Introduction

In today’s digital era, automating repetitive tasks and streamlining complex processes are essential for individuals and organizations alike. While single-agent AI solutions can tackle straightforward jobs, they often struggle with multifaceted workflows that require diverse expertise and parallel execution. 「Eigent」 addresses this challenge by offering a 「multi-agent workflow」 desktop application that lets you build, manage, and deploy custom AI teams capable of handling end-to-end automation.

This guide will walk you through everything you need to know about Eigent—from the core concepts and standout features to installation steps, real-world use cases, and tips for customizing your own AI workforce. Written in clear, conversational English suitable for readers with a technical foundation at the junior-college level, this document aims to provide practical insights without oversimplification.

Table of Contents

  1. What Is a Multi-Agent Workflow?

  2. Why Choose Eigent?

  3. Getting Started in Minutes

    • Cloud Edition
    • Community Self-Hosted
    • Enterprise Edition

  4. Key Features Explained

    • Dynamic Task Decomposition
    • Parallel Execution Engine
    • Model Compatibility
    • Tool Integrations (MCP)
    • Human-in-the-Loop
    • Open-Source and Extensible

  5. Step-by-Step Installation

  6. Example Workflows

    1. Trip Planning and Slack Reporting
    2. Q2 Financial Report from CSV
    3. Automated Market Research
    4. SEO Audit for Product Launch
    5. Duplicate File Detection

  7. Frequently Asked Questions

  8. Customizing Your AI Team

  9. Roadmap and Community

  10. Technical Stack

  11. Contributing and License

1. What Is a Multi-Agent Workflow?

Imagine assigning different parts of a complex project to specialized team members: one person researches data, another writes the report, a third creates charts, and a fourth reviews the final draft. A 「multi-agent workflow」 applies the same idea to AI. Instead of a single AI model doing everything, you deploy multiple AI “workers,” each designed for specific sub-tasks, and orchestrate them in parallel.

Key advantages:

  • 「Clear division of labor:」 Each agent focuses on a single task, reducing overlap and confusion.
  • 「Faster results:」 Agents operate in parallel, so overall completion time is significantly lower.
  • 「Scalability:」 Easily add or remove agents as project scope changes.
  • 「Flexibility:」 Plug in new tools or models to enhance capabilities.

Eigent brings this power to your desktop, letting you build complex automations without writing orchestration code by hand. Whether it’s drafting a market analysis, generating financial reports, or auditing a website, Eigent’s multi-agent engine handles the heavy lifting.

2. Why Choose Eigent?

When evaluating automation platforms, consider how easily you can:

  1. 「Deploy locally or in the cloud」 without lengthy setup.
  2. 「Integrate your preferred AI models」, whether open-source or proprietary.
  3. 「Combine existing tools」 (web scrapers, code runners, document editors) into one seamless workflow.
  4. 「Pause for human review」 at critical decision points.
  5. 「Extend functionality」 via open-source contributions.

Eigent excels in all these areas with:

  • 「Zero-configuration launch:」 Start in minutes, even without DevOps support.
  • 「Multi-agent orchestration:」 Built-in scheduler for concurrent task execution.
  • 「MCP (Model Context Protocol) integration:」 200+ ready-to-use connectors.
  • 「Human-in-the-loop checkpoints:」 Automatic pauses when human input is needed.
  • 「100% open source:」 Full transparency, community-driven enhancements.

3. Getting Started in Minutes

Cloud Edition (Recommended)

For the quickest onboarding, use Eigent’s cloud platform. No local setup is required—you can:

  • Spin up a new workspace in under five minutes.
  • Access hosted AI models and managed services.
  • Receive automatic updates and scaling.
  • Benefit from priority support with a paid subscription.

Start with the cloud edition →

Community Self-Hosted Edition

Prefer full control over your data? Clone and run the community version on your own machine:

「Prerequisites:」 Node.js and npm installed

# Clone and install
git clone https://github.com/eigent-ai/Eigent-desktop.git
cd Eigent-desktop
npm install
npm run dev

You now have a locally hosted instance where all your workflows run on your hardware.

Enterprise Edition

Large organizations with strict security and custom needs can opt for the Enterprise Edition, which includes:

  • Commercial licensing and Service Level Agreements (SLA).
  • Enterprise-grade features like Single Sign-On (SSO) and role-based access control.
  • Scalable cluster deployment and professional services.

Contact 「info@eigent.ai」 for pricing and custom integrations.

4. Key Features Explained

4.1 Dynamic Task Decomposition

Eigent’s engine automatically breaks down a high-level assignment into sub-tasks that specialized agents can handle. For example, a “market research report” task might split into:

  1. Data gathering
  2. Data analysis
  3. Chart creation
  4. Report drafting

Each part is assigned to an agent optimized for that function, and progress is tracked in real time.

Workflow decomposition diagram

4.2 Parallel Execution Engine

By default, agents run in parallel whenever possible. If a sub-task depends on another, Eigent queues it appropriately. This concurrency model reduces wait times dramatically compared to sequential scripts.

4.3 Model Compatibility

Whether you prefer open-source LLMs running locally or cloud-based APIs, Eigent supports:

  • 「Local models:」 Complete privacy and offline operation.
  • 「Custom enterprise models:」 Plug in your in-house AI.
  • 「Cloud models:」 Connect to OpenAI, Azure, or other APIs.

4.4 Tool Integrations (MCP)

MCP (Model Context Protocol) connectors let agents access external capabilities. Built-in tools include:

Tool Category Examples
Web Browsing HTTP scraper, search API
Code Execution Shell scripts, Python runner
Document Tools Notion, Google Docs
Notifications Slack, Email, Webhooks
Databases SQL, NoSQL clients

You can also add your own MCP connectors for internal systems or unique APIs.

MCP integration gif

4.5 Human-in-the-Loop

For tasks requiring judgment calls—such as final report approval or ambiguous data cleaning—Eigent pauses the workflow and waits for your feedback. Configure these checkpoints easily in the workflow editor.

Human-in-the-loop gif

4.6 Open Source and Extensible

Eigent is MIT-licensed and hosted on GitHub, encouraging community contributions. Browse the repo, audit the code, or submit pull requests:

git clone https://github.com/eigent-ai/eigent.git

5. Step-by-Step Installation

For those opting to self-host, follow these steps:

  1. 「Clone the repo」: git clone https://github.com/eigent-ai/Eigent-desktop.git
  2. 「Install dependencies」: npm install
  3. 「Run the app」: npm run dev
  4. 「Open in browser」: Navigate to http://localhost:3000
  5. 「Add your models」: Configure local or cloud models in Settings > Models
  6. 「Create your first workflow」: Select “New Workflow” and follow the guided setup.

6. Example Workflows

6.1 Trip Planning and Slack Reporting

「Scenario:」 Two tennis fans in San Francisco want a 3-day itinerary for the 2026 Palm Springs tournament, including flights, hotels, activities, and a final Slack summary.

「Workflow steps:」

  1. 「Flight search agent」: Fetches round-trip options.
  2. 「Hotel booking agent」: Finds vegan-friendly hotels with spa access.
  3. 「Activities agent」: Plans hiking routes and local tours.
  4. 「Budget agent」: Calculates total cost against a $5,000 budget.
  5. 「Report agent」: Compiles an HTML report and text summary.
  6. 「Slack agent」: Posts the summary to #tennis-trip-sf.

Result: A detailed itinerary with booking links and a Slack update.

(Continued in full guide…)