PydanticAI
PydanticAI is an open-source, model-agnostic Python agent framework built by the Pydantic team, designed to bring the ergonomic, type-safe design philosophy of FastAPI to production-grade generative AI application development. It provides structured outputs, dependency injection, and first-class support for leading model providers including OpenAI, Anthropic, Google Gemini, xAI, AWS Bedrock, Cohere, Mistral, Groq, and many more. The framework integrates seamlessly with Pydantic Logfire for OpenTelemetry-based observability, and includes pydantic-graph for complex agentic workflows, pydantic-evals for systematic agent evaluation, and clai for a CLI chat interface. PydanticAI is maintained by Pydantic, a London-based developer tooling company backed by Sequoia Capital, and forms a core part of their end-to-end AI engineering stack.
Solid contracts, transparent operations, and an easy start — typically complete on four or five facets with one clear soft spot.
API Evangelist profiles PydanticAI the way a machine reads it — 35 machine-readable artifacts across 17 APIs, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.
Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — PydanticAI scores 60.3/100 (strong), with a separate agent-readiness read of 48/100 (agent ready). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.
Kin Score
This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.
Kin Score
How this is scored →scored 2026-07-27 · rubric v0.5
How we profile PydanticAI
Each block below is one kind of artifact we hold for PydanticAI. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.
APIs 17
Each API is captured as its own OpenAPI definition — every operation, parameter, and response. This is the single most useful machine-readable description of what an API does, and it's what lets us score, lint, mock, and generate against it without asking the provider for anything.
Individual APIs this provider publishes, each with its own machine-readable definition.
PydanticAI Alerts API
The Alerts API from PydanticAI — 2 operation(s) for alerts.
PydanticAI API Keys API
The API Keys API from PydanticAI — 2 operation(s) for api keys.
PydanticAI Audit Logs API
The Audit Logs API from PydanticAI — 2 operation(s) for audit logs.
PydanticAI Billing API
The Billing API from PydanticAI — 1 operation(s) for billing.
PydanticAI Channels API
The Channels API from PydanticAI — 2 operation(s) for channels.
PydanticAI Dashboards API
The Dashboards API from PydanticAI — 2 operation(s) for dashboards.
PydanticAI discovery API
The discovery API from PydanticAI — 1 operation(s) for discovery.
PydanticAI Group Mappings API
The Group Mappings API from PydanticAI — 2 operation(s) for group mappings.
PydanticAI Instance API
The Instance API from PydanticAI — 3 operation(s) for instance.
PydanticAI Invitations API
The Invitations API from PydanticAI — 1 operation(s) for invitations.
PydanticAI Members API
The Members API from PydanticAI — 2 operation(s) for members.
PydanticAI OAuth API
The OAuth API from PydanticAI — 6 operation(s) for oauth.
PydanticAI Organizations API
The Organizations API from PydanticAI — 3 operation(s) for organizations.
PydanticAI Projects API
The Projects API from PydanticAI — 16 operation(s) for projects.
PydanticAI SCIM API
The SCIM API from PydanticAI — 8 operation(s) for scim.
PydanticAI Usage API
The Usage API from PydanticAI — 6 operation(s) for usage.
PydanticAI Variables API
The Variables API from PydanticAI — 2 operation(s) for variables.
Scroll within the panel for all 17 ·
Pricing Plans 1
Pricing is part of the interface. Machine-readable plans tell you what a tier costs and includes before you commit — one of the six things the Kin Score reads for commercial clarity.
Published pricing tiers and plan structures.
Rate Limits 1
Rate limits are the difference between a demo that works and a production integration that doesn't fall over. Publishing them is an operational-transparency signal — and a hard requirement for any agent that plans its own throughput.
Documented rate limits and quota policies.
Pydantic Ai Rate Limits
RATE LIMITSFinOps 1
Cost, billing, and metering signals let a buyer model the financial operations of an API before it's live. We profile them for the same reason we profile pricing: the money is part of the contract.
Cost, billing, and metering signals for API financial operations.
Pydantic Ai Finops
FINOPSSemantic Vocabularies 1
JSON-LD contexts give the data shared meaning across APIs. We profile them because semantics are what let a machine reconcile 'customer' here with 'customer' somewhere else.
JSON-LD contexts and semantic vocabularies used across these APIs.
Pydantic Ai Context
JSON-LDSpectral Rules 1
Governance rulesets we run against this provider's specs — the automated checks behind parts of the score. Profiling them makes the quality bar explicit and re-runnable, not a matter of opinion.
PydanticAI API Rules
SPECTRALJSON Schema 7
Standalone JSON Schema definitions describe the data models behind the API. We profile them so the shapes are validatable on their own — useful long after a single request is forgotten.
Standalone JSON Schema definitions for this provider's data models.
AlertRead
JSON SCHEMAAPIKeyRead
JSON SCHEMAAuditLogInfoRead
JSON SCHEMADashboardDefinitionRead
JSON SCHEMAOrganizationMemberReadV1
JSON SCHEMAOrganizationReadV1
JSON SCHEMAProjectRead
JSON SCHEMAScroll within the panel for all 7 ·
Security Posture 4
Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Scopes 1
OAuth scopes are the vocabulary of least-privilege access. Profiling them shows exactly what an integration — or an agent acting on a user's behalf — is allowed to do.
OAuth scopes governing access to this provider's APIs.
Agentic Access 1
An x-agentic-access contract marks which operations are safe for an agent to run on its own and which need a human in the loop. It is the difference between an API an agent can use and one it can use safely.
Recommended x-agentic-access execution contracts for AI agents.
Resources
Every other property we hold for PydanticAI — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.
Get Started 1
Portal, sign-up, and the first successful call
Documentation 1
Reference material describing how the API behaves
Agent Surfaces 1
MCP servers, agent skills, and machine-readable catalogs
Build 2
SDKs, sample code, and the tooling you integrate with
Access & Security 5
Authentication, authorization, and security posture
Operate 3
Status, limits, changes, and where to get help
Commercial 3
Pricing, plans, and the legal terms of use
Company 3
The organization behind the API
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