Hivemind — Shared Brain for Your Agents

Turn your team's agent traces into reusable skills that propagate across every agent.

Stars
★ 1.6k
Last updated
4d ago
License
Apache-2.0
Primary language
TypeScript

At a glance

How it runs
CLIAgent plugin / skillMCP server
Works with
Platform-specificCodex · Claude Code · Claude API
Cost
Free tier plus a paid hosted plan
Setup effort
Low · running in minutes
You'll need
Node.js >=22Deeplake account/tokenShell / CLINetwork accessLocal filesystem
Typical use
A team wants new engineers to benefit from past solutions discovered by senior engineers' agents.
Not a fit if
  • Teams that need fully self-hosted, no-cloud operation
  • Teams unwilling to let all workspace members read captured sessions
  • Users needing Claude desktop-chat capture, not just Local Agent Mode

What does this agent do, and when should you use it?

Hivemind is a cloud-backed shared memory engine for coding agents like Claude Code, OpenClaw, Codex, Cursor, Hermes, and pi. It automatically captures prompts, tool calls, and responses as structured traces in Deeplake, then mines them for recurring patterns to codify into reusable SKILL.md files. Features include hybrid lexical+semantic retrieval, proactive recall, session summaries, a codebase graph, and automatic rule sharing. Data is stored in your Deeplake workspace by default, with BYOC support for GCS, Azure, or S3. Privacy controls via .hivemind files allow per-directory routing or opt-out. Licensed under Apache-2.0.

Hivemind installs hooks or extensions into supported agents (Claude Code, OpenClaw, Codex, Cursor, Hermes, pi) to capture every session's prompts, tool calls, and responses, writing them to the Deeplake sessions table. A background worker generates AI-written wiki summaries (stored in the memory table) and mines for patterns to create SKILL.md files in the project's .claude/skills/ directory. During inference, hybrid retrieval (BM25 + optional embeddings) and proactive recall inject relevant memories into the agent's context. It also virtualizes ~/.deeplake/memory/ as a file system backed by SQL, builds a codebase graph of files/symbols/imports, and can generate code docs and team rules using the host agent's CLI (e.g., claude -p).

  1. A team wants new engineers to benefit from past solutions discovered by senior engineers' agents.
  2. A Claude Code user asks 'What was Emanuele working on?' and gets answers from shared memory.
  3. OpenClaw users want session capture and skill mining without conflicting with the built-in memory-core plugin.
  4. Codex users need cross-session memory without manually managing hooks.json.
  5. An org wants to enforce rules like 'no DROP TABLE on prod' across all coding agents.
  6. A consultancy needs to isolate client work by routing traces to specific workspaces via .hivemind files.

How do you install or deploy this agent?

Install globally: npm i -g @deeplake/hivemind && hivemind install. This detects installed agents and wires hooks, showing a one-line consent prompt before signing in via browser. For headless installs: HIVEMIND_TOKEN=<token> hivemind install or hivemind install --token <token>. You can install for a specific agent: hivemind claude install, hivemind codex install, hivemind claw install, etc. Restart your agents after install. Requires Node.js >=22 and a Deeplake account (get a token at https://deeplake.ai).

How do you use this agent?

Once installed, agents automatically capture sessions. Check status with hivemind status. Query memory naturally, e.g., 'Search traces for authentication bugs we've solved'. Manage skills: hivemind skillify shows current scope, hivemind skillify scope <me|team> sets mining scope, hivemind skillify pull installs teammates' skills. View summaries in ~/.deeplake/memory/summaries/. Disable capture with HIVEMIND_CAPTURE=false claude. Configure per-directory routing by placing a .hivemind file like { "orgId": "acme-corp", "workspaceId": "client-work" }. Enable semantic search with hivemind embeddings install (adds ~600 MB dependency).

What are this agent's strengths and limitations?

