Multi-agent · agent platform
Raven: review, pricing, security and alternatives
Raven is an open-source agent platform published by EverMind AI, in the multi-agent family. Raven organizes a persistent ecosystem of multiple agents and their execution environments for collaborative tasks. Its repository has 5,778 stars and its last commit is from October 24, 2026.
| Adoption (stars) | 21/40 | |
|---|---|---|
| Activity (commits, releases) | 30/30 | |
| Framework (licence, control, models) | 15/30 |
What Raven does
Raven 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 #27 of the 43 projects of this family listed in the directory.
Who is Raven 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)
Access and human control
Its documentation does not detail the access granted to the agent: check the settings before connecting it to your accounts.
We could not establish whether it asks for human approval before sensitive actions: test it first on an unimportant account or folder.
Raven pricing
The code is free, under the Apache-2.0 licence.
Getting started with Raven
- 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.
- Give it a first playground with nothing at stake: a test folder, a secondary account or a throwaway project. Only open your real accounts once you have seen how it behaves.
- 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 21, 2026, the EverMind-AI/Raven repository has 5,778 stars, 202 forks and 48 open issues, with 1,930 commits in total. It received changes this month.
Over the last 52 weeks: 1,869 commits, an average of 35.9 per week.
21 releases in total; 21 in the last twelve months. Latest release: v0.2.5, on October 20, 2026.
Raven 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.
Raven 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 |
|---|---|---|---|---|---|
| Raven | open source | 66 | 5.8K ★ | – | – |
| Orca | open source | 91 | 104.7K ★ | yes | – |
| CrewAI | open source | 88 | 60.1K ★ | yes | – |
| Agno | open source | 87 | 42.9K ★ | 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 | – |
How we rated it
Score: 66/100, computed only from public, verifiable data, with no subjective testing or partnership:
- Adoption 21/40: 5,778 stars on a log scale (40 points from about 200,000).
- Activity 30/30: last commit less than a month ago, 21 releases in six months, 1,869 commits in a year.
- Framework 15/30: 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
Raven is a serious option; check the limitations below before granting it access.
Strengths
- Very active development
- Frequent releases (21 in a year)
- Permissive licence (Apache-2.0)
Alternatives
- Orca104.7K ★
- CrewAI60.1K ★
- Agno42.9K ★
- Paperclip106.8K ★
- AgentScope33.8K ★
- OpenAI Agents SDK30.3K ★
Learn more
Frequently asked questions
Is Raven free?
The software is free (Apache-2.0 licence). You still pay for the model calls, unless you use a local model.
Is Raven safe?
Our risk level: low. Give it minimum rights and approve irreversible actions.
Which models does Raven use?
According to its documentation: Claude (Anthropic) and GPT (OpenAI).
Can Raven be installed on your own server?
This is not clearly documented: check with the vendor.
What are the alternatives to Raven?
In the same family: Orca, CrewAI, Agno, and Paperclip.
Raven or Orca: what is the difference?
Both belong to the multi-agent family. Raven has 5.8K 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