# Alternatives to Pydantic AI

Pydantic AI is a Python agent framework that brings type-safe, structured outputs and dependency injection to LLM apps.

Pydantic AI ranks #10 of 10 in AI agent frameworks, with an Alt Score of 79. It is licensed under MIT and free from Free. 13 of 13 checklist rows are verified against a public source.

Source: https://altcatalog.com/alternatives/pydantic-ai/
Category: AI agent frameworks

## Overview

- **Who it's for**: Python developers building production-grade GenAI applications and agents who want FastAPI-style ergonomics, strict type safety, and Pydantic-validated structured outputs rather than a loosely-typed agent framework.
- **What you get**: A free, open-source (MIT-licensed) model-agnostic agent framework supporting most major LLM providers, with function/tool calling, streamed structured outputs, human-in-the-loop tool approval, multi-agent delegation patterns, and the companion pydantic-graph library for graph-based stateful workflows; deep tracing integration is available through Pydantic Logfire, a separate paid observability product.
- **How it works**: Developers define an Agent with a model, instructions, and Pydantic-typed dependencies and output schema, then register Python functions as tools the LLM can call during a run; results are validated against the declared output type, with support for streaming, message-history persistence across turns, and composing multiple agents or pydantic-graph state machines for more complex workflows.

## Profile

- **License**: MIT (verified 2026-07-16)
- **Pricing model**: Free (verified 2026-07-16)
- **Starts at**: Free (verified 2026-07-16)
- **Platforms**: ?
- **Status**: ?

## Ranked alternatives

| # | App | Alt Score | Licence | Platforms |
|---|-----|-----------|---------|-----------|
| 1 | [LangGraph](https://altcatalog.com/alternatives/langgraph.md) | 100 | MIT License | Linux, macOS, Windows, Web |
| 2 | [LlamaIndex](https://altcatalog.com/alternatives/llamaindex.md) | 96 | MIT License | ? |
| 3 | [CrewAI](https://altcatalog.com/alternatives/crewai.md) | 93 | MIT | Linux, macOS, Windows, Web |
| 4 | [Haystack](https://altcatalog.com/alternatives/haystack.md) | 93 | Apache-2.0 | ? |
| 5 | [Mastra](https://altcatalog.com/alternatives/mastra.md) | 93 | Apache License 2.0 | ? |
| 6 | [Agno](https://altcatalog.com/alternatives/agno.md) | 86 | Apache-2.0 | ? |
| 7 | [AutoGen](https://altcatalog.com/alternatives/autogen.md) | 86 | MIT | Linux, macOS, Windows |
| 8 | [Semantic Kernel](https://altcatalog.com/alternatives/semantic-kernel.md) | 86 | MIT | Linux, macOS, Windows |
| 9 | [OpenAI Agents SDK](https://altcatalog.com/alternatives/openai-agents-sdk.md) | 83 | MIT | ? |

Alt Score = Verified coverage (90%) + Visibility (10%). See https://altcatalog.com/how-alt-score-works/

## Feature comparison

Legend: Yes / No / Partial / ? (not verified).

| AI agent frameworks checklist | Pydantic AI | LangGraph | LlamaIndex | CrewAI | Haystack | Mastra |
|---|---|---|---|---|---|---|
| Pricing model | Free | OSS + paid hosting | OSS + paid hosting | OSS + paid hosting | OSS + paid hosting | OSS + paid hosting |
| Starts at | Free | $39/seat/month (LangSmith Plus plan, includes LangGraph hosted deployment; usage-based charges apply on top) | $50/month (LlamaParse Starter) | Free | Free | $250/month |
| License | MIT | MIT License | MIT License | MIT | Apache-2.0 | Apache License 2.0 |
| Platforms | ? | Linux, macOS, Windows, Web | ? | Linux, macOS, Windows, Web | ? | ? |
| Open source | Yes | Yes | Yes | Yes | Yes | Yes |
| Language (Python) | Yes | Yes | Yes | Yes | Yes | No |
| Language (JS/TS) | No | Yes | Partial | No | No | Yes |
| Multi-agent orchestration | Yes | Yes | Yes | Yes | Yes | Yes |
| Graph / stateful workflows | Yes | Yes | Yes | Yes | Yes | Yes |
| Human-in-the-loop | Yes | Yes | Yes | Yes | Yes | Yes |
| Streaming support | Yes | Yes | Yes | Yes | Yes | Yes |
| Built-in memory / state persistence | Partial | Yes | Yes | Yes | Yes | Yes |
| Tool / function calling | Yes | Yes | Yes | Yes | Yes | Yes |
| Model-agnostic (multi-provider) | Yes | Yes | Yes | Yes | Yes | Yes |
| Observability / tracing integration | Yes | Yes | Yes | Yes | Yes | Yes |
| Managed / hosted deployment | No | Yes | Yes | Yes | Yes | Yes |
| RAG support | Partial | Yes | Yes | Yes | Yes | Yes |

## Sources

Sources for Pydantic AI. Each alternative is sourced on its own page.

