hivemind-graph

One engineer's agent figures out a tricky migration on Monday.

Tuesday, every agent on the team can execute the pattern.

On LoCoMo, the public long-context memory benchmark, Hivemind is 25% cheaper, 1.7× fewer tokens, and 31% fewer turns than running without shared memory. (See the numbers below.)

Beyond memory. Hivemind doesn't just remember. It mines your team's traces for repeated patterns and codifies them into reusable skills that propagate back into every agent on the team. The agent your junior engineer used this morning is sharper because of what your senior engineer's agent figured out last week.

• 📥 Captures every session's prompts, tool calls, and responses as structured traces in Deeplake
• 🧠 Codifies patterns into reusable SKILL.md files, available to every agent on your team
• 🔍 Searches traces and skills with hybrid lexical + semantic retrieval (ILIKE lexical fallback when embeddings off)
• 🔗 Propagates capability across sessions, agents, teammates, and machines in real time
• 📁 Intercepts file operations on ~/.deeplake/memory/ through a virtual filesystem backed by SQL
• 📝 Summarizes sessions into AI-generated wiki pages via a background worker at session end
• ☁️ BYOC: keep data in your own GCS, Azure, S3, or on-prem bucket. See Security & storage

Benchmarks

On the LoCoMo long-context memory benchmark (100 QA pairs, Claude Haiku via claude -p, hybrid lexical + semantic retrieval), Hivemind cuts cost, tokens, and turns versus a no-memory baseline:

The agent reaches the answer in fewer turns with less context, because the prior work is already in scope at recall time, not re-derived per session.

Quick start

One command, all your agents.

macOS / Linux

curl -fsSL https://deeplake.ai/hivemind.sh | sh

Windows — in PowerShell:

irm https://deeplake.ai/hivemind.ps1 | iex

Any platform, via npm — for CI and Dockerfiles, or where policy blocks piping a downloaded script to a shell. Skips the checks the installers do, so Node 22+ and a writable npm prefix are on you:

npm i -g @deeplake/hivemind && hivemind install

The installer detects every supported assistant on your machine (table below), wires up the hooks, and shows a one-line consent prompt before opening a browser for sign-in. Restart your assistants after install.

Headless / CI installs: pass an API token instead of using the browser flow:

HIVEMIND_TOKEN=<your-token> hivemind install
# or
hivemind install --token <your-token>

Get a token from your account settings on https://deeplake.ai. With no token in a non-interactive shell, the install completes with hooks but skips sign-in; run hivemind login later to enable shared memory.

Install for a specific assistant only:

hivemind install --only claude
hivemind claude install    # equivalent
hivemind codex install
hivemind claw install
hivemind cursor install
hivemind hermes install
hivemind pi install
hivemind claude_cowork install   # Alpha

Check what's wired up:

hivemind status

Supported assistants:

🅰️ Claude Cowork is Alpha. Auto-recall (the hivemind_search / read / index tools) is solid. ¹Auto-capture covers Local Agent Mode sessions only — those write a transcript we can tail; plain desktop-chat turns leave no readable local trace and aren't captured (why).

Alternative install paths

If you prefer Claude Code's native plugin marketplace:

/plugin marketplace add activeloopai/hivemind
/plugin install hivemind
/reload-plugins
/hivemind:login

Auto-updates on each session start. Manual update: /hivemind:update.

openclaw plugins install clawhub:hivemind

Then type /hivemind_login in chat, click the auth link, and sign in.

Commands

Auto-recall and auto-capture are enabled by default. Data i