Skill Detail

Operate a local multi-agent workforce with Eigent

Use Eigent when an operator needs a local desktop agent workforce that can coordinate developer, browser, document, multimodal, model-provider, and MCP-backed work in one controlled environment.

Templates & WorkflowsCustom Agents
Templates & Workflows Custom Agents Security Reviewed
⭐ 14.3k GitHub stars
INSTALL WITH ANY AGENT
npx skills add agentskillexchange/skills --skill operate-a-local-multi-agent-workforce-with-eigent Copy
Works best when you want a reusable capability, not another fragile one-off prompt.
At a glance
Tools required
Eigent desktop/frontend, local backend, Docker/PostgreSQL for local mode, model provider credentials or local models, optional MCP servers
Install & setup
For local mode, clone the repository, start `server/` with Docker Compose after copying `.env.example` to `.env`, configure the frontend `.env.development` for the local proxy, run `npm install`, and start the desktop/frontend with `npm run dev`.
Author
eigent-ai
Publisher
Open Source
Last updated
Jun 14, 2026
Quick brief

Eigent is an open-source cowork desktop application for building and running a custom multi-agent workforce. Its published workflow is strongest when the operator wants local deployment, model-provider control, MCP tool integration, and parallel specialized agents for complex work that spans code, browsing, documents, and multimodal inputs.

How it works

What this skill actually does

Invoke this skill when a normal single chat session is too narrow: deploy the local backend, configure model providers and tool settings, import local or remote MCP servers, start the frontend, and assign tasks to the workforce agents with human review. The scope boundary is the local multi-agent operating environment and its setup/run loop. It is not just an Eigent product card, nor a generic agent-framework entry.

Inputs and prerequisites: Eigent desktop/frontend, local backend, Docker/PostgreSQL for local mode, model provider credentials or local models, optional MCP servers.

Setup notes: For local mode, clone the repository, start `server/` with Docker Compose after copying `.env.example` to `.env`, configure the frontend `.env.development` for the local proxy, run `npm install`, and start the desktop/frontend with `npm run dev`.

Source and verification boundary: use https://github.com/eigent-ai/eigent/blob/main/server/README_EN.md as the canonical reference before running the workflow; keep commands, API calls, CLI usage, and generated outputs reviewable against that upstream source.

Framework fit: publish this as a Custom Agents workflow only when the operator can invoke the documented toolchain directly, rather than treating the upstream project as a generic product listing.