Hermes — Community Web UI (unofficial)

Memory is no longer a differentiator on its own. ChatGPT, Claude, Cursor, and GitHub Copilot all have some form of memory now. With GPT-5.5 and Claude Mythos pushing the frontier in April 2026, Anthropic, OpenAI, and Microsoft are all shipping scheduling and agent features. The category boundaries that existed twelve months ago are blurring fast.

The distinction that matters is not "has memory" vs. "has no memory." It's whether context persists across sessions automatically, whether execution happens on hardware you control, whether you can reach the same agent identity from any device, and whether the system gets meaningfully better at your workflow over time without manual configuration.

Hermes answers yes to all four. It runs as a persistent process on your server. Memory is markdown files in ~/.hermes/. The same agent that answered your Telegram message at 9am is available in your terminal at 2pm, with full context.

Why synthesis matters: The market is converging. Chat assistants added scheduling. Editors shipped cloud agents. CLIs are getting skills. Any single feature is available somewhere else. The value is having all of them in one self-hosted system, running continuously, with a persistent identity that accumulates real knowledge of your stack over time.

Session-scoped tool

You → [Tool] → Answer → Done

(some tools carry memory, but execution is stateless)

Persistent agent

You ↔ [Hermes] ↔ (memory, skills,

schedule, tools,

surfaces)

Memory: ~/.hermes/ (markdown files, editable)
Skills: auto-written from experience
Schedule: cron, runs while you sleep
Surfaces: Telegram · Discord · Slack · browser
Model: your choice, swap anytime

🧠

Memory that compounds

Memory docs →

⏰

Autonomous scheduling

Scheduling docs →

📡

Reach it from anywhere

Messaging docs →

🔧

47 built-in tools

Web search and extraction, browser automation, code execution, vision analysis, image generation, TTS, subagent delegation, and more.

Tools reference →

📚

Self-improving skills

The agent writes its own skills from experience. Compatible with agentskills.io open standard and shareable via Skills Hub.

Skills docs →

🔌

MCP integration

Connect to any MCP server. Hermes can also expose itself as an MCP server for Claude Code, Cursor, or Codex.

MCP docs →

🎤

Voice mode

Real-time voice in CLI (Ctrl+B to record), Telegram voice bubbles, Discord voice channels. Supports faster-whisper locally or Groq/OpenAI Whisper.

Voice docs →

🖥

6 terminal backends

Local, Docker, SSH, Daytona, Singularity, Modal. Run execution anywhere from a $5 VPS to serverless cloud, sandboxed as needed.

Backend docs →

🎭

Personality & SOUL.md

Define the agent's default voice with a global SOUL.md file. 14 built-in personas plus custom personalities via config.

Personality docs →

🤝

Agent orchestration

Spawn Claude Code or Codex as sub-agents for heavy coding tasks. Results fold back into Hermes memory. Hermes also runs as an MCP server for other tools.

Orchestration docs →

🔒

Security model

7-layer defense in depth: user allowlists, dangerous command approval, Docker isolation, MCP credential filtering, prompt injection scanning, cross-session isolation, input sanitization.

Security docs →

Light mode with profile support

Settings & password protection

Workspace file browser

Sessions, projects & tags

What it includes

💻

Solo developers

Don't want to re-explain your stack every session. Want an AI that actually knows your environment, your conventions, and what you fixed last week.

👥

Teams on a shared server

Multiple people sharing capable AI access without separate subscriptions. Each gets their own profile, memory, and history on the same instance.

⚡

Automation-heavy

Want an AI running scheduled tasks, delivering results to your phone, without babysitting it. Morning briefings, PR reviews, monitoring.

🔐

Privacy-conscious

Conversations, memory, and files stay on your hardware. No data leaving your server. Full control over what the agent can access.

🔄

Multi-model users

Switch between OpenAI, Anthropic, Google, DeepSeek, and others based on cost, capability, or rate limits without rebuilding your workflow.

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Hermes vs. OpenClaw

OpenClaw (MIT, 365k+ stars) is the closest comparison: open-source, self-hosted, always-on. OpenClaw has the widest messaging surface (24+ platforms including iMessage, LINE, WeChat, Teams) and native Chrome CDP browser control. Hermes wins on stability (OpenClaw's Telegram integration broke across multiple 2026 releases) and security — three separate 2026 audits found malicious skills in ClawHub (Koi Security linked 335 to "ClawHavoc," Bitdefender flagged ~900 packages, ~20% of the ecosystem). Hermes writes skills automatically from experience; OpenClaw centers on a human-curated marketplace. Hermes runs in Python/ML ecosystem; OpenClaw is Node.js.