Pros
  • Measured improvements on LoCoMo benchmark: 25% cheaper, 1.7× fewer tokens, 31% fewer turns
  • Multi-agent support (Claude Code, OpenClaw, Codex, Cursor, Hermes, pi) with automated hook installation
  • Automatic skill mining and propagation across agents
  • Hybrid retrieval (BM25 + embeddings) and proactive recall
  • BYOC support for GCS, Azure, S3, and on-prem storage
  • Granular privacy controls via .hivemind routing and opt-out
Limitations
  • Default reliance on Deeplake cloud (API, account) – not fully self-hosted
  • All workspace members can read captured data and skills – requires trust
  • Semantic search requires an additional ~600 MB embedding model, otherwise degrades to lexical only
  • OpenClaw integration may feel slow with large reasoning models; recommended to use Haiku
  • Codex requires manual hook trust on first launch; otherwise inactive
  • Claude Cowork integration is Alpha and only captures Local Agent Mode sessions, not desktop chat

How does this agent compare with similar options?

Hivemind coexists with OpenClaw's built-in memory-core plugin without claiming the memory slot. No direct comparisons to other memory engines like MemGPT or Mem0 are mentioned.

Key facts side by side with the most closely related agents.

Agent Source review Form / cost Stars Updated Language Full support on
Hivemind — Shared Brain for Your Agents This agent 56 · Major gaps CLIFreemium ★ 1.6k 4d ago TypeScript Codex · Claude Code · Claude API
NoPUA — Unlocking AI's Potential Through Love 52 · Major gaps Agent plugin / skillFree + model costs ★ 1.4k 20d ago Python Codex · Claude Code
Self-Learning Skills 56 · Major gaps Agent plugin / skillFree + model costs ★ 968 1mo ago — Codex · Claude Code
Emulo 78 · Good Agent plugin / skillFree + model costs ★ 297 16d ago HTML Codex · Claude Code

How does FollowAgents rate this agent?

FollowAgents source review · FARS-2.1
Major gaps
56/ 100 5-point scale 2.8 / 5
This review covers the source as of Aug 09, 2026. The project has shipped 16 stable release(s) since, which have not been re-reviewed. The score and verdict describe the reviewed version only. Recent releases ↓
Trust 13/29
Reliability 8/14
Adaptability 12/18
Convention 10/18
Effectiveness 9/13
Verifiability 4/8
Why each dimension lost points
Trust13 / 29 · 2.2/5

Evidence: one-line consent prompt during install, data collection notice clearly lists captured data types, and options to disable capture (HIVEMIND_CAPTURE=false, .hivemind collect:false). Credentials file stored with 0600 permissions, directory 0700. However, least privilege is insufficient: installer modifies multiple agent config files, and capture is enabled by default without fine-grained permission control. User confirmation: one-line consent prompt during install, but no explicit confirmation of data collection scope. Data flow transparency: README details captured data types and storage location, but not how data is transmitted to cloud. Sensitive data handling: credentials file permissions correct, but no mention of encryption or anonymization. Dependency security: dependency versions not pinned, potential known vulnerabilities. External effects: installer modifies multiple agent configs, but no rollback mechanism described. Rollback: uninstall command provided, but impact on configs not explained. Source attribution: no clear source attribution information.

Reliability8 / 14 · 2.9/5

Self-consistency: README consistent with code structure, features match implementation. Dependency availability: dependency versions not pinned, availability risk. Failure messages: tests cover error handling, but no user-visible error message examples.

Adaptability12 / 18 · 3.3/5

Audience and scenarios: clearly supports multiple agents, provides install guides for different scenarios. Capability boundaries: clearly states capture scope (e.g., Claude Cowork only Local Agent Mode), but other limitations not mentioned. Trigger precision: capture controlled via env vars and config files, but trigger conditions not specified. Environment fit: supports multiple OS and agents, but no specific environment limitations.

