f5f5d467702247a860
MD5 46c9f22d41451502c1e9749c383db597
BLAKE2b-256 93c7e46af5b38951b828dbc47cb1ab12257a28b3b1fefbda960e27b2db7bb485

See more details on using hashes here.

File details

Details for the file agent_utilities-0.2.21-py3-none-any.whl.

File metadata

File hashes

Hashes for agent_utilities-0.2.21-py3-none-any.whl
Algorithm Hash digest
SHA256 5ff479278dbdd839b84413dcdea90c7df50f54cb68b6d0d11bb4a3a04fba9555
MD5 397dd439603208e62a3f5ce2b251ba1a
BLAKE2b-256 2739a6b71ad21422c2842c90b10bf000be875977632ee01d24d720df2ba79632

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