Agentic Index
Agno vs Pydantic AI (2026)
Both vendors last verified
Agno and Pydantic AI are both Python agent frameworks and a close head to head. That verdict is the Agentic Index coverage score, graded from each vendor's own published materials.
Pydantic AI is fully open source with strong typing and tooling, model flexibility and observability through Logfire, from a team whose validation library is already in most Python stacks. Agno, formerly Phidata, is a high performance agent runtime with multi agent support and memory, Apache 2.0 for self hosting, with Pro from $150 a month for the managed tier. Pydantic AI suits type safety and a free license, and Agno suits runtime performance and built in knowledge retrieval.
On the Agentic Index agent infrastructure ranking, Agno clears the bar and Pydantic AI does not. Agno documents all five production contract capabilities in full; Pydantic AI does not document security and identity governance in full, nor observability and auditability. 33 of the 186 vendors in the lane clear it. See the agent infrastructure ranking
This comparison is published by Agentic Index, an independent agentic AI vendor research platform. Agno and Pydantic AI are each graded against the same 14 capability Agentic Index taxonomy, from the vendor's own public materials under the Agentic Index verification standard, alongside 1,084 researched vendors. No vendor pays for placement and no vendor has reviewed this page. How this evidence is graded
Choose Agno if
- Runtime performance and built in knowledge retrieval are what your agents actually need.
- Multi agent support in the framework rather than bolted on is the architecture you want.
- Apache 2.0 self hosting with a managed option gives you both paths.
Choose Pydantic AI if
- Free and open source with no managed tier upsell is the position you prefer.
- Type safety through Pydantic is already how your team writes Python.
- Logfire observability is a coherent story from the same team.
| Feature | A Agno |
P Pydantic AI |
|---|---|---|
| Action & orchestration | ||
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Integrations & Tool Calling Ability to connect agents to real systems through native integrations, OAuth-authenticated actions, custom tools, APIs, webhooks, or MCP-compatible tools. |
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AgnoIntegrations & Tool Calling The Agno SDK ships more than 100 toolkits, alongside MCP tools and custom tools that agents call to act in outside systems. SourceAgno, agno.com homepage and docs.agno.com/tools/mcpread 2026-09-21 |
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Pydantic AIIntegrations & Tool Calling Model Context Protocol support is first class, alongside Agent2Agent and UI event stream standards, built in capabilities for web search, web fetch, image generation, tool search, code execution and file access, and a composable capability system that bundles tools, hooks, instructions and model settings into reusable units, built in house or installed as third party capability packages. Sourcepydantic.dev/docs/ai/tools-toolsets/toolsetsread 2026-09-21 |
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Workflow Orchestration Ability to sequence, branch, retry, route, and combine deterministic workflow nodes with autonomous agent steps. |
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AgnoWorkflow Orchestration The SDK gives three patterns, agents, teams that delegate across member agents, and workflows that run ordered steps with loops, parallel branches and approval gates, so deterministic steps and agent steps combine in one run. SourceAgno, agno.com homepage and docs.agno.com/workflowsread 2026-09-21 |
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Pydantic AIWorkflow Orchestration Agents compose into multi-agent systems through subagents and a dynamic workflow capability in which an orchestrator coordinates a catalog of sub-agents with fan-out, chaining and voting, and durable execution through Temporal, DBOS, Prefect, Restate and other backends lets long-running runs survive crashes and restarts. SourcePydantic AI, pydantic.dev/docs/ai durable execution and harness pagesread 2026-09-21 |
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Triggers & Channel Coverage How agents wake up and where they work: schedules, webhooks, message events, CRM events, inbox events, chat, email, voice, and collaboration tools. |
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AgnoTriggers & Channel Coverage The Scheduler creates cron jobs that execute AgentOS endpoints and tracks their run history, so an agent, team or workflow starts without a person initiating it, and AgentOS interfaces serve agents in Slack, WhatsApp and other chat apps. SourceAgno, docs.agno.com/scheduler/overview and agno.com homepageread 2026-09-21 |
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Pydantic AITriggers & Channel Coverage Event driven workflows and UI event stream standards are supported, with token by token streaming for interactive applications, but as a library Pydantic AI leaves triggering and channel coverage to the host application, and it ships no scheduler, webhook framework or channel matrix. Sourcepydantic.dev/docs/ai/harness/gh-awread 2026-09-21 |
