Eigent review, pricing and limits

Eigent replaces a single AI assistant with four parallel workers that run on your own machine, so sensitive files never reach a vendor's cloud. It suits developers, legal teams, and technical shops that need multi-step automation without sending data to a third party. Self-hosting needs Docker and an API key; it passed $250,000 in revenue within three months.

Eigent is an open-source multi-agent AI desktop that runs four specialized workers, Developer, Browser, Document, and Multi-Modal, in parallel on the CAMEL-AI framework (35,000+ GitHub stars). The entire stack runs locally, so files stay on the machine unless a cloud API is connected. It plugs into more than 10 LLM providers, from OpenAI and Anthropic to local Ollama models.

Maker: Eigent AI · Autonomy: semi autonomous · Maturity: BETA

Underlying models: GPT-4o, Claude Sonnet, Claude Opus, Gemini 3 Pro, GLM-4.7 (Z.AI), MiniMax M2.5, Local models via Ollama, Local models via vLLM

About Eigent

Eigent is an open-source multi-agent AI desktop built by EIGENT UK LTD, a London-based startup founded in 2023 by the team behind CAMEL-AI, the academic multi-agent framework with over 35,000 GitHub stars and 200+ contributors. Released under the Apache 2.0 license, Eigent deploys a team of 4 specialized AI workers in parallel on your own machine instead of replacing a single assistant with a faster one: a Developer Agent that writes and runs code, a Browser Agent that navigates the web, a Document Agent that processes files, and a Multi-Modal Agent that handles images and audio.

Each worker in Eigent is backed by the CAMEL-AI orchestration framework, which routes subtasks to the appropriate specialist and coordinates results into a coherent output. Eigent is model-agnostic: you can connect GPT-4o, Claude Sonnet or Opus, Gemini Pro, GLM-4.7 from Z.AI, MiniMax M2.5, or a local model running via Ollama or vLLM, all from the same desktop interface. The platform ships with more than 200 built-in Model Context Protocol (MCP) tools covering browser automation, code execution, Google Workspace, Notion, Slack, and mobile phone control via the Mobile MCP, plus you can install additional MCP servers for custom integrations.

Eigent fits developers and technical teams who need to automate long, multi-step workflows without sending sensitive data to a cloud provider. A legal team can have the Document Agent parse contracts while the Browser Agent fetches jurisdiction-specific case law, all without any file leaving the local machine. A sales team can use the Browser Agent for lead capture and the Developer Agent to build a custom report, coordinated in a single prompt. The platform suits startups, regulated industries, and anyone who has hit the limits of a single-threaded AI assistant.

Eigent reached v0.0.90 as of April 2026, adding support for Gemini 3 Pro, MiniMax M2.5, Z.AI GLM-4.7, and mobile phone automation since launch. The project passed $250,000 in revenue within three months of its product launch, and 10% of every subscription funds CAMEL-AI.org research into multi-agent scaling laws.

Pricing

Open-source self-hosted core is free (Apache 2.0, GitHub). Managed cloud plans: Plus $19.90/month (yearly) or $24.99/month (monthly), 2,000 task credits/month, 7-day free trial. Pro $99.99/month (yearly) or $129.99/month (monthly), 10,000 task credits/month. Enterprise: custom pricing with local deployment and SSO.

Key Features

• 4-Agent Parallel Workforce: Eigent deploys Developer, Browser, Document, and Multi-Modal agents simultaneously on a single task, completing multi-step workflows in parallel rather than sequentially.
• 200+ Built-in MCP Tools: Ships with over 200 Model Context Protocol tools spanning terminal commands, browser control, Slack, Notion, and Google Workspace, plus phone automation through the Mobile MCP and support for adding custom MCP servers.
• Model-Agnostic BYOK: Connects to 10+ LLM providers including OpenAI, Anthropic, Google Gemini, Z.AI, MiniMax, and local models via Ollama or vLLM, so you are not locked into a single model vendor.
• Local-First Privacy: The entire agent workforce runs on your own machine or self-hosted server; files, credentials, and workflow data never leave your environment unless you explicitly connect a cloud API.
• Open Source Codebase: The full codebase is publicly available on GitHub under a permissive open-source license, so you can inspect, fork, and modify the orchestration logic and MCP integrations yourself.
• Human-in-the-Loop Checkpoints: When an agent hits uncertainty or a step requiring a judgment call, Eigent pauses and asks the user rather than guessing, reducing costly automated mistakes in long workflows.

Strengths

• Free open-source core means $0 in software costs; you pay only for LLM API calls or local compute, which can be significantly cheaper than managed agents at scale.
• Runs 4 specialized agents in parallel rather than sequentially, cutting wall-clock time on multi-step workflows that involve web research, coding, and document processing in a single task.
• Model-agnostic design lets you swap GPT-4o for a local Llama 3 model in one settings change, giving control over cost, latency, and data residency that closed platforms cannot match.

Weaknesses

• Self-hosted setup requires Docker, PostgreSQL, and Node.js configuration plus an LLM API key or local Ollama install; non-technical users will find this barrier too high compared to a managed agent like Manus.
• No published SWE-bench or GAIA benchmark scores as of June 2026, making direct performance comparisons with specialized coding or research agents difficult to verify.
• Managed cloud Plus plan credits may run out quickly on large or frequent workflows, and overage costs are not clearly listed, creating budget unpredictability.

Visit Eigent Official Site