Self-learning memory for AI agents — experience captured automatically, distilled into lessons overnight, shared across your whole fleet. Works with Hermes, OpenClaw, Claude Code, and Pi.
- ✓Actively maintained (<30d)
- ✓Clear description
- ✓Topics declared
- ✓Documented (README)
- !Licence file present but not machine-readable
claude mcp add hicortex -- npx -y @gamaze/hicortex{
"mcpServers": {
"hicortex": {
"command": "npx",
"args": ["-y", "@gamaze/hicortex"]
}
}
}MCP Servers overview
# Hicortex
<img src="docs/dashboard-composition.png" alt="Hicortex dashboard — live memory analytics" width="800">
[](https://www.npmjs.com/package/@gamaze/hicortex)
[](https://www.npmjs.com/package/@gamaze/hicortex)
[](LICENSE)
[](https://nodejs.org)
**Memory that shows up before your agent asks.** One memory across every agent, every project, every machine — they stop assuming and start knowing.
- **One brain, every harness** — Claude Code, Hermes, OpenClaw, Pi, OpenCode, and any MCP-compatible agent share the same memory.
- **Pushed, not pulled** — a compact recall index is injected on *every prompt*, so the decisions, corrections, and context an agent needs are already in front of it. No re-explaining, no copy-paste, nothing to maintain. **Zero LLM calls per turn** — no API cost or rate-limit hit from recall.
- **Consolidates overnight** — each night it reads the day's sessions, distills what matters, and turns it into Learnings, links, and a knowledge graph.
- **Local-first** — raw sessions never leave the machine; only distilled memory is stored.
## Install
```bash
npx @gamaze/hicortex init
```
Auto-detects your environment, configures one LLM (Ollama, the Claude CLI, or an API key), installs a local daemon (launchd on macOS, systemd on Linux), and registers MCP tools with Claude Code.
For multi-machine setups, point thin clients at a shared server — no local DB or LLM on the clients:
```bash
npx @gamaze/hicortex init --server https://your-server.example.com
```
`init` auto-detects the other harnesses and installs their clients: a Pi extension (`~/.pi/agent/extensions/hicortex.ts` — pushed recall, identity + lessons, the nine tools; or copy `pi-extension/hicortex/index.ts` there manually), an OpenCode plugin (`~/.config/opencode/plugins/hicortex.ts` — the same trio; or copy `opencode-plugin/hicortex/index.ts` there manually), the Hermes plugin, and the OpenClaw plugin. [pi-mcp-adapter](https://github.com/nicobailon/pi-mcp-adapter) remains a generic MCP escape hatch for any harness (verified against the SSE endpoint) — Pi no longer needs it. See the [install docs](https://hicortex.gamaze.com/docs/installation).
## How it works
```
CAPTURE (nightly) CONSOLIDATE (nightly) RECALL (every prompt)
sessions → denoise score · reflect · link a compact index of
→ POST /distill decay · dedup · supersede relevant memories is
(one model, all phases) pushed into the prompt
→ full text lazy-loaded
```
Memories strengthen when agents use them, fade when they don't, and link to related ones automatically. Retrieval is hybrid BM25 + vector search — zero-LLM at query time.
## Features
- **Per-prompt recall push** — relevant memory lands in context every turn; the agent fetches full content with `hicortex_get` only when it needs it.
- **Memory analytics** at `/dashboard` — growth, recall adoption, and a nightly digest of what was learned.
- **Knowledge graph** at `/viz` — memories clustered by domain, connected by relationship edges.
- **Domains & tags** — multi-tag classification with a configurable vocabulary; your categories drift with your data.
- **Learnings from reflection** — nightly reflection extracts general, reusable Learnings, not just Experience logs.
- **Dedup & supersession** — near-duplicates merged; stale decisions and corrections superseded, not re-surfaced.
- **Standing context layer** — hand-edited "who you are / how to work" Markdown, injected every session, never decayed.
## MCP
Nine MCP tools — `hicortex_search`, `hicortex_get`, `hicortex_recent`, `hicortex_ingest`, `hicortex_lessons`, `hicortex_index`, `hicortex_graph`, `hicortex_update`, `hicortex_delete` — plus a `/learn` skill to save explicit learnings. [Full reference →](https://hicortex.gamaze.com/docs/)
## Stack
TypeScript · Node.js 20+ · SQLite + sqlite-vec + FTS5 (semantic + full-text in one DB) · ONNX embeddings (bge-small-en, CPU) · MCP over HTTP/SSE · one configurable LLM (Ollama, Claude CLI, or any OpenAI-compatible endpoint).
## Development
```bash
git clone https://github.com/gamaze-labs/hicortex.git
cd hicortex
```
[AGENTS.md](AGENTS.md) at the repository root defines the machine-checkable verification contract. "Done" means the full command chain exits with code 0. The contract mirrors what CI runs. Contributors — human or agent — run it before claiming work complete.
Contributions welcome — see [CONTRIBUTING.md](CONTRIBUTING.md).
## Links
- **Website:** [hicortex.gamaze.com](https://hicortex.gamaze.com)
- **Docs:** [hicortex.gamaze.com/docs](https://hicortex.gamaze.com/docs/)
- **Changelog:** [CHANGELOG.md](CHANGELOG.md)
- **npm:** [@gamaze/hicortex](https://www.npmjs.com/package/@gamaze/hicortex)
- **Issues:** [gamaze-labs/hicortex/issues](https://github.com/gamaze-labs/hicortex/issues)
- **Security:** [SECURITY.md](SECURITY.md)
## License
Personal and noncommercial use is free under the [PolyForm Noncommercial License 1.0.0](LICENSE). Commercial use requires a per-seat license — see [hicortex.gamaze.com](https://hicortex.gamaze.com).
What people ask about hicortex
What is gamaze-labs/hicortex?
+
gamaze-labs/hicortex is mcp servers for the Claude AI ecosystem. Self-learning memory for AI agents — experience captured automatically, distilled into lessons overnight, shared across your whole fleet. Works with Hermes, OpenClaw, Claude Code, and Pi. It has 2 GitHub stars and its last recorded update is dated 2026-09-12.
How do I install hicortex?
+
You can install hicortex by cloning the repository (https://github.com/gamaze-labs/hicortex) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.
Is gamaze-labs/hicortex safe to use?
+
Our security agent has analyzed gamaze-labs/hicortex and assigned a Trust Score of 80/100 (tier: Trusted). See the full breakdown of passed checks and flags on this page.
Who maintains gamaze-labs/hicortex?
+
gamaze-labs/hicortex is maintained by gamaze-labs. The last recorded GitHub activity is dated 2026-09-12, with 0 open issues.
Are there alternatives to hicortex?
+
Yes. On ClaudeWave you can browse similar mcp servers at /categories/mcp, sorted by popularity or recent activity.
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