Convention10 / 18 · 2.8/5

Information architecture: README well-structured, but missing API docs. Install notes: multiple install methods, but no troubleshooting. Naming stability: version numbers update frequently, but naming conventions not explained. Examples and FAQ: examples provided, but no FAQ. Known limitations: Claude Cowork limitation clearly stated, but others not. License: Apache-2.0, but no copyright info. Versioning and changelog: no changelog. Maintenance responsibility: maintainers not identified.

Effectiveness9 / 13 · 3.5/5

Output usability: skills and search provided, but output format not specified. Marginal value: shared memory and skill reuse, but benefits not quantified. Cost-benefit: benchmark data provided, but actual costs not explained.

Verifiability4 / 8 · 2.5/5

Claim traceability: benchmark data in README has sources, but no reproduction method. Cross-source corroboration: only README, no other sources. Fact-inference separation: README distinguishes facts and inferences, but not explicitly labeled.

Risks and how to mitigate them
  • Capture is enabled by default, may inadvertently collect sensitive data; users should configure explicitly.
  • Dependency versions are not pinned, posing supply chain risk.
  • Installer modifies multiple agent configs; evaluate permissions carefully.
Evidence confidence: Low Reviewed Aug 09, 2026 Reviewed revision 7d17a412e983 New commits since this review; the score may not cover them
See the full review method →

Recent releases

Latest entries from the project's GitHub Releases. Notes are quoted from upstream as written, not rewritten or tested by FollowAgents.

  1. v0.7.161 v0.7.161 — [hivemind-codex-skills] skillify pull: show the agent skill roots that a global pull links
    Release notes excerpt
    What's Changed * [hivemind-codex-skills] skillify pull: show the agent skill roots that a global pull links by @khustup2 in https://github.com/activeloopai/hivemind/pull/448 Full Changelog: https://github.com/activeloopai/hivemind/compare/v0.7.160...v0.7.161
    View on GitHub ↗
  2. v0.7.160 v0.7.160 — fix: `.hivemind` "collect": false makes Hivemind fully inactive in a tree
    Release notes excerpt
    What's Changed * fix: .hivemind "collect": false makes Hivemind fully inactive in a tree by @activesoull in https://github.com/activeloopai/hivemind/pull/444 New Contributors * @activesoull made their first contribution in https://github.com/activeloopai/hivemind/pull/444 Full Changelog: https://github.com/activeloopai/hivemind/compare/v0.7.159...v0.7.160
    View on GitHub ↗
  3. v0.7.159 v0.7.159 — fix(redact): stop a secret value at a backslash so serialized capture entries stay valid JSON
    Release notes excerpt
    What's Changed * fix(redact): stop a secret value at a backslash so serialized capture entries stay valid JSON by @efenocchi in https://github.com/activeloopai/hivemind/pull/360 Full Changelog: https://github.com/activeloopai/hivemind/compare/v0.7.158...v0.7.159
    View on GitHub ↗

FAQ

Is Hivemind free?
Hivemind is open-source under Apache-2.0, but it requires a Deeplake cloud account and API token. Data is stored in Deeplake workspaces, and pricing depends on usage. Check Deeplake's website for details.
How secure is my data?
Data is encrypted in transit (TLS) and at rest (AES-256). Tenant isolation is enforced at the storage layer. You can also bring your own cloud (GCS, Azure, S3) to keep data within your perimeter.
Can I control which sessions are captured?
Yes, set the environment variable HIVEMIND_CAPTURE=false to disable capture entirely, or place a .hivemind file with collect: false in a directory to opt out. Use .hivemind.local for personal overrides.
Which agents does Hivemind support?
Claude Code, OpenClaw, Codex, Cursor, Hermes Agent, pi, and Claude Cowork (Alpha). Integration methods vary: marketplace plugin, hooks, native extensions, or MCP server.
What happens if retrieval fails?
Retrieval failures are silent and do not block the agent. Proactive recall has a timeout (default 1000ms) and skips on any miss or error.
View on GitHub ↗ Install ↓

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