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| Knowledge & context | ||
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Knowledge Grounding & RAG Ability to ground agent behavior in company data through document ingestion, retrieval, external knowledge APIs, semantic search, or RAG layers. |
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AgnoKnowledge Grounding & RAG Knowledge loads files, URLs or raw text into a knowledge base backed by a vector store, and the agent searches it to ground its response; a published pages mode keeps Markdown and vectors in sync with a documentation site and shows the page revision behind each result. SourceAgno, docs.agno.com/knowledge/overviewread 2026-09-21 |
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Pydantic AIKnowledge Grounding & RAG A typed Embedder API generates embeddings across providers for semantic search and retrieval, and agents can pull context on demand through tools, but Pydantic AI keeps no index or vector store over the customer's documents, so the developer assembles retrieval for each run. Web search and web fetch reach the public web, not the customer's knowledge. SourcePydantic AI, pydantic.dev/docs/ai/guides/embeddings and llms.txtread 2026-09-21 |
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Memory & State Persistence Ability to persist context across a run, conversation, workflow, user, team, or longer-term memory layer. |
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AgnoMemory & State Persistence Memory stores facts per user_id in the configured database and loads them into later runs across conversations, with a memory mode controlling when records are created, updated or deleted, alongside sessions scoped to a single conversation. SourceAgno, docs.agno.com/memory/overviewread 2026-09-21 |
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Pydantic AIMemory & State Persistence The Harness Memory capability gives each agent a persistent notebook of Markdown files it writes, reads, searches and deletes across runs, in a namespace resolved by application code so the model cannot reach another user's memory, with stores ranging from process lifetime in memory to persistent file and SQLite stores. Durable execution separately preserves run state across restarts. SourcePydantic AI, pydantic.dev/docs/ai/harness/memoryread 2026-09-21 |
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| Control & trust | ||
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Human Oversight & Guardrails Approval steps, consent checkpoints, escalation rules, structured guardrails, policy constraints, and pause/resume controls. |
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AgnoHuman Oversight & Guardrails Human-in-the-loop covers agents, teams and workflows: user confirmation requires explicit approval before a tool executes, user input and dynamic user input pause for information, and external tool execution hands a call outside the agent's control, with approvals managed from the AgentOS control plane. SourceAgno, docs.agno.com/hitl/overview and agno.com homepageread 2026-09-21 |
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Pydantic AIHuman Oversight & Guardrails Deferred tools let a developer require approval before specific tool calls run, with the condition able to depend on the call's arguments, the conversation history or user preferences, and the Harness guardrails capability validates the prompt, tool calls and output with allow and block rules, so low and high risk actions can run under different autonomy modes. SourcePydantic AI, pydantic.dev/docs/ai/tools-toolsets/deferred-tools and harness/guardrailsread 2026-09-21 |
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Security, Identity & Governance RBAC, SSO, auditability, encryption, least-privilege tool access, compliance posture, and data handling policy. |
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AgnoSecurity, Identity & Governance AgentOS offers JWT authentication across REST, MCP, A2A and WebSocket requests, roles as named bundles of scopes, service accounts and per-user data isolation, with basic RBAC on Pro, a SAML SSO add-on, and per-resource RBAC and audit logs on Enterprise. The site shows a SOC 2 badge with no report, auditor or date, and the attestation details sit in a trust center at trust.agno.com. SourceAgno, docs.agno.com/agent-os/security/overview and agno.com/pricingread 2026-09-21 |
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Pydantic AISecurity, Identity & Governance The framework is a library with no hosted service or user layer, and its controls are least-privilege tool access, through a FileSystem capability scoped to one directory tree with symlink-safe containment and a Shell capability with allow and deny controls and environment scrubbing. Pydantic AI names no supported identity providers or provisioning standards, and no attestation covers the framework. SourcePydantic AI, pydantic.dev/docs/ai/harness/filesystem and harness/shellread 2026-09-21 |
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Observability & Auditability Traces, logs, execution histories, metrics, audit events, and debugging detail for production agent behavior. |
