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hermes-agent

NousResearch/hermes-agent · Updated

The agent that grows with you

NousResearch/hermes-agent is a Python repository in the AI Agents category with 257,929 stars and 56,577 forks on GitHub, released under the MIT license, last updated today.

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How to install hermes-agent in your AI client

Setup for Claude Code, Claude Desktop, Cursor, Codex, Windsurf, Cline and VS Code — copy-paste ready.

How to install hermes-agent in Claude CodeAnthropic's agentic CLI

  1. Clone & open

    bash
    git clone https://github.com/NousResearch/hermes-agent.git
    cd hermes-agent
    claude
  2. Let Claude read it

    Ask “/init” to generate a CLAUDE.md, then have Claude explain, run, or extend the codebase. It reads files on demand.

Documentation

Full README

Hermes Agent ☤

Hermes Agent | Hermes Desktop

The self-improving AI agent built by [Nous Research](https://nousresearch.com). It's the only agent with a built-in learning loop — it creates skills from experience, improves them during use, nudges itself to persist knowledge, searches its own past conversations, and builds a deepening model of who you are across sessions. Run it on a $5 VPS, a GPU cluster, or serverless infrastructure that costs nearly nothing when idle. It's not tied to your laptop — talk to it from Telegram while it works on a cloud VM.

Use any model you want — Nous Portal, OpenRouter, OpenAI, your own endpoint, and many others. Switch with hermes model — no code changes, no lock-in.

<b>A real terminal interface</b>Full TUI with multiline editing, slash-command autocomplete, conversation history, interrupt-and-redirect, and streaming tool output. <b>Lives where you do</b>Telegram, Discord, Slack, WhatsApp, Signal, and CLI — all from a single gateway process. Voice memo transcription, cross-platform conversation continuity. <b>A closed learning loop</b>Agent-curated memory with periodic nudges. Autonomous skill creation after complex tasks. Skills self-improve during use. FTS5 session search with LLM summarization for cross-session recall. Honcho dialectic user modeling. Compatible with the agentskills.io open standard. <b>Scheduled automations</b>Built-in cron scheduler with delivery to any platform. Daily reports, nightly backups, weekly audits — all in natural language, running unattended. <b>Delegates and parallelizes</b>Spawn isolated subagents for parallel workstreams. In Desktop, choose their provider, model, and limits under Settings → Model → Subagents, then Apply the complete route. Write Python scripts that call tools via RPC, collapsing multi-step pipelines into zero-context-cost turns. <b>Runs anywhere, not just your laptop</b>Six built-in terminal backends — local, Docker, SSH, Modal, Daytona, and Vercel Sandbox — plus plugin backends such as Singularity/Apptainer. Daytona and Modal offer serverless persistence — your agent's environment hibernates when idle and wakes on demand, costing nearly nothing between sessions. Run it on a $5 VPS or a GPU cluster. <b>Research-ready</b>Batch trajectory generation, trajectory compression for training the next generation of tool-calling models.


Quick Install

Linux, macOS, WSL2

bash
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash

Windows (native, PowerShell)

Heads up: Native Windows runs Hermes without WSL — CLI, gateway, TUI, and tools all work natively. If you'd rather use WSL2, the Linux/macOS one-liner above works there too. Found a bug? Please file issues.

Run this in PowerShell:

powershell
iex (irm https://hermes-agent.nousresearch.com/install.ps1)

The source installer delegates Python 3.14, Node.js, npm, ripgrep, FFmpeg, and Python dependencies to PM. If Git is absent, it stages the verified Git for Windows archive in Hermes' tool store. It does not replace your system Git. See installation methods for the separate MSIX/App Installer package and its update ownership.

Excerpt — the full document is on GitHub.

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