FRENES

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.

Score
66/100
Adoption (stars) 21/40
Activity (commits, releases) 30/30
Framework (licence, control, models) 15/30
Open sourceActively maintainedLow risk

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.

Run commands in a terminalRun commands in a terminal : 5 %5 %Read and edit filesRead and edit files : 7 %7 %Drive a web browserDrive a web browser : 7 %7 %Call online services and APIsCall online services and APIs : 9 %9 %Read and send messagesRead and send messages : 5 %5 %
Share of the 43 agents in the family that have each access, according to their documentation. In orange, Raven's access.

Raven pricing

The code is free, under the Apache-2.0 licence.

Getting started with Raven

  1. Install it: the project ships as a Python package (install with pip or uv). The exact command is in the repository README.
  2. Create an API key with the model provider and put it in an environment variable, never in a shared or versioned file.
  3. 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.
  4. 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.

Nov 2, : 0 · Nov 2, 2025Nov 2,Nov 9, : 0 · Nov 9, 2025Nov 16, : 0 · Nov 16, 2025Nov 23, : 0 · Nov 23, 2025Nov 30, : 0 · Nov 30, 2025Dec 7, : 0 · Dec 7, 2025Dec 14, : 0 · Dec 14, 2025Dec 21, : 0 · Dec 21, 2025Dec 28, : 0 · Dec 28, 2025Dec 28,Jan 4, : 0 · Jan 4, 2026Jan 11, : 0 · Jan 11, 2026Jan 18, : 0 · Jan 18, 2026Jan 25, : 0 · Jan 25, 2026Feb 1, : 0 · Feb 1, 2026Feb 8, : 0 · Feb 8, 2026Feb 15, : 0 · Feb 15, 2026Feb 22, : 0 · Feb 22, 2026Feb 22,Mar 1, : 0 · Mar 1, 2026Mar 8, : 0 · Mar 8, 2026Mar 15, : 0 · Mar 15, 2026Mar 22, : 0 · Mar 22, 2026Mar 29, : 0 · Mar 29, 2026Apr 5, : 0 · Apr 5, 2026Apr 12, : 0 · Apr 12, 2026Apr 19, : 0 · Apr 19, 2026Apr 19,Apr 26, : 0 · Apr 26, 2026May 3, : 0 · May 3, 2026May 10, : 0 · May 10, 2026May 17, : 0 · May 17, 2026May 24, : 0 · May 24, 2026May 31, : 0 · May 31, 2026Jun 7, : 0 · Jun 7, 2026Jun 14, : 0 · Jun 14, 2026Jun 14,Jun 21, : 0 · Jun 21, 2026Jun 28, : 0 · Jun 28, 2026Jul 5, : 70 · Jul 5, 2026Jul 12, : 12 · Jul 12, 2026Jul 19, : 12 · Jul 19, 2026Jul 26, : 24 · Jul 26, 2026Aug 2, : 21 · Aug 2, 2026Aug 9, : 10 · Aug 9, 2026Aug 9,Aug 16, : 37 · Aug 16, 2026Aug 23, : 166 · Aug 23, 2026Aug 30, : 334 · Aug 30, 2026Sep 6, : 277 · Sep 6, 2026Sep 13, : 321 · Sep 13, 2026Sep 20, : 115 · Sep 20, 2026Sep 27, : 269 · Sep 27, 2026Oct 4, : 33 · Oct 4, 2026Oct 4,Oct 11, : 22 · Oct 11, 2026Oct 18, : 71 · Oct 18, 2026Oct 25, : 75 · Oct 25, 2026Oct 25,
Commits per week on the main repository, last 52 weeks (GitHub API, checked October 25, 2026).

21 releases in total; 21 in the last twelve months. Latest release: v0.2.5, on October 20, 2026.

v0.1.2 · Jul 1, 2026v0.1.2Jul 1, 2026v0.1.1 · Jul 1, 2026v0.1.3 · Jul 10, 2026v0.1.4 · Jul 13, 2026v0.1.5 · Jul 16, 2026v0.1.6 · Jul 19, 2026v0.1.7 · Jul 21, 2026v0.1.8 · Jul 22, 2026v0.1.9 · Jul 23, 2026v0.1.10 · Jul 31, 2026v0.1.11 · Aug 10, 2026v0.1.12 · Aug 18, 2026v0.1.13 · Aug 25, 2026v0.2.0 · Sep 23, 2026v0.2.1 · Sep 24, 2026v0.2.2 · Sep 25, 2026v0.2.3 · Sep 27, 2026tech-report-v1 · Sep 27, 2026v0.2.4 · Oct 3, 2026v0.2.5 · Oct 20, 2026v0.2.5Oct 20, 2026
The latest 20 releases published on GitHub (hover a point for details).

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.

OrcaOrca : 104.7K104.7KCrewAICrewAI : 60.1K60.1KAgnoAgno : 42.9K42.9KPaperclipPaperclip : 106.8K106.8KAgentScopeAgentScope : 33.8K33.8KOpenAI Agents SDKOpenAI Agents SDK : 30.3K30.3KEigentEigent : 15.7K15.7KMicrosoft Agent FrameworkMicrosoft Agent Framework : 14.3K14.3KRavenRaven : 5.8K5.8K
Log scale; Raven in orange. Checked October 25, 2026.

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.

Quick comparison: multi-agent
AgentModelScoreStars or entry priceSelf-hostableHuman approval
Ravenopen source665.8K ★––
Orcaopen source91104.7K ★yes–
CrewAIopen source8860.1K ★yes–
Agnoopen source8742.9K ★yes–
Paperclipopen source86106.8K ★yes–
AgentScopeopen source8533.8K ★yes–
OpenAI Agents SDKopen source8530.3K ★yes–
Eigentopen source8115.7K ★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)

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