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AgnoObservability & Auditability Tracing records execution spans in the customer's own database, covering run input and output, model calls, tool calls with timing, results and errors, team delegation and workflow steps, viewable in the control plane or queryable through the AgentOS API; retention is unlimited on every plan and Enterprise adds audit logs. SourceAgno, docs.agno.com/agent-os/tracing/overview and agno.com/pricingread 2026-09-21 |
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Pydantic AIObservability & Auditability Built-in OpenTelemetry instrumentation records model calls and tool invocations as spans that flow to any OpenTelemetry backend the customer runs, so each step can be inspected. The trace store and views are the customer's chosen backend or the separately sold Pydantic Logfire, and the framework has no audit log separate from runtime traces and no retention by plan. SourcePydantic AI, pydantic.dev/docs/ai/capabilities/instrumentation and integrations/logfireread 2026-09-21 |
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Deployment & Data Residency Deployment modes and options, including SaaS, dedicated cloud, VPC, on-prem, hybrid, local runtime, and self-hosting. |
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AgnoDeployment & Data Residency The open source runtime runs in the customer's own cloud, with deployment templates for Docker, AWS, Azure, GCP, Helm, Modal, Railway and Render. Agno says data never leaves the customer's system, and Enterprise adds a self hosted control plane. SourceAgno, agno.com/pricing and docs.agno.com/deploy/templatesread 2026-09-21 |
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Pydantic AIDeployment & Data Residency The agent runtime is an open source library that runs wherever the customer runs Python, with durable execution on backends the customer operates such as Temporal, DBOS and Prefect, so agent data stays on the customer's infrastructure. SourcePydantic AI, pydantic.dev/docs/ai overview and durable execution pagesread 2026-09-21 |
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| Solution readiness | ||
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Prebuilt Agents, Templates & Packs Ready-made workflows, packaged employees, templates, blueprints, industry solutions, and role-specific agents that reduce time-to-value. |
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AgnoPrebuilt Agents, Templates & Packs Agno publishes complete agent applications as templates, each with its own repository: Scout, a company intelligence agent across web, Slack, Drive, wiki and CRM sources; Dash, a self-learning data agent; and Coda, a code companion for pull request review and issue triage in Slack. Each works on its own. SourceAgno, docs.agno.com/deploy/templatesread 2026-09-21 |
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Pydantic AIPrebuilt Agents, Templates & Packs Pydantic AI Harness ships two complete agents alongside its capabilities, Coder, an autonomous coding harness with six tools and context management, and Researcher, a complete web-research harness that returns source-backed answers. The 30-plus capabilities themselves are parts the developer assembles. SourcePydantic AI, pydantic.dev/docs/ai/harnessread 2026-09-21 |
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| Platform extensibility | ||
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Model Flexibility & Routing Ability to work across multiple foundation models, route tasks to different models, or let buyers bring their own providers and keys. |
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AgnoModel Flexibility & Routing The developer sets each agent's model by choosing a provider model class and model id, from a catalog spanning OpenAI, Anthropic, Google, open-weight hosts and gateways, and agents on different models can run side by side. SourceAgno, docs.agno.com/models/overview and agno.com homepageread 2026-09-21 |
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Pydantic AIModel Flexibility & Routing The developer chooses the model for each agent from a provider catalog that Pydantic AI describes as covering every model, with a path for custom models, and the Pydantic AI Gateway offers single-key access across providers or bring-your-own-key. SourcePydantic AI, pydantic.dev/docs/ai overview and overview/gatewayread 2026-09-21 |
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APIs, SDKs & MCP Extensibility Composability layer: stable APIs, SDKs, MCP tool consumption/serving, custom tools, and integration into internal systems. |
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AgnoAPIs, SDKs & MCP Extensibility Agents built with the Python SDK are served by AgentOS over a REST API, as an MCP server, over A2A and through chat interfaces, with a published API reference and authentication on each route. SourceAgno, docs.agno.com/agent-os/security/overview and agno.com/pricingread 2026-09-21 |
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Pydantic AIAPIs, SDKs & MCP Extensibility Pydantic AI is an open source Python SDK developed in the open, with a public interface, a capability system for building and publishing custom capabilities, and agents that can be served to other systems over Agent2Agent and to editors over the Agent Client Protocol. SourcePydantic AI, pydantic.dev/docs/ai overview, capabilities and harness/acp pagesread 2026-09-21 |
