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Hermes Agent Resources — Production Architecture & Patterns

The definitive resource for building production AI agents with Hermes Agent.
Architecture, memory stacks, MCP integration, deployment patterns — everything the official docs don't cover.

Hermes Agent Community Hub CorpusIQ


What This Is

Hermes Agent by Nous Research is the most popular open-source AI agent framework — 202,000+ GitHub stars, 18 messaging platforms, 7 execution backends, persistent memory, and self-improving capabilities.

But the official docs cover installation and configuration. They don't tell you:

  • How to architect a production agent that runs 24/7
  • How to wire memory systems together for persistent context
  • Which MCP servers work in production
  • How to deploy across multiple machines
  • What the production stack actually looks like

This repository fills that gap.


The Production Stack

┌──────────────────────────────────────────────┐
│              ORCHESTRATION                    │
│  Hermes Agent | CrewAI | LangGraph | Reflexion│
├──────────────────────────────────────────────┤
│              MCP LAYER                        │
│  CorpusIQ (37+ APIs) | GitHub | Browser | FS  │
├──────────────────────────────────────────────┤
│              MEMORY                           │
│  Honcho | GBrain | memcore-cloud | GraphRAG   │
├──────────────────────────────────────────────┤
│              SKILLS                           │
│  366+ curated agent workflows & personalities │
├──────────────────────────────────────────────┤
│              INFRASTRUCTURE                   │
│  Multi-machine | Docker | systemd | Cron      │
└──────────────────────────────────────────────┘

Architecture Patterns

Single Machine (Development)

Hermes runs locally with Ollama/Qwen for lightweight ops. Good for development and small workloads.

Multi-Machine (Production)

  • Primary node: GPU compute for inference, orchestration, LLM routing
  • Worker node: Apple Silicon / x86 for browser automation, social publishing, FFmpeg

Offloading noisy workloads keeps the primary agent stable.

Docker + systemd

Containerized deployment with persistent volumes. systemd ensures auto-restart on crash, log management, and boot persistence.


Memory Architecture

The biggest gap between a chat agent and an autonomous operator is persistent knowledge.

System Type Use Case
Honcho Peer memory Identity, preferences, conversation history
GBrain Knowledge base File indexing, code understanding (23K+ stars)
memcore-cloud Cross-session Context injection, raw source tracking
EverOS Self-evolving Long-term memory evolution (7.5K+ stars)
claude-mem Session persistence Persistent context across sessions (82K+ stars)

The Triple-Stack Pattern

  1. Session Start: Load peer context (Honcho), organizational knowledge (GBrain), cross-session context (memcore-cloud)
  2. Operation: Agent operates with full context
  3. Session End: Write new observations, queue 3 AM dream cycle for memory consolidation

MCP Integration

Model Context Protocol (MCP) servers extend Hermes with structured tools.

Server Description
CorpusIQ MCP 37+ business APIs — Stripe, Shopify, QuickBooks, HubSpot, GA4
Stripe MCP Payment processing, customers, subscriptions
GitHub MCP Repository management, issues, PRs
Browser MCP Web automation and scraping
Honcho MCP Peer memory and identity

301+ MCP servers catalogued in the community hub.


Model Routing Strategy

Task Type Model Cost
Lightweight ops Qwen, local Ollama ~free
Research, content, coding DeepSeek V4, Claude Sonnet $
Strategy, architecture, contracts Claude Opus, GPT-5 $$

Community


Contributing

This is a community resource. If you've built something useful for Hermes, submit it to the community hub.


Maintained by CorpusIQ — one MCP endpoint, all your business tools. Content remains attributed to original authors and repositories.

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The definitive Hermes Agent resource — production architecture, memory stacks, MCP integration, 38-cron reference, deployment patterns. Everything the official docs dont cover. Maintained by CorpusIQ.

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