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Major changes across 20 documentation pages: Staleness fixes: - Fix FAQ: wrong import path (hermes.agent → run_agent) - Fix FAQ: stale Gemini 2.0 model → Gemini 3 Flash - Fix integrations/index: missing MiniMax TTS provider - Fix integrations/index: web_crawl is not a registered tool - Fix sessions: add all 19 session sources (was only 5) - Fix cron: add all 18 delivery targets (was only telegram/discord) - Fix webhooks: add all delivery targets - Fix overview: add missing MCP, memory providers, credential pools - Fix all line-number references → use function name searches instead - Update file size estimates (run_agent ~9200, gateway ~7200, cli ~8500) Expanded thin pages (< 150 lines → substantial depth): - honcho.md: 43 → 108 lines — added feature comparison, tools, config, CLI - overview.md: 49 → 55 lines — added MCP, memory providers, credential pools - toolsets-reference.md: 57 → 175 lines — added explanations, config examples, custom toolsets, wildcards, platform differences table - optional-skills-catalog.md: 74 → 153 lines — added 25+ missing skills across communication, devops, mlops (18!), productivity, research categories - integrations/index.md: 82 → 115 lines — added messaging, HA, plugins sections - cron-internals.md: 90 → 195 lines — added job JSON example, lifecycle states, tick cycle, delivery targets, script-backed jobs, CLI interface - gateway-internals.md: 111 → 250 lines — added architecture diagram, message flow, two-level guard, platform adapters, token locks, process management - agent-loop.md: 112 → 235 lines — added entry points, API mode resolution, turn lifecycle detail, message alternation rules, tool execution flow, callback table, budget tracking, compression details - architecture.md: 152 → 295 lines — added system overview diagram, data flow diagrams, design principles table, dependency chain Other depth additions: - context-references.md: added platform availability, compression interaction, common patterns sections - slash-commands.md: added quick commands config example, alias resolution - image-generation.md: added platform delivery table - tools-reference.md: added tool counts, MCP tools note - index.md: updated platform count (5 → 14+), tool count (40+ → 47)
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slug, sidebar_position, title, description, hide_table_of_contents
| slug | sidebar_position | title | description | hide_table_of_contents |
|---|---|---|---|---|
| / | 0 | Hermes Agent Documentation | The self-improving AI agent built by Nous Research. A built-in learning loop that creates skills from experience, improves them during use, and remembers across sessions. | true |
Hermes Agent
The self-improving AI agent built by Nous Research. The only agent with a built-in learning loop — it creates skills from experience, improves them during use, nudges itself to persist knowledge, and builds a deepening model of who you are across sessions.
What is Hermes Agent?
It's not a coding copilot tethered to an IDE or a chatbot wrapper around a single API. It's an autonomous agent that gets more capable the longer it runs. It lives wherever you put it — a $5 VPS, a GPU cluster, or serverless infrastructure (Daytona, Modal) that costs nearly nothing when idle. Talk to it from Telegram while it works on a cloud VM you never SSH into yourself. It's not tied to your laptop.
Quick Links
| 🚀 Installation | Install in 60 seconds on Linux, macOS, or WSL2 |
| 📖 Quickstart Tutorial | Your first conversation and key features to try |
| 🗺️ Learning Path | Find the right docs for your experience level |
| ⚙️ Configuration | Config file, providers, models, and options |
| 💬 Messaging Gateway | Set up Telegram, Discord, Slack, or WhatsApp |
| 🔧 Tools & Toolsets | 47 built-in tools and how to configure them |
| 🧠 Memory System | Persistent memory that grows across sessions |
| 📚 Skills System | Procedural memory the agent creates and reuses |
| 🔌 MCP Integration | Connect to MCP servers, filter their tools, and extend Hermes safely |
| 🧭 Use MCP with Hermes | Practical MCP setup patterns, examples, and tutorials |
| 🎙️ Voice Mode | Real-time voice interaction in CLI, Telegram, Discord, and Discord VC |
| 🗣️ Use Voice Mode with Hermes | Hands-on setup and usage patterns for Hermes voice workflows |
| 🎭 Personality & SOUL.md | Define Hermes' default voice with a global SOUL.md |
| 📄 Context Files | Project context files that shape every conversation |
| 🔒 Security | Command approval, authorization, container isolation |
| 💡 Tips & Best Practices | Quick wins to get the most out of Hermes |
| 🏗️ Architecture | How it works under the hood |
| ❓ FAQ & Troubleshooting | Common questions and solutions |
Key Features
- A closed learning loop — Agent-curated memory with periodic nudges, autonomous skill creation, skill self-improvement during use, FTS5 cross-session recall with LLM summarization, and Honcho dialectic user modeling
- Runs anywhere, not just your laptop — 6 terminal backends: local, Docker, SSH, Daytona, Singularity, Modal. Daytona and Modal offer serverless persistence — your environment hibernates when idle, costing nearly nothing
- Lives where you do — CLI, Telegram, Discord, Slack, WhatsApp, Signal, Matrix, Mattermost, Email, SMS, DingTalk, Feishu, WeCom, Home Assistant — 14+ platforms from one gateway
- Built by model trainers — Created by Nous Research, the lab behind Hermes, Nomos, and Psyche. Works with Nous Portal, OpenRouter, OpenAI, or any endpoint
- Scheduled automations — Built-in cron with delivery to any platform
- Delegates & parallelizes — Spawn isolated subagents for parallel workstreams. Programmatic Tool Calling via
execute_codecollapses multi-step pipelines into single inference calls - Open standard skills — Compatible with agentskills.io. Skills are portable, shareable, and community-contributed via the Skills Hub
- Full web control — Search, extract, browse, vision, image generation, TTS
- MCP support — Connect to any MCP server for extended tool capabilities
- Research-ready — Batch processing, trajectory export, RL training with Atropos. Built by Nous Research — the lab behind Hermes, Nomos, and Psyche models