Hermes Agent + Honcho

Hermes Agent is an open-source AI agent from Nous Research with tool-calling, terminal access, a skills system, and multi-platform deployment (Telegram, Discord, Slack, WhatsApp). Honcho gives Hermes persistent cross-session memory and user modeling. For setup, configuration, and CLI commands, see the Hermes Agent Honcho docs.

What Honcho provides

Honcho acts as a long-term memory and user-model layer alongside Hermes’ built-in memory files (MEMORY.md and USER.md). It gives Hermes three capabilities:

Prompt-time context injection — durable context about a user loaded into the prompt before generating a response.
Cross-session continuity — recall of stable preferences, project history, and working context across conversations.
Durable writeback — stable facts learned during a conversation stored back for future turns.

These sit alongside Hermes’ local session history. Session history remembers the current conversation. Honcho remembers what should still matter later.

Dual-peer architecture

Both the user and the AI agent have peer representations in Honcho:

User peer: observed from user messages. Learns preferences, goals, communication style.
AI peer: observed from assistant messages. Builds the agent’s knowledge representation.

Both representations are injected into the system prompt, giving Hermes awareness of both who it’s talking to and what it knows.

Available tools

Hermes exposes four Honcho tools to the agent:

Tool	What it does
`honcho_profile`	Fast peer card retrieval (no LLM). Returns curated key facts about the user.
`honcho_search`	Semantic search over memory. Returns raw excerpts ranked by relevance.
`honcho_context`	Dialectic Q&A powered by Honcho’s LLM. Synthesizes answers from conversation history.
`honcho_conclude`	Writes durable facts to Honcho when the user states preferences, corrections, or important context.

Running Honcho locally with Hermes

Follow the Self-Hosting Guide to get Honcho running locally. Once it’s up, point Hermes at your instance:

hermes memory setup  # select "honcho", enter http://localhost:8000 as the base URL

Or manually create/edit the config file (checked in order: $HERMES_HOME/honcho.json > ~/.hermes/honcho.json > ~/.honcho/config.json):

{
  "baseUrl": "http://localhost:8000",
  "hosts": {
    "hermes": {
      "enabled": true,
      "aiPeer": "hermes",
      "peerName": "your-name",
      "workspace": "hermes"
    }
  }
}

For the full list of config fields (recallMode, writeFrequency, sessionStrategy, dialecticReasoningLevel, etc.), see the Hermes memory provider docs.

Community quick-start: elkimek/honcho-self-hosted provides a one-command installer with pre-configured model tiers and Hermes Agent integration.

Verifying the integration

1. Check status

hermes memory status

This should show Honcho as the active memory provider with your base URL.

2. Store a fact and recall it across sessions

In one conversation, tell Hermes something specific:

My favorite programming language is Rust and I always use dark mode.

Start a new session (different thread, new CLI invocation, or a different platform). Ask:

What do you know about my preferences?

If Hermes mentions Rust and dark mode without being told again, cross-session memory is working. The deriver processed your messages, extracted observations, and the dialectic recalled them.

3. Test tool calling directly

Ask Hermes to use a specific Honcho tool:

Use your honcho_search tool to find anything you know about me.

If Hermes calls the tool and returns results, the full tool pipeline (API connection, vector search, embedding) is functional.

Configuration options

Field	Default	Description
`recallMode`	`hybrid`	`hybrid` (auto-inject + tools), `context` (inject only), `tools` (tools only)
`writeFrequency`	`async`	`async`, `turn`, `session`, or integer N
`sessionStrategy`	`per-directory`	`per-directory`, `per-repo`, `per-session`, `global`
`dialecticReasoningLevel`	`low`	`minimal`, `low`, `medium`, `high`, `max`
`dialecticDynamic`	`true`	Auto-bump reasoning level by query complexity
`messageMaxChars`	`25000`	Max chars per message (chunked if exceeded)

Next steps