Pydantic AI

Free tier

GenAI Agent Framework, the Pydantic way — build production-grade AI apps with confidence

Free·Technical·Powered by Model-agnostic (OpenAI, Anthropic, Gemini, Mistral, Cohere, Groq, Ollama, and more)·API available·Open source

Visit

Key strengths

Model-agnostic support for virtually every major LLM providerFully type-safe with IDE auto-completion and compile-time error catchingSeamless observability via Pydantic Logfire (OpenTelemetry)Composable, extensible agent capabilities (tools, hooks, MCP, A2A)Built-in evaluation framework (Pydantic Evals) for systematic performance testing

Completely free

London, United Kingdom

Founded 2024

Self-hostable

Get alerts when Pydantic AI changes

Free. We'll email you when pricing, the free tier, API access or open-source status changes.

No ratings yet

Typed, structured LLM output: Use output_type=PydanticModel to get validated, schema-enforced responses from any supported LLM provider.
Multi-agent graph workflows: Define stateful pipelines using pydantic_graph with typed nodes, reducers, parallel execution, and durable state persistence.
MCP client/server integration: Connect agents to external tools and data sources via the Model Context Protocol using built-in client and FastMCP support.
Eval-driven development: Write test datasets with pydantic_evals, run LLM-judge or custom evaluators, and track regressions in Pydantic Logfire over time.
Durable, fault-tolerant agents: Wrap agent runs in Temporal, DBOS, or Prefect workflows to handle long-running tasks, retries, and human-in-the-loop approvals.
Streaming structured outputs: Use run_stream to incrementally yield validated partial outputs, enabling real-time UI updates and progressive rendering.