# Agenta vs LobeHub Agenta records 45,760 monthly visits with +29.5% month-over-month growth and Freemium pricing. LobeHub records 654,548 monthly visits with -25% growth and Freemium pricing. | Metric | [Agenta](https://openaitools.app/tool/agenta) | [LobeHub](https://openaitools.app/tool/lobehub) | | :--- | :--- | :--- | | Website URL | https://www.agenta.ai | https://lobehub.com | | Categories | AI Developer Tools, Prompt Engineering, Large Language Models (LLMs), AI Agent | AI Agent, AI Chatbot, AI Assistant, Large Language Models (LLMs) | | Pricing Model | Freemium | Freemium | | Monthly Visits | 45,760 | 654,548 | | MoM Growth Rate | +29.5% | -25% | | Primary Market | United States | China | | Direct Visits | 17,206 | 193,171 | | Review Score | 4.4 | 4.6 | | Saved Count | 0 | 0 | | Supported Platforms | Website | Website | ## Agenta Agenta positions itself as an open-source workspace where teams build AI agents and AI co-workers rather than one-off prompts. You can start from pre-built agent templates, give an agent access to models and tools, and run it from a chat surface, Slack or Telegram so the work happens where your team already communicates. Agents can browse, read and write files, and run scheduled automations that trigger from your connected systems. What sets Agenta apart is its focus on operational control. Agents connect to more than a thousand integrations and MCP servers, secrets live in a vault the agent can use but not read, and permissions and approval steps decide which actions run automatically and which need a human sign-off. Every run is logged with duration, token usage and cost, so you can trace why an agent produced a certain result and iterate on it with feedback. For engineering teams, Agenta ships as MIT-licensed software you can self-host with Docker Compose or Helm, keeping agents and data on your own infrastructure with no vendor lock-in. A managed cloud option is available for teams that prefer not to run the stack themselves, and both share the same workspace concepts of agents, skills, sessions and automations. **Pricing & Plans:** Freemium. The open-source edition is MIT-licensed and free to self-host; cloud access is offered alongside it, with a demo available for larger teams. Exact seat and usage limits are listed on the pricing page. - **Agent and co-worker builder:** Assemble agents from templates or from scratch, give them models, skills and tools, and run them from a chat UI, Slack or Telegram. - **MCP connections and 1,000+ integrations:** Wire agents into Notion, GitHub, HubSpot, Slack, Linear, Drive and more over MCP, and swap tools or skills without rewriting the agent. - **Evaluations and run observability:** Score agent outputs, collect feedback and inspect every run with duration, token usage and cost logging so improvements are measurable. - **Guardrails, approvals and a secret vault:** Decide which actions run unattended and which require approval, while credentials stay in a vault your agent can use but cannot read. - **Self-hosting with MIT license:** Deploy the full workspace on your own infrastructure with Docker Compose or Helm charts and keep agents and data on-premises. **Strengths:** Open-source and MIT-licensed, so it can be self-hosted without vendor lock-in; Connects to over a thousand tools and MCP servers instead of a fixed integration list; Built-in evaluation and full run logging with token and cost tracking; Approval gates and a secret vault keep agents within human control **Limitations:** The workspace concept is broad, so new users need time to map it to their workflow; Self-hosting requires someone comfortable running containers and Helm charts; Some enterprise features are only fully explained after contacting sales [Profile (Markdown)](https://openaitools.app/tool/agenta.md) ## LobeHub LobeHub positions itself as a home for "super-agents" that behave less like a chatbot you prompt and more like a colleague who joins the team. You invite an agent into a channel such as Slack, Discord or Telegram, and it reads back through messages, docs and repositories to build context. From there it watches for requests that fit its remit, creates its own tasks when nobody tags it, and reports back in the original thread once something ships. The agents are built to work in parallel and across tools. LobeHub can plug in different IM apps, agent runtimes and models side by side, so work like writing code, drafting documentation or running releases can be delegated to the runtime best suited for it. Deliverables come with acceptance checks and evidence — a screenshot or short recording — so a human can accept, reject or send back a result before it is merged into the main workflow. The project also leans heavily on a self-evolving loop. Each practice an agent performs is scored, recurring mistakes are surfaced for a human to re-teach, and learned lessons take effect immediately. LobeHub is available as a hosted service plus a downloadable desktop client, and the core codebase is open source with a large