Comparisons / Agno vs Anthropic Agent SDK
Agno vs Anthropic Agent SDK: Which Agent Framework to Use?
Agno (formerly Phidata) is a lightweight Python framework for building agents. The Anthropic Agent SDK packages Claude Code's agent loop as a library. Here is how they compare — paradigm, ecosystem, and the use cases each one is actually built for.
By the numbers
Agno
39.2k
5.2k
Python
Apache-2.0
2022-05-04
Agno (formerly Phidata)
Anthropic Agent SDK
3.1k
582
Python
MIT
2023-01-17
Anthropic
Google, Spark Capital
Yes
GitHub stats as of April 2026. Stars indicate community interest, not necessarily quality or fit for your use case.
| Concept | Agno | Anthropic Agent SDK |
|---|---|---|
| Agent | `Agent(model=OpenAIChat(), instructions=[...])` class with `run()` method | Claude agent with built-in tools, MCP servers, and system prompt |
| Tools | Function tools via `@tool` decorator or built-in toolkits (web search, SQL, etc.) | Built-in tools (`bash`, file read/write, web) + MCP server connections |
| Agent Loop | `Agent.run()` handles tool dispatch internally, configurable via `show_tool_calls` | SDK's internal agentic loop with automatic tool dispatch |
| Memory / Knowledge | Knowledge bases (PDF, URL, vector DB) injected via `knowledge` param + built-in memory | — |
| Multi-Agent (Teams) | `Team` class with `agents` list, `mode` (sequential, parallel, coordinate), and shared memory | — |
| Storage | `SqlAgentStorage`, `PostgresAgentStorage` for persisting sessions and state | — |
| Sub-Agents | — | Agents invoke other agents as tools via the SDK |
| Lifecycle Hooks | — | 18 hook events: pre/post tool call, message, error, etc. |
| MCP Integration | — | One-line MCP server config for Playwright, Slack, GitHub, etc. |
Agno vs Anthropic Agent SDK, head to head
Agno Agno (formerly Phidata) is a lightweight Python framework for building agents.
Anthropic Agent SDK The Anthropic Agent SDK packages Claude Code's agent loop as a library.
Both wrap the same underlying agent pattern — an LLM call, a tool dispatch, a loop — in different abstractions. The choice between them is mostly about which mental model and ecosystem fits the team you have, not which one is technically more capable.
Pick Agno if
Pick Agno if agno adds value when you want a batteries-included agent with minimal boilerplate — especially for multi-modal agents or team orchestration. But each of its abstractions maps to a small piece of plain Python. If your agent is straightforward, writing it directly gives you full control with zero framework overhead. Agno is the right fit when the tradeoffs in its intro line up with how your team actually wants to work day-to-day; Anthropic Agent SDK would force you to translate.
Pick Anthropic Agent SDK if
Pick Anthropic Agent SDK if the Anthropic Agent SDK's real value is packaging Claude Code's battle-tested agent loop with built-in tools and MCP integration. If you want a production agent that reads files, runs commands, and connects to services, it saves significant plumbing. For understanding how agents work, the plain version is more instructive. Anthropic Agent SDK is the right fit when the tradeoffs in its intro line up with how your team actually wants to work day-to-day; Agno would force you to translate.
What both add
Both Agno and Anthropic Agent SDK pull in a class hierarchy and a dependency tree to wrap what is, at the core, an HTTP POST in a while loop. If your use case is straightforward — one provider, a handful of tools, a single agent — the framework cost may exceed the framework benefit. The lesson below shows the same pattern in ~60 lines without either dependency.
Or build your own in 60 lines
Both Agno and Anthropic Agent SDK implement the same 8 patterns. An agent is a function. Tools are a dict. The loop is a while loop. The whole thing composes in ~60 lines of Python.
No framework. No dependencies. No opinions. Just the code.
Build it from scratch →