Hicortex — AI Fleet Memory

Name: Hicortex — AI Fleet Memory
Author: gamaze-labs

by gamaze-labsversion 0.25.0i★ –iRuns on your computer

Registry nameio.github.gamaze-labs/hicortex

Install

Overview

Description from the maker (original English)

Shared fleet memory for AI agents: nightly self-correction, recall every prompt (supported agents).

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Search & AI memory
You need to fill in: HICORTEX_AUTH_TOKEN

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: HICORTEX_AUTH_TOKEN, HICORTEX_SERVER_URL

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "hicortex": {
      "command": "npx",
      "args": [
        "-y",
        "@gamaze/hicortex"
      ],
      "env": {
        "HICORTEX_AUTH_TOKEN": "your-value",
        "HICORTEX_SERVER_URL": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add hicortex --env HICORTEX_AUTH_TOKEN=your-value --env HICORTEX_SERVER_URL=your-value -- npx -y @gamaze/hicortex

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "hicortex": {
      "command": "npx",
      "args": [
        "-y",
        "@gamaze/hicortex"
      ],
      "env": {
        "HICORTEX_AUTH_TOKEN": "your-value",
        "HICORTEX_SERVER_URL": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "hicortex": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@gamaze/hicortex"
      ],
      "env": {
        "HICORTEX_AUTH_TOKEN": "your-value",
        "HICORTEX_SERVER_URL": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

HICORTEX_AUTH_TOKEN secret env
Bearer token for a remote Hicortex server (server prints it via `hicortex status`). Optional — a local server needs no token.
HICORTEX_SERVER_URL env
URL of a remote Hicortex server (e.g. https://your-server:8787). Optional — omit for a local server on this machine.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account gamaze-labs, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

More stars than 0% of the other 7246 servers in this category
Published to the registry more recently than 81% of the other 7246 servers in this category
Basic checks equal to or better than 100% of the other 7246 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Hicortex — AI Fleet Memory safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: HICORTEX_AUTH_TOKEN

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.25.0) reached the registry 8 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Hicortex — AI Fleet Memory

Shared memory for AI agents — it corrects itself overnight, and what one agent learns, the whole fleet knows. 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 — in every supported coding agent, 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

npx @gamaze/hicortex init

Claude Desktop: one "yes" during 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:

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 ten 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 remains a generic MCP escape hatch for any harness (verified against the SSE endpoint) — Pi no longer needs it. See the install docs.

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.

The first nightly run captures the last 7 days of sessions by default (not your entire history) — run hicortex nightly --recapture-window once to import more.

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.
Self-correcting store — every night, stale facts are rewritten in place with dated provenance; near-duplicates resolve into one (verbatim copies kept free, merges recoverable); superseded decisions are demoted, never re-surfaced. No zombie memory.
Unprompted by design — coding agents get recall injected via hooks; instruction-capable clients (Claude Desktop, Cursor-class) get standing instructions, so memory is used without being asked. Plain MCP clients keep full search.
Self-calibrating — recall, decay and merge boundaries report their own statistics; tuning is measured, never guessed.
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 →

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

git clone https://github.com/gamaze-labs/hicortex.git

cd hicortex

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.

License

Personal and noncommercial use is free under the PolyForm Noncommercial License 1.0.0. Commercial use requires a per-seat license — see hicortex.gamaze.com.

Hicortex — AI Fleet Memory

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

Hicortex — AI Fleet Memory

Install

How it works

Features

MCP

Stack

Development

Links

License