by Eigent AI
Eigent review, pricing and limits
Open-source multi-agent desktop: 4 parallel AI workers on your machine.
- Best for
- Backend engineers and DevOps engineers at startups who need local multi-step automation without data leaving the team's infrastructure
- Not for
- Non-technical business users who want a managed agent they can start in under 5 minutes without any setup
Should you use Eigent?
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.
Fully local multi-agent execution with 200+ MCP tools that runs entirely on your own machine, giving data sovereignty that no managed cloud agent platform can match.
The CAMEL-AI framework lineage and 35,000+ GitHub star community give Eigent credibility and contributor momentum that is hard for a new entrant to replicate quickly, but the Apache 2.0 license means any competitor can fork and redistribute the same codebase, limiting proprietary defensibility.
Also for
- Legal and compliance analysts at regulated companies who must process documents without uploading them to a third-party cloud
- Technical sales teams automating lead research, qualification workflows, and outreach drafts using parallel agents
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- AI researchers and open-source contributors building on or studying the CAMEL-AI multi-agent framework
- Backend engineers at privacy-first startups automating multi-step internal workflows
- Legal technology analysts at regulated financial or healthcare firms who cannot send documents to third-party cloud APIs
Also not for
- Enterprise IT buyers who need SOC2 Type II or ISO 27001 certification before deploying any new software
Main trade-off
Setup requires Docker, PostgreSQL, and API key configuration, which immediately filters out non-technical users and slows enterprise adoption compared to managed alternatives that are ready in under 5 minutes.
Eigent pricing
- Top plan
- $129.99/mo
- Billing model
- Freemium
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.
Before you commit
- Cloud LLM API costs (OpenAI, Anthropic, Google) are paid separately to those providers and can accumulate quickly for long parallel-agent workflows, especially with GPT-4o or Claude Opus.
- Managed Plus plan's 2,000 monthly task credits may not cover heavy usage, and overage costs or credit top-up pricing are not clearly disclosed on the pricing page.
What Eigent does on its own
- Scope of autonomy
- Semi-autonomous
- Human approval boundary
- Human in the loop
- Maturity
- Beta
Safety controls
- Runs sandboxedSupported
- Audit loggingSupported
- Human in the loopSupported
- Output filteringNot supported
What it can operate
- Web browsing
- Code execution
- File system
- API calls
- Shell commands
- Document reading
Where Eigent runs
- Deployment
- Cloud · Local
- Where it runs
- Desktop · API
- Memory
- Long term
Models it runs on
- 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
Systems it connects to
| System | Type |
|---|---|
| Google Workspace | Native |
| Notion | Native |
| Slack | Native |
| GitHub | Native |
| Ollama | Native |
| OpenAI API | API |
| Anthropic API | API |
Languages it supports
- English
What Eigent does
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.
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.
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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 and limits
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.
Limits
- 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.
Eigent alternatives
| Agent | Where it runs | Price | Maturity | Rating |
|---|---|---|---|---|
| Eigent This page | Cloud · Your machine | Free plan | Beta | -- |
 OpenClawEigent runs four dedicated workers in a visual desktop app; OpenClaw takes a chat-first approach built into Slack and WhatsApp instead. Choose the one that matches how your team already works: a dedicated app or an existing chat channel. | Cloud · Your machine · API | Free | Beta | -- |
 Hermes AgentHermes Agent is a single self-improving, MIT-licensed agent you drive from the command line, while Eigent runs four separate workers in parallel from a desktop app. Command-line users who want one agent that keeps learning may prefer Hermes; teams that want dedicated specialists working at once should stick with Eigent. | Cloud · Your machine · API | Free plan | Available | 3.7 |
 Claude CodeClaude Code is a single coding-focused agent that ships PRs from your terminal with a published benchmark score, whereas Eigent spreads work across four specialists covering browsing, documents, and code together. If coding is the only job, Claude Code's narrower focus is simpler; if the task spans research, files, and code at once, Eigent's parallel workers cover more ground. | -- | -- | -- | -- |
Eigent facts
- Works offline
- Yes
- Minimum skill level
- Intermediate
- Budget fit
- Budget
- Open source
- Yes
- Ships
- Weekly
- Last major update
- Maker founded
- 2023
- Headquarters
- London, United Kingdom
- Total funding
- Backed by Sky Arc Capital (amount undisclosed)
- Team size
- 8
What changed
Questions about Eigent
How much does Eigent cost in 2026?
Eigent's self-hosted core is free forever; you only pay for your own hardware and any cloud API keys you connect. A managed Plus plan is also available for cloud access without the self-hosting setup. The Pro plan costs $99.99/month billed yearly (or $129.99/month billed monthly) and includes 10,000 monthly task credits. Enterprise pricing is custom, and a Teams plan is in development.
What do you get on Eigent's free tier?
Self-hosting the core costs nothing beyond your own hardware and any LLM API calls or local compute you use. Signing up for the managed cloud version adds 500 registration credits plus a 7-day trial capped at 1,000 total credits with a 300-credit daily limit; a paid plan is required after that.
Which tools compete with Eigent in 2026?
OpenClaw is the closest open-source alternative, using a chat-first interface tied into Slack and WhatsApp rather than a dedicated desktop app. Manus is a fully managed cloud option with no local install, trading data control and model choice for zero setup. Claude Cowork offers tight integration with Claude models in a polished paid workspace but has no self-hosted option. Teams building a custom pipeline in code may prefer a developer SDK like Microsoft AutoGen or CrewAI instead of a desktop app.
Is Eigent better than OpenClaw?
Neither is objectively better since they solve the same problem differently. Eigent runs as a dedicated desktop app with agents executing in parallel; OpenClaw drops the same kind of task into chat channels you already use, like Slack and WhatsApp. Choose Eigent for a purpose-built workspace and full local control; choose OpenClaw if your team already works in chat and wants agent access without a new application to learn.
How do you set up Eigent?
The managed cloud version is fastest: create an account at eigent.ai and start a task in the desktop app within minutes, no install required. Self-hosting needs Docker for the backend, Node.js, and either a cloud API key or a local Ollama install, roughly 20 to 30 minutes end to end. Once connected, type a goal into the task prompt and Eigent's orchestrator assigns it across the right workers automatically.
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.
Read the full background
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.
Sources and guides
Official sources
- Eigent official site Vendor
- GitHub repository GitHub
Autonomy, guardrails, integrations and pricing on this page are read from Eigent AI's own documentation. The verdict is Hokai's reading of them, not the vendor's claim.
Hokai guides that mention Eigent
Lists that include Eigent
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