GitHub following. **Pricing & Plans:** LobeHub offers a free tier to get started and paid plans for heavier private or team usage; the pricing page source flags custom or contact-for-pricing options for business needs. - **Agents that join your channels:** Invite an AI teammate into Slack, Discord, Telegram or other IM apps and let it read channel history, docs and code to get up to speed. - **Proactive task picking:** Agents can claim and create tasks they were never tagged in, based on permissions you set, then ping you only when something is ready. - **Parallel multi-model work:** Point an agent at different runtimes and models so several jobs — coding, docs, releases — progress at the same time. - **Evidence-based acceptance:** Every delivery arrives with checks and visual proof, and you accept or send it back before changes are merged. - **Self-evolving learning:** Agents track how often they get things right, flag recurring mistakes and turn your corrections into lessons that apply right away. **Strengths:** Agents work proactively instead of waiting for prompts; Connects multiple chat apps, runtimes and models in one workspace; Open-source core with an active community and large GitHub presence; Deliveries include evidence so humans can review before accepting **Limitations:** The bot-facing pages block automated access, which can frustrate scripted workflows; Setup and permission tuning take real effort before agents are useful; Best value comes from heavy chat-based team workflows, not solo casual use [Profile (Markdown)](https://openaitools.app/tool/lobehub.md) ## Frequently Asked Questions ### How do Agenta and LobeHub compare in monthly traffic? Agenta has 45,760 monthly visits, while LobeHub has 654,548. Traffic estimates describe audience size, not product quality. ### How do their growth rates compare? Agenta has a month-over-month growth rate of +29.5%; LobeHub has -25%. ### How does pricing compare? Agenta: Freemium. Freemium. The open-source edition is MIT-licensed and free to self-host; cloud access is offered alongside it, with a demo available for larger teams. Exact seat and usage limits are listed on the pricing page. LobeHub: Freemium. LobeHub offers a free tier to get started and paid plans for heavier private or team usage; the pricing page source flags custom or contact-for-pricing options for business needs. ## Alternatives | # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) | | :--- | :--- | :--- | :--- | :--- | :--- | :--- | | 1 | [Ollama](https://openaitools.app/tool/ollama) | 9,421,973 | +4.3% | Free, Freemium, Paid | Run and build with open AI models locally or in the cloud | [.md](https://openaitools.app/tool/ollama.md) | | 2 | [Hermes-Agent](https://openaitools.app/tool/hermes-agent-1) | 3,638,741 | -5.4% | Freemium | Open-source personal AI assistant with persistent memory and multi-platform messaging integration for automated task execution. | [.md](https://openaitools.app/tool/hermes-agent-1.md) | | 3 | [Clawdbot (OpenClaw)](https://openaitools.app/tool/clawdbot) | 1,903,068 | -25.4% | Paid, Free | Open-source personal AI assistant running locally and connecting to chat apps to automate everyday tasks. | [.md](https://openaitools.app/tool/clawdbot.md) | | 4 | [Orca](https://openaitools.app/tool/orca) | 1,025,891 | +1% | Free, Open Source, Enterprise on request | Run many coding agents in parallel, each in its own worktree | [.md](https://openaitools.app/tool/orca.md) | | 5 | [Dify](https://openaitools.app/tool/dify-ai) | 819,691 | -15% | Freemium | Build, deploy, and govern production-ready agentic AI workflows | [.md](https://openaitools.app/tool/dify-ai.md) | | 6 | [Open WebUI](https://openaitools.app/tool/open-webui) | 804,534 | -2.8% | Freemium | Self-hosted open-source AI platform and chat interface for running local or cloud large language models. | [.md](https://openaitools.app/tool/open-webui.md) | | 7 | [AnythingLLM](https://openaitools.app/tool/anythingllm) | 512,269 | +12.9% | Freemium | Privacy-first open-source AI assistant for document chat, local RAG, and meeting transcription workflows. | [.md](https://openaitools.app/tool/anythingllm.md) | | 8 | [LibreChat](https://openaitools.app/tool/librechat) | 346,879 | -3.5% | Free | Open-source AI platform uniting multiple LLM providers, custom agents, and tools in a customizable workspace. | [.md](https://openaitools.app/tool/librechat.md) | | 9 | [Arize AI](https://openaitools.app/tool/arize-com) | 249,028 | +3.2% | Paid, Contact for Pricing | Agent observability, evaluation, and continuous improvement for production AI | [.md](https://openaitools.app/tool/arize-com.md) | | 10 | [OpenBot](https://openaitools.app/tool/openbot) | 145,308 | +2,617.1% | Freemium, Free, Contact for Pricing | Desktop application that runs collaborative teams of AI agents locally using existing developer subscriptions. | [.md](https://openaitools.app/tool/openbot.md) | --- Source: https://openaitools.app/compare/agenta-vs-lobehub More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)