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"]
}
}
}Resumen de MCP Servers
# 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).
Lo que la gente pregunta sobre hicortex
¿Qué es gamaze-labs/hicortex?
+
gamaze-labs/hicortex es mcp servers para el ecosistema de Claude AI. 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. Tiene 2 estrellas en GitHub y su última actualización registrada es del 2026-09-12.
¿Cómo se instala hicortex?
+
Puedes instalar hicortex clonando el repositorio (https://github.com/gamaze-labs/hicortex) o siguiendo las instrucciones del README en GitHub. ClaudeWave también te ofrece bloques de instalación rápida en esta misma página.
¿Es seguro usar gamaze-labs/hicortex?
+
Nuestro agente de seguridad ha analizado gamaze-labs/hicortex y le ha asignado un Trust Score de 80/100 (tier: Trusted). Revisa el desglose completo de comprobaciones superadas y flags en esta página.
¿Quién mantiene gamaze-labs/hicortex?
+
gamaze-labs/hicortex es mantenido por gamaze-labs. La última actividad registrada en GitHub es del 2026-09-12, con 0 issues abiertos.
¿Hay alternativas a hicortex?
+
Sí. En ClaudeWave puedes explorar mcp servers similares en /categories/mcp, ordenados por popularidad o actividad reciente.
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