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Hermes vs. Claude Code

Claude Code is Anthropic's official agentic tool spanning terminal, IDE, desktop, and browser. It has a 26-event hooks system, a plugin/skills marketplace, CLAUDE.md/MEMORY.md project memory with auto-memory since v2.1.59+, and cloud-managed scheduling on Anthropic infrastructure. Messaging channels (Telegram/Discord/iMessage) remain a research preview; Slack has not shipped. Key differences: scheduling requires cloud or desktop app (not a headless server daemon), memory doesn't accumulate across projects, and it's locked to Claude models. Hermes can spawn Claude Code as a sub-agent for heavy implementation tasks.

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Hermes vs. Cursor

Cursor has changed substantially. Memories (per-project) shipped June 2025. Automations launched March 2026 with time-based, event-based, and Slack triggers on cloud VMs. Cursor v3.0 (April 2026) is explicitly agent-first with a $29.3B valuation. Cursor excels at editor-native agents with strong IDE integration. Hermes is self-hosted and server-resident: the same persistent identity follows you across every surface without cloud intermediation, works with any model family, and for workflows requiring data sovereignty or deep Python/ML tooling on your own hardware, Cursor's cloud architecture is a fundamental mismatch.

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Hermes vs. Claude.ai / ChatGPT

Both are no longer simple chat tools. Claude Cowork added scheduling (Feb 2026) and 50+ connectors. ChatGPT (now running GPT-5.5, released April 23 2026) has Agent Mode, Scheduled Tasks, and 50+ connectors. Both have improved memory. The fundamental difference isn't features — it's where execution lives. Neither is self-hosted. Neither is provider-agnostic. Memory, sessions, and agent execution run on their servers, not yours. For workflows requiring data sovereignty, persistent server-resident execution, or provider flexibility, that's a disqualifying constraint.

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Hermes vs. Perplexity Computer

Perplexity Computer (February 2026) is a cloud agentic workflow engine that routes across 19+ frontier models, runs tasks in isolated sandboxes, and connects to 400+ services via prebuilt OAuth. Zero setup, broad coverage. Key difference from Hermes: cloud-only, no data sovereignty, opaque credit costs, and no persistent environment state between runs.

Works on Linux, macOS, WSL2, and Android (Termux). On Windows, use WSL2 first.

curl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash

source ~/.bashrc      # reload shell
hermes model          # choose your LLM provider
hermes                # start chatting

hermes model          # choose LLM provider and model
hermes tools          # configure enabled tools
hermes gateway setup  # set up messaging platforms
hermes doctor         # diagnose any issues

Full installation guide →

Supported LLM providers

⚡ Run hermes model to browse and authenticate interactively

🖥

VPS — self-hosted

~$4–8/mo

Full control at roughly the same cost. Hetzner CX22 is the recommended pick: 4 GB RAM, 2 vCPU, 40 GB SSD, 20 TB bandwidth. Add Coolify for one-click deploys from GitHub with no manual Docker work.

• Hetzner CX22 (~$4.50/mo) — best price-performance
• Coolify for easy GitHub deploys (free, open-source)
• Vultr, DigitalOcean, Linode all work from $5/mo
• Full root access, no vendor lock-in
• Docker or bare metal, any Linux distro

Install docs →

☁

PaaS platforms

$5–7/mo

Git-push deploys with no server management. Good if you want to skip infrastructure entirely. Railway, Render, and Fly.io all support Node.js and Python with automatic SSL and domains.

• Railway Hobby — $5/mo, connect GitHub, auto-deploy
• Render — free tier available (sleeps on inactivity)
• Fly.io — Docker-native, 30+ global regions
• No SSH or server management required
• Built-in CI/CD on every git push

Install docs →

Minimum requirements — no GPU needed (Hermes calls external APIs)

• RAM: 1 GB min, 2 GB recommended
• CPU: 1 vCPU minimum
• Storage: 10–20 GB SSD
• OS: Ubuntu 22.04 LTS or any modern Linux
• Model: Bring your own key — Claude, OpenAI, Gemini, or local

✏

Not the best in-editor autocomplete. Cursor and Windsurf do that job better. Use one alongside Hermes — that's not what it's optimizing for.

🔧

Not zero-setup. You're running a server. That means initial configuration, and you're responsible for uptime, upgrades, and backups. The tradeoff is data sovereignty and control.

🤖

Doesn't make weaker models magical. Memory and skills help, but the underlying model determines reasoning quality. Hermes with a weak model is a well-organized weak model.

⚠

Needs guardrails for high-stakes automations. Autonomous execution on a schedule with shell access is powerful and requires judgment. Terminal commands can require confirmation — use that for anything consequential.

⚡

Not the lowest-friction one-shot tool. For a quick answer you'll never revisit, a chat interface is faster. Hermes earns its setup cost over time, not in the first session.