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Testing, Debugging & Optimization Testing, debugging, scoring, retries, fallbacks, quality gates, and optimization loops for improving agent workflows before and after deployment. |
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AgnoTesting, Debugging & Optimization Evals turn expected behavior into repeatable checks that run in development and CI: an accuracy eval runs the agent and has an evaluator model compare its response with the expected output, alongside agent as judge, reliability and performance evals. SourceAgno, docs.agno.com/evals/overviewread 2026-09-21 |
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Pydantic AITesting, Debugging & Optimization Pydantic Evals lets customers create datasets, run evaluations, systematically test the performance and accuracy of the agentic systems they build, and track model performance over time from the CLI or in Logfire, with the evaluation workflow sharing the same OpenTelemetry trace as production runs. Sourcepydantic.dev/docs/ai/evals/evalsread 2026-09-21 |
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| Specialist automation | ||
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Browser & Computer Use Browser, desktop, or remote/local computer control for workflows that cannot be handled through stable APIs alone. |
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AgnoBrowser & Computer Use Interactive browsing in Agno runs through third party engines such as Browserbase, Stagehand and AgentQL, each bought separately. The product has no browser, desktop or computer control of its own, and its Web Browser toolkit opens URLs in a browser without operating the page. SourceAgno, docs.agno.com/tools/toolkits/others/web-browser and /tools/toolkits/web-scrape/browserbaseread 2026-09-21 |
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Pydantic AIBrowser & Computer Use The Harness Playwright Browser capability gives an agent a real, stateful Chromium browser through async Playwright that it drives itself, navigating, clicking, typing, scrolling and extracting page text, with no separate account required. SourcePydantic AI, pydantic.dev/docs/ai/harness/playwrightread 2026-09-21 |
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Pricing snapshot
Sourced from the Index pricing dataset · open each vendor's profile for full detail.
| Pricing | A Agno |
P Pydantic AI |
|---|---|---|
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Entry price Lowest public entry point |
Pro from $150 a month, with a free tier and a free open source runtime. Enterprise is custom. | Free and open source. |
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Pricing confidence How public the numbers are |
Public, exact | Public, exact |
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Billing Primary billing axis |
Flat. The hosted control plane is a monthly subscription with no usage metering, and Pro add ons are priced per seat, per live connection and for SAML SSO. | Nothing is billed for the framework, which is free and open source. Model usage is billed by the customer's own model provider. |
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Variable cost Workload / overage exposure |
Low variable cost | Low variable cost |
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Free tier / trial Try before you buy |
Free tierTrial
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Free tier
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Buying motion Self-serve vs sales call |
Mixed | Self-serve |
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Pricing verified When this pricing was last checked |
Product updates
Newest first, each linked to its source.
Agno
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· Agent capability
CompanyOS, a new part of AgentOS, gives agents ongoing areas of responsibility called Products, each with Sources such as repositories, documentation, local Markdown files and websites.
Source -
· Deployment / data residency
Agno v3.1.4 adds a sandbox parameter so ClaudeAgent and CodexAgent run their whole harness process inside an isolated computer for each session, with DockerSandbox as a provider the customer operates and AgentCoreSandbox on Amazon Bedrock AgentCore Runtime.
Source -
· Security / enterprise
Role based access control and user management come to AgentOS in Agno 3.1.0, with a role store, scope policies, an audit log, a user directory and an admin interface.
Source
Pydantic AI
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· Workflow orchestration
SubAgents in Pydantic AI v2.62.0 can run a delegation as a task that the model can send to the background, steer, answer and cancel.
Source -
· Deployment / data residency
Pydantic AI v2.56.0 adds SmolSandbox, a workspace that runs Harness capabilities inside a local smolvm microVM.
Source -
· Human approval / guardrails
Pydantic AI v2.53.0 adds ToolCallJudge, which puts a second model in front of selected tool calls and asks it one risk question before the tool runs.
Source
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