Eigent: review, pricing, security and alternatives

What Eigent does

Eigent 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 #7 of the 43 projects of this family listed in the directory.

You use it from: desktop app. Usable models: Claude (Anthropic), GPT (OpenAI), Gemini (Google), and local models (Ollama, llama.cpp, vLLM…). It can run on your own machine or server.

Who is Eigent 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 and you want the option of a local model, with no API fees.

Access and human control

According to its documentation, Eigent can:

• run commands in a terminal
• read and edit files
• drive a web browser
• call online services and APIs

We could not establish whether it asks for human approval before sensitive actions: test it first on an unimportant account or folder.

Eigent pricing

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

Getting started with Eigent

1. Install it: the project ships as a Node.js package (install with npm, or run directly with npx). The exact command is in the repository README.
2. Pick the model: an API key from a provider, or a local model if your machine has enough graphics memory (the VRAM calculator tells you).
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.

Points found for Eigent:

• Sensitive access: it can run commands in a terminal, with no established default human approval.
• Outside content: it reads web pages or API responses, which may contain booby-trapped instructions (prompt injection).

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 July 29, 2025, the eigent-ai/eigent repository has 15,653 stars, 1,878 forks and 180 open issues, with 2,413 commits in total. It received changes this month.

Over the last 52 weeks: 924 commits, an average of 17.8 per week.

37 releases in total; 24 in the last twelve months. Latest release: v1.0.6, on October 16, 2026.

Eigent 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.

Eigent 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.

How we rated it

Score: 81/100, computed only from public, verifiable data, with no subjective testing or partnership:

• Adoption 26/40: 15,653 stars on a log scale (40 points from about 200,000).
• Activity 30/30: last commit less than a month ago, 8 releases in six months, 924 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.