- **License**: MIT — <https://raw.githubusercontent.com/pydantic/pydantic-ai/main/LICENSE> (verified 2026-07-16)
  - Quote: “The MIT License (MIT) Copyright (c) Pydantic Services Inc. 2024 to present”
- **Pricing model**: Free — <https://raw.githubusercontent.com/pydantic/pydantic-ai/main/LICENSE> (verified 2026-07-16)
  - Note: Pydantic AI itself is a free, MIT-licensed open-source library. Pydantic Logfire, the observability platform it integrates with, is a separate paid product not covered by this claim.
  - Quote: “Permission is hereby granted, free of charge, to any person obtaining a copy of this software”
- **Starts at**: Free — <https://raw.githubusercontent.com/pydantic/pydantic-ai/main/LICENSE> (verified 2026-07-16)
  - Note: Same basis as pricing_model: MIT-licensed OSS library with no cost to use.
  - Quote: “Permission is hereby granted, free of charge, to any person obtaining a copy of this software”
- **Open source**: Yes — <https://raw.githubusercontent.com/pydantic/pydantic-ai/main/LICENSE> (verified 2026-07-16)
  - Quote: “The MIT License (MIT) Copyright (c) Pydantic Services Inc. 2024 to present”
- **Language (Python)**: Yes — <https://raw.githubusercontent.com/pydantic/pydantic-ai/main/README.md> (verified 2026-07-16)
  - Quote: “Pydantic AI is a Python agent framework designed to help you quickly, confidently, and painlessly build production grade applications and workflows with Generative AI.”
- **Language (JS/TS)**: No — <https://raw.githubusercontent.com/pydantic/pydantic-ai/main/README.md> (verified 2026-07-16)
  - Note: The agent framework itself is Python-only; Logfire (a separate observability product) offers JS/TS SDKs for tracing, but that is not the agent framework.
  - Quote: “Pydantic AI is a Python agent framework designed to help you quickly, confidently, and painlessly build production grade applications and workflows with Generative AI.”
- **Multi-agent orchestration**: Yes — <https://ai.pydantic.dev/multi-agent-applications/> (verified 2026-07-16)
  - Quote: “Agent delegation — agents using another agent via tools Programmatic agent hand-off — one agent runs, then application code calls another agent Graph based control flow — for the most complex cases, a”
- **Graph / stateful workflows**: Yes — <https://ai.pydantic.dev/graph/> (verified 2026-07-16)
  - Quote: “Alongside Pydantic AI, we’ve developed pydantic-graph — an async graph and state machine library for Python where nodes and e”
- **Human-in-the-loop**: Yes — <https://raw.githubusercontent.com/pydantic/pydantic-ai/main/README.md> (verified 2026-07-16)
  - Quote: “Human-in-the-Loop Tool Approval: Easily lets you flag that certain tool calls require approval before they can proceed, possibly depending on tool call arguments, conversation history, or user prefere”
- **Streaming support**: Yes — <https://raw.githubusercontent.com/pydantic/pydantic-ai/main/README.md> (verified 2026-07-16)
  - Quote: “Streamed Outputs: Provides the ability to stream structured output continuously, with immediate validation, ensuring real time access to generated data.”
- **Built-in memory / state persistence**: Partial — <https://ai.pydantic.dev/message-history/> (verified 2026-07-16)
  - Note: Pydantic AI exposes message-history APIs (all_messages()/all_messages_json()) that applications can use to persist and reload conversation state, and pydantic-graph supports stateful graphs, but there
  - Quote: “Storing and loading messages (to JSON)”
- **Tool / function calling**: Yes — <https://raw.githubusercontent.com/pydantic/pydantic-ai/main/README.md> (verified 2026-07-16)
  - Quote: “The `tool` decorator let you register functions which the LLM may call while responding to a user.”
- **Model-agnostic (multi-provider)**: Yes — <https://raw.githubusercontent.com/pydantic/pydantic-ai/main/README.md> (verified 2026-07-16)
  - Quote: “Model-agnostic: Supports virtually every model and provider: OpenAI, Anthropic, Gemini, DeepSeek, Grok, Cohere, Mistral, and Perplexity; Azure AI Foundry, Amazon Bedrock, Google Cloud, Ollama, LiteLLM”
- **Observability / tracing integration**: Yes — <https://raw.githubusercontent.com/pydantic/pydantic-ai/main/README.md> (verified 2026-07-16)
  - Quote: “Seamless Observability: Tightly integrates with Pydantic Logfire, our general-purpose OpenTelemetry observability platform, for real-time debugging, evals-based performance monitoring, and behavior, t”
- **Managed / hosted deployment**: No — <https://ai.pydantic.dev/durable_execution/overview/> (verified 2026-07-16)
  - Note: Pydantic AI is a library you deploy yourself; durable/long-running execution is achieved via third-party orchestration systems (Temporal, DBOS, Prefect, Restate) rather than a managed hosting service
  - Quote: “Pydantic AI officially supports four durable execution solutions: Temporal DBOS Prefect Restate”
- **RAG support**: Partial — <https://ai.pydantic.dev/examples/data-analytics/rag/> (verified 2026-07-16)
  - Note: RAG is achieved by combining function tools with vector search (e.g. pgvector) and the framework's embeddings support, and there is a documented RAG example, but there is no first-class built-in vecto
  - Quote: “RAG search example. This demo allows you to ask questions about an October 2024 snapshot of the Logfire documentation.”

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Ranked by verified data, never by who paid. https://altcatalog.com/trust/