MemoryLake
For Hermes Agent

MemoryLake for Hermes Agent

Persistent, shared memory for multi-agent workflows — every Hermes agent in your team draws from one brain.

MemoryLake for Hermes Agent

Why Hermes Agent needs MemoryLake

Hermes is built for multi-agent workflows — research agent, writing agent, customer-support agent, all working in coordination.

But out of the box, each agent is its own island. The research agent finds something. The writing agent does not know. You hand-paste between them.

Real teamwork requires a shared brain. That is what MemoryLake gives Hermes Agent.

What you get

One memory, every agent

Whatever any Hermes agent learns is available to every other Hermes agent — and to any non-Hermes tool sharing the project.

Auto-capture, auto-recall

Each agent automatically saves important context and pulls relevant memory when it needs it. No manual handoff.

Conflict detection across agents

When two agents return contradictory information, MemoryLake flags it instead of silently using the latest one.

Persistent across sessions and devices

Restart, switch laptops, hand off to a teammate — memory stays.

Cross-product portability

The same memory works in Claude, ChatGPT, OpenClaw, and any MCP client. Hermes is one of many — not a silo.

Triple-party encryption

Architectural privacy. No single party (including us) holds all the keys.

Install in 60 seconds

  1. 1

    Sign up at MemoryLake (free for personal use)

    Create a free account at app.memorylake.ai.

  2. 2

    Connect Hermes Agent

    In your Hermes Agent dashboard, add the MemoryLake connection. Paste your MemoryLake project token.

  3. 3

    Done

    All Hermes agents in the project now share one memory store.

What people use it for

"Research agent gathers data in the morning; writing agent uses it in the afternoon. No copy-paste, no re-explaining."
"One agent ran into a conflicting fact across two sources. MemoryLake flagged the conflict; the team triaged it before the report went out."
"Brought a new agent into a long-running project. It immediately had the team's accumulated context — onboarding was instant."

How shared memory works in Hermes

Without MemoryLake+ MemoryLake
Research → writing handoffManual copy-pasteAutomatic
Multiple agents on same taskIndependent contextShared, deconflicted
Resuming a task next dayRe-explain everythingPicks up where it left off
Agent disagreementSilent contradictionFlagged for review
New agent joining teamCold startInherits team memory

FAQ

Why is your product called Hermes?

The name reflects the messenger / coordinator role agents play in multi-agent systems. We are aware of overlap with NousResearch's Hermes LLM series — they are a different product (open-source language model weights, not an agent framework). When in doubt, search "Hermes Agent" or look for the MemoryLake-connected version.

Does Hermes Agent require MemoryLake?

No — Hermes runs without MemoryLake too. But for any workflow with more than one agent, MemoryLake is what makes them feel like a team rather than coworkers who never speak.

Can I share memory between Hermes and non-Hermes tools?

Yes — MemoryLake projects are tool-agnostic. The same memory is accessible from Claude, ChatGPT, OpenClaw, and any MCP client.

Does MemoryLake handle conflicts between agents?

Yes. When two agents store conflicting facts, MemoryLake's conflict detection surfaces both with timestamps and sources. You decide which is right; the resolution is versioned.

Is data shared with other MemoryLake users?

No. Project memory is private to your account/team unless you explicitly share it.

Is it really free?

Free for personal use. Team and enterprise tiers price based on number of agents and memory volume.

Docs and resources