{"categories":[{"label":"Application Frameworks","url":"https://skillfed.io/packages/category/software-development-libraries-application-frameworks/6"}],"enrichment":{"capability":"A batteries-included harness for building Pydantic-AI agents with an in-process knowledge graph, orchestration, memory, and tools\u2014deployable as a library, MCP server, or REST gateway.","skillfed_tags":["ai-agents","knowledge-graph","pydantic"],"use_cases":["Build a standalone Python agent with built-in knowledge graph, memory, and tools without setting up external infrastructure.","Integrate a knowledge graph and skill toolkit into Claude Code, Cursor, or other IDE-embedded AI tools via the MCP server.","Deploy a shared knowledge graph backend across multiple agent clients or containers using the REST gateway.","Set up an enterprise multi-host agent fleet with Vault, SSO, DNS, and observability using the enterprise profile.","Ingest, query, and reason over domain knowledge using the in-process graph without a separate database.","Evolve agent behavior by capturing learned skills and refined prompts back into a shared knowledge graph."],"what_it_does":"Agent Utilities is a framework for building AI agents on top of Pydantic-AI that bundles a knowledge graph, tool orchestration, memory, and skill management into a single harness. The zero-infrastructure default runs the knowledge graph in-process using the epistemic-graph Rust engine, with no external databases or services required to start. It exposes three consumption models: a Python library for standalone agents, an MCP server for integration with existing tools like Claude Code and Cursor, and a REST gateway for sharing a knowledge graph backend across multiple clients.\n\nThe package ships with configuration management via Pydantic Settings and environment variables, support for multiple deployment profiles (tiny for homelabs, single-node-prod, and enterprise), and a skill toolkit that auto-loads into agent tools. It handles secrets, multi-model configuration, and optional durable persistence to backends like Postgres or Neo4j. The core authority\u2014the epistemic-graph engine\u2014manages compute, caching, semantics, and persistence, while the gateway layer handles identity, action policies, and metrics.","worth_installing":"Yes. The package is actively maintained, has low install friction, carries a permissive MIT license, and solves a real problem\u2014bootstrapping Pydantic-AI agents with orchestration and knowledge graphs without external infrastructure. It's suitable for both rapid prototyping (tiny profile) and production deployments (enterprise profile). No known security vulnerabilities. The main gotcha is the Python 3.11+ requirement and the need to configure a model provider API key."},"id":"agent-utilities","links":{"html":"https://skillfed.io/packages/agent-utilities","md":"https://skillfed.io/packages/agent-utilities.md","pypi":"https://pypi.org/project/agent-utilities/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-13","license_spdx":null,"license_treatment":"permissive","name":"agent-utilities","python_support":"supports_current","summary":"Agent Utilities for Pydantic AI Agents"},"popularity":{"monthly_downloads":74931,"position":14766,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.26.4"}