Honcho Memory — Cloud Memory Backend

Think of your AI agent like a forgetful friend who remembers your name but not what you talked about last week. Honcho fixes that — it gives your agent a cloud-based memory that persists across every conversation, so it actually remembers who you are and what matters to you.

What Is Honcho?

Honcho is one of eight external memory providers you can plug into Hermes Agent. While the built-in MEMORY.md file is like a sticky note, Honcho is a full-fledged cloud database that stores, organizes, and retrieves user context intelligently. It’s designed for multi-agent systems where context needs to flow across sessions and even between different agents.

Why Choose Honcho?

Honcho excels at cross-session user modeling. It doesn’t just store raw chat logs — it uses dialectic reasoning to draw conclusions about the user over time. For example, if you mention you’re learning Spanish in three separate conversations, Honcho will eventually note that as a persistent fact, not just a one-off comment.

It’s also session-aware. When your agent starts a new conversation, Honcho injects a summary of what was already discussed, so the agent doesn’t ask the same questions twice. This is especially useful for customer support bots, personal assistants, or any system where continuity matters.

Getting Started

First, install the Python package and grab an API key from app.honcho.dev (or self-host for free):

pip install honcho-ai

Then activate Honcho as your memory provider:

hermes memory setup

Select “Honcho” from the interactive picker. You can verify it’s active with:

hermes memory status

Or set it manually in ~/.hermes/config.yaml:

memory:
  provider: honcho

How Honcho Works

Once active, Hermes automatically injects Honcho’s context into the system prompt before each turn. It prefetches relevant memories in the background, syncs conversation turns after each response, and mirrors built-in memory writes to Honcho. You don’t have to change anything about how you use the agent — it just becomes smarter.

Honcho gives your agent five tools: honcho_profile (read/update user card), honcho_search (semantic search), honcho_context (session summary), honcho_reasoning (LLM-synthesized insights), and honcho_conclude (create/delete persistent conclusions).

Tuning Cost vs. Depth

Honcho has three knobs to control how often it calls APIs and LLMs:

• contextCadence — how often the base context refreshes
• dialecticCadence — how often the reasoning engine fires
• dialecticDepth — how many reasoning passes per invocation (1–3)

Lower cadence = cheaper but less fresh. Higher depth = smarter but slower.

Final Thoughts

Honcho is the best choice if you’re building a multi-agent system where user context needs to persist across sessions and agents. It’s not the simplest provider, but it’s the most intelligent.

Practical tip: Start with default settings, then reduce dialecticCadence if costs creep up. You’ll get 80% of the value at half the price.