Is Eigent — Local Cowork Desktop for AI Agents free to use?

Yes. Eigent — Local Cowork Desktop for AI Agents is freely available on TokRepo. Check the Source & Thanks section on the asset page for the specific open-source license.

How do I install Eigent — Local Cowork Desktop for AI Agents?

Visit the asset page on TokRepo and click "Copy for agent" to get the installation instructions. Most assets can be installed with a single command.

ScriptsMay 11, 2026·2 min read

Eigent — Local Cowork Desktop for AI Agents

Name: Eigent — Local Cowork Desktop for AI Agents
Author: AI Open Source

Eigent is an open-source cowork desktop for running multi-agent workflows locally. Use it to delegate research, planning, and execution with replays.

AI Open Source · Community

Agent ready

This asset can be read and installed directly by agents

TokRepo exposes a universal CLI command, install contract, metadata JSON, adapter-aware plan, and raw content links so agents can judge fit, risk, and next actions.

Stage only · 29/100Stage only

Agent surface

Any MCP/CLI agent

Kind

Script

Install

Single

Trust

Trust: Established

Entrypoint

README.md

Universal CLI install command

npx tokrepo install df030664-12c6-4393-afa0-1c7604c6ef75

install contract metadata JSON adapter plan raw content

Intro

Eigent is an open-source cowork desktop for running multi-agent workflows locally. Use it to delegate research, planning, and execution with replays.

Best for: People who want a local, app-like “cowork” experience to run agent workflows and replay executions
Works with: Local desktop workflows; see repo README for official site and docs links
Setup time: 10 minutes

How to Use It Well

Setup time ~10 minutes (download app + run one replay/workflow)
The README contains multiple “Replay” examples (links) you can use as a baseline
GitHub stars + forks (verified): see Source & Thanks

Use it as a “workflow runner with replay”: keep tasks small, require artifacts, and build a habit of replaying runs to spot brittle steps. Over time, turn the most valuable replays into reusable templates.

FAQ

Q: Is it cloud or local? A: The repo describes a local cowork desktop experience; check the official docs linked in the README for architecture details.

Q: Do I need to code to use it? A: You can start from provided replays/examples, then customize workflows as your needs grow.

Q: How do I evaluate quality? A: Prefer runs that leave auditable artifacts: inputs, outputs, logs, and a replay you can share with teammates.

🙏

Source & Thanks

Source: https://github.com/eigent-ai/eigent > License: Apache-2.0 > GitHub stars: 13,971 · forks: 1,649

Discussion

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