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Eigent

Eigent is an open-source cowork desktop application for building, managing, and deploying a customizable multi-agent AI workforce. It enables automated, parallel execution of complex workflows, supports local deployment, enterprise features (SSO, access control), custom model integrations, and deep MCP (Model Context Protocol) tooling integration while preserving data privacy.

Introduction

Eigent — Open Source Cowork Desktop for Multi-Agent Productivity

Eigent is an open-source desktop/web application designed to let individuals and teams build, manage, and deploy a multi-agent AI “workforce” that automates complex, multi-step workflows. Built in public and based on the CAMEL-AI multi-agent framework, Eigent focuses on parallel task execution, extensible tool integrations, privacy-first local deployment, and enterprise-ready access controls.

Core capabilities
  • Multi-Agent Workforce: Eigent orchestrates a collection of specialized agents (Developer Agent, Browser Agent, Document Agent, Multi-Modal Agent, etc.) that can work in parallel to decompose and complete complex tasks.
  • MCP (Model Context Protocol) Integration: Eigent ships with a broad set of built-in MCP tools (web browsing, code execution, Notion/Google/Slack connectors, etc.) and allows installation of custom tools to extend agent capabilities for domain-specific workflows.
  • Local-first Deployment: Recommended local deployment mode runs a full backend and model integrations on-prem, supporting vLLM, Ollama, LM Studio and other local models to keep data private and reduce external dependencies.
  • Cloud / Managed Options: For quick evaluation or team usage, Eigent also offers a cloud-connected quick start and a managed cloud service with premium support and scaling.
  • Human-in-the-Loop: When agents hit uncertainty, Eigent can request human intervention to guide decisions or to approve critical steps.
  • Enterprise Features: SSO, access control, customizable enterprise deployment, negotiated SLAs, and features tailored for corporate adoption.
Typical use cases
  • Automating multi-step business processes (market research, report generation, data extraction and summarization).
  • Developer workflows that require code generation, execution, and validation across agents.
  • Multi-modal content processing (images, audio) with dedicated agents.
  • Team collaboration tasks: prepare presentations, summarize meeting notes, and post outputs to communication channels (Slack, Notion, etc.).
Tech & architecture highlights
  • Backend: FastAPI + Uvicorn; multi-agent orchestration built on CAMEL.
  • Frontend / Desktop: React + TypeScript, packaged with Electron for a desktop experience; Tailwind CSS and Radix UI for component styling.
  • Local model support: Designed to integrate with local model runtimes (vLLM, Ollama, LM Studio, etc.) and custom model providers.
  • Tooling: MCP tooling system to attach external services and internal APIs as tools for agents.
  • License & community: 100% open source under Apache 2.0; active community channels (GitHub issues, Discord, X/Twitter, Reddit) for contributions and support.
Getting started
  • Quick preview: clone the GitHub repo and run the dev mode for a cloud-connected preview.
  • Local deployment: follow the provided server/local deployment guide to run fully standalone with local models and no cloud dependencies.
  • Enterprise: contact the team for SSO, deployment assistance, and enterprise SLAs.
Notable metadata
  • GitHub stars (context snapshot): ~7.8k stars.
  • Repo created on: 2025-07-29.

Eigent is aimed at users and teams who need an extensible, privacy-conscious platform to turn complex human workflows into coordinated AI-driven processes that can run autonomously or with human oversight.

Information

  • Websitegithub.com
  • Authorseigent-ai
  • Published date2025/07/29

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