IGenius Memory Server

PyPI Python VS Code Marketplace License: MIT GitHub

A structured, AI-powered memory backend that gives any MCP-compatible agent persistent memory via the iGenius Memory service. All AI processing happens server-side — you just need an API key.

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3 Ways to Use iGenius

Client	Install	Best For
🧩 VS Code Extension	Marketplace	Full sidebar UI, memory browser, AI provider settings
⚡ MCP Server	pip install igenius-mcp	Any MCP client — VS Code, Claude Desktop, Cursor, Windsurf
🖥️ Desktop App	Windows Installer	Standalone system-tray app, works with any editor

Get a free API key at igenius-memory.online — all three clients use the same key.

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1. VS Code Extension (Marketplace)

Install directly from the VS Code Marketplace — no pip, no config files:

ext install igenius-memory.igenius-memory

Or search "iGenius Memory" in the Extensions panel. Includes sidebar UI, memory browser, status bar indicator, AI provider settings, and auto-warms briefings on a configurable interval.

2. MCP Server (pip)

For any MCP-compatible client (VS Code Copilot, Claude Desktop, Cursor, Windsurf, etc.):

pip install igenius-mcp

Then add to your MCP config:

VS Code — ~/.vscode/mcp.json:

{
  "servers": {
    "igenius-memory": {
      "command": "igenius-mcp",
      "env": { "IGENIUS_API_KEY": "ig_your_key_here" },
      "type": "stdio"
    }
  }
}

Claude Desktop / Cursor / Windsurf — add to your MCP config file:

{
  "mcpServers": {
    "igenius-memory": {
      "command": "python",
      "args": ["-m", "igenius_mcp.server"],
      "env": { "IGENIUS_API_KEY": "ig_your_key_here" }
    }
  }
}

⚠️ Windows users: If VS Code can't find igenius-mcp, use python -m igenius_mcp.server instead.

3. Desktop App (Windows)

Standalone system-tray application — works alongside any editor or IDE:

• Download Installer (NSIS setup or MSI)
• Built with Tauri + Rust — lightweight, native, ~5 MB
• System tray with quick access to briefings, search, and memory stats
• Configure LLM provider (LM Studio, OpenAI, Anthropic, Google) from the UI

Restart VS Code after installing the extension or adding MCP config — all 17 memory tools become available to Copilot and any MCP-compatible agent.

Available Tools

Tool	Description
memory_briefing	Session briefing from all memory layers (call FIRST)
memory_ingest	Ingest user/agent messages for AI extraction
memory_consolidate	Merge accumulated extracts into master briefing
memory_process	Detect trigger words and auto-classify text
memory_store	Direct store to a specific memory layer
memory_search	Natural language search across memories
memory_recall	Retrieve all persistent session memories
memory_summarize	LLM-powered summary of a memory layer
memory_delete	Delete a memory by ID
memory_update	Update fields on an existing memory
memory_review	List short-term memories for triage
memory_promote	Promote short-term → long-term
memory_pin	Pin a fact permanently (user-confirmed, never expires)
memory_triggers_list	List trigger words and their layers
memory_triggers_add	Add a new trigger word
visual_report	Render URL → screenshot → vision analysis → full UI/UX report (requires [visual])
visual_screenshot	Render URL → return base64 PNG (requires [visual])

LLM Requirements

iGenius uses an LLM backend for AI extraction, consolidation, and (optionally) visual analysis. You can use a local or remote LLM provider.

Local Setup (LM Studio, Ollama, etc.)

Requirement	Minimum
GPU VRAM	6 GB+
Recommended model	Qwen 3.5 4B (non-thinking) or equivalent
Context window	3,000+ tokens

⚠️ IMPORTANT: Do NOT use thinking/reasoning models (e.g. QwQ, DeepSeek R1, o1, o3). Thinking models emit <think> chains before the actual response, which breaks iGenius's structured JSON extraction pipeline. Only use standard non-thinking (instruct/chat) models.

Why these specs? iGenius sends structured extraction prompts that expect clean JSON output. A 4B-parameter non-thinking model at 3k context is the sweet spot for fast, accurate extraction without hallucination or timeouts. Larger models (8B+) work too — just ensure you have the VRAM headroom and that the model is a non-thinking variant.

Remote Setup (OpenAI, Anthropic, Google, etc.)

No local hardware requirements. Any API-accessible model works — configure the provider, model name, and API key in the VS Code extension settings or environment variables.

Environment Variables

Variable	Required	Default
IGENIUS_API_KEY	Yes	—
IGENIUS_API_URL	No	https://igenius-memory.online/v1

Visual Tools (Optional)

Give your AI agent eyes — render any URL, take a pixel-perfect screenshot, and get instant UI/UX analysis from a local vision model.

Install

pip install "igenius-mcp[visual]"
python -m playwright install chromium

Then load a vision-capable model in LM Studio (e.g. Qwen 3.5 9B Vision, non-thinking).

⚠️ Do NOT use thinking/reasoning vision models — same restriction as above.

Visual MCP Tools

Tool	Description
visual_report	Render URL → screenshot → vision analysis → full UI/UX report
visual_screenshot	Render URL → return base64-encoded PNG (no analysis)

Visual Environment Variables

Variable	Default	Description
IGENIUS_VISION_URL	http://localhost:1234/v1	Vision model API endpoint
IGENIUS_VISION_MODEL	auto-detect	Override the vision model name
IGENIUS_VISION_KEY	—	API key for vision endpoint (e.g. LM Studio auth token)
IGENIUS_VIEWPORT_W	1280	Screenshot viewport width
IGENIUS_VIEWPORT_H	800	Screenshot viewport height

100% local — screenshots and analysis never leave your machine.

Agent Instructions

For best results, add the iGenius agent instructions to your workspace:

• VS Code: Place igenius.instructions.md in ~/.vscode/prompts/
• Claude Code: Add to CLAUDE.md
• Workspace: Add to .github/copilot-instructions.md

Get the template at igenius-memory.info

How It Works

Agent ←→ MCP (stdio) ←→ igenius-mcp ←→ REST API ←→ iGenius Backend

The memory tools are a thin proxy — they translate MCP tool calls into REST API requests. All AI extraction, LLM summarization, and encryption happens server-side.

The visual tools run locally — Playwright renders URLs on your machine and a local vision model (e.g. LM Studio + Qwen2.5-VL) analyzes the screenshots. Screenshots and analysis never leave your machine.

Plans

Plan	Price	Requests	API Keys	IPs/Key
Starter	Free	1,000/week	1	3
Pro	$19/mo	50,000/day	5	10
Enterprise	Contact	500,000/day	20	50

Details at igenius-memory.store

Coming Soon

iGenius Context Engine — unlimited effective context for local LLMs through intelligent recursive summarization. Run a 3B model with a 4K context window and handle conversations of any length.

Links

• Landing Page
• Documentation
• API Portal & Free Key
• Store & Plans
• VS Code Extension
• Desktop App

Support the Project

iGenius Memory is built and maintained by NovaMind Labs. If you find it useful, here's how you can help:

• Star the repo — it helps more developers discover iGenius
• Upgrade to Pro — $19/mo directly funds development → igenius-memory.store
• Report bugs & ideas — open an issue
• Spread the word — tell your friends, tweet about it, write a blog post

Every user, star, and subscription helps keep iGenius alive and improving. Thank you!

License

MIT