Multi-agent · agent framework
Agno: review, pricing, security and alternatives
Agno is an open-source agent framework published by Agno, in the multi-agent family. Agno provides a Python framework for building agents, coordinating agent teams, and managing their tools and memory. Its repository has 42,878 stars and its last commit is from October 23, 2026.
| Adoption (stars) | 32/40 | |
|---|---|---|
| Activity (commits, releases) | 30/30 | |
| Framework (licence, control, models) | 25/30 |
What Agno does
Agno belongs to the multi-agent family: systems that split a task between several specialised agents passing work to one another. On our grid it ranks #3 of the 43 projects of this family listed in the directory.
A framework is not used as is: it is a library developers build into their own code to describe the agent's tools, decision loop and memory. It requires programming skills, but leaves control over every detail.
You use it from: developer SDK and API. Usable models: any OpenAI-compatible model. It can run on your own machine or server.
Who is Agno for?
It interests technical teams that want to split a complex task between several specialised agents that check each other. Typical tasks people give it:
- pair a writer agent with a reviewer agent
- split a project into subtasks given to roles
- simulate a team (analysis, plan, execution)
It is a good candidate if your data must stay on your machines.
Access and human control
A framework has no access of its own: the tools you plug in define what the agent can do. Start with read-only tools.
We could not establish whether it asks for human approval before sensitive actions: test it first on an unimportant account or folder.
Agno pricing
The code is free, under the Apache-2.0 licence.
Getting started with Agno
- Install it: the project ships as a Python package (install with
piporuv). The exact command is in the repository README. - Create an API key with the model provider and put it in an environment variable, never in a shared or versioned file.
- Start with the minimal example from the docs, then add one tool at a time and check what the agent does with it.
- Give it a short, checkable task, review the result and its action log, then raise the difficulty step by step.
Security: risk level
More agents mean higher bills and chained errors: set a budget and a maximum number of steps.
Three habits: least privilege (minimal rights, dedicated keys), human approval for irreversible actions, a sandbox for code execution. The AI agent security check reviews your setup in a few minutes.
Project activity and releases
Created on May 4, 2022, the agno-agi/agno repository has 42,878 stars, 6,179 forks and 940 open issues, with 6,278 commits in total. It received changes this month.
Over the last 52 weeks: 1,796 commits, an average of 34.5 per week.
258 releases in total; 25 in the last twelve months. Latest release: v3.1.10, on October 23, 2026.
Agno vs other multi-agent
GitHub stars of the best-rated open-source projects in the multi-agent family. Stars measure attention, not quality: a heavily promoted project collects them fast, a specialised tool will have few.
Agno and other multi-agent at a glance
The 7 best-ranked agents in the same family, 7 of them open source. The score out of 100 only applies to open-source projects; for proprietary services we show the published entry price. A dash marks information the documentation does not state.
| Agent | Model | Score | Stars or entry price | Self-hostable | Human approval |
|---|---|---|---|---|---|
| Agno | open source | 87 | 42.9K ★ | yes | – |
| Orca | open source | 91 | 104.7K ★ | yes | – |
| CrewAI | open source | 88 | 60.1K ★ | yes | – |
| Paperclip | open source | 86 | 106.8K ★ | yes | – |
| AgentScope | open source | 85 | 33.8K ★ | yes | – |
| OpenAI Agents SDK | open source | 85 | 30.3K ★ | yes | – |
| Eigent | open source | 81 | 15.7K ★ | yes | – |
| Microsoft Agent Framework | open source | 81 | 14.3K ★ | yes | – |
How we rated it
Score: 87/100, computed only from public, verifiable data, with no subjective testing or partnership:
- Adoption 32/40: 42,878 stars on a log scale (40 points from about 200,000).
- Activity 30/30: last commit less than a month ago, 25 releases in six months, 1,796 commits in a year.
- Framework 25/30: licence, default human approval, self-hosting, model choice and documentation site.
The score does not say whether the agent will succeed at your tasks: it measures how solid the project is. The full grid is on the method page.
Verdict
Agno is one of the most solid projects in its family: followed, active and well framed.
Strengths
- Widely followed: 42.9K stars
- Very active development
- Frequent releases (25 in a year)
- Can run on your side: data under control
- Free choice of model
Limitations
- Requires programming skills
Avoid if…
- You want a ready-made agent, without code
Alternatives
- Orca104.7K ★
- CrewAI60.1K ★
- Paperclip106.8K ★
- AgentScope33.8K ★
- OpenAI Agents SDK30.3K ★
- Eigent15.7K ★
Learn more
Frequently asked questions
Is Agno free?
The software is free (Apache-2.0 licence). You still pay for the model calls, unless you use a local model.
Is Agno safe?
Our risk level: low. Give it minimum rights and approve irreversible actions.
Which models does Agno use?
According to its documentation: any OpenAI-compatible model.
Can Agno be installed on your own server?
Yes, from the agno-agi/agno repository. Data then stays with you, but security and updates are your job.
What are the alternatives to Agno?
In the same family: Orca, CrewAI, Paperclip, and AgentScope.
Agno or Orca: what is the difference?
Both belong to the multi-agent family. Agno has 42.9K stars against 104.7K for Orca. The right choice mostly depends on the access you are willing to give it.
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Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score