Geniuz's answer:

• mVara — runs its own fleet of AI agents on Geniuz daily, in production
• First Chair Destinations — knowledge management for vacation rentals
• Tom Ferry International — market intelligence for real estate professionals

ContextForge.dev's answer

Next.js 16 (App Router), React and Tailwind CSS for the dashboard, hosted on Vercel. Supabase (PostgreSQL) with pgvector powers the semantic vector search, and Deno edge functions serve the API. Embeddings use OpenAI text-embedding-3-small. The MCP client is a Node.js package (contextforge-mcp) on npm, implementing the Model Context Protocol.

Geniuz's answer:

Built in Rust. On-device semantic search runs on ONNX Runtime with a bundled embedding model and tokenizer, so inference happens locally with no network calls. Memory is stored in an embedded SQLite database. It connects to AI clients through Anthropic's Model Context Protocol (MCP), and ships with a terminal UI (ratatui) plus native desktop apps for macOS, Windows, and Linux.

ContextForge.dev's answer

ContextForge was born from a simple frustration: AI coding agents forget everything the moment a session ends. Every new conversation meant re-explaining the same architecture, naming conventions, and past decisions. ContextForge was built to give AI agents a permanent, searchable memory through the Model Context Protocol — so knowledge is captured once and reused forever, across sessions and projects. It even dogfoods its own memory to help build itself.

Geniuz's answer:

Geniuz came out of mVara's own work running a fleet of AI agents. The recurring problem was that every agent forgot everything between sessions — every morning was Day 1, re-teaching context, standards, and decisions. mVara built Geniuz to solve that for themselves: a local memory layer their agents share and hand off context through, every day. The product is what the company actually uses, which is why it's shaped around real daily use rather than a demo.

ContextForge.dev's answer

Software developers and engineering teams who use AI coding assistants — Claude Code, Cursor, GitHub Copilot, ChatGPT, Windsurf — and are tired of re-explaining their project, architecture, and conventions every session. It fits solo developers working across multiple projects as well as small teams that need shared, persistent context.

Geniuz's answer:

Developers, AI power users, and teams who work with Claude every day — people running Claude Desktop, Claude Code, Cursor, Windsurf, or their own agent frameworks who are tired of re-explaining their context each session. It's especially suited to fleet and agent operators coordinating multiple AI agents that need shared, persistent memory, and to anyone privacy-conscious who wants that memory to stay on their own machine.

ContextForge.dev's answer

Most memory tools are tied to a single agent or are just a key-value store. ContextForge is MCP-native, so it's portable across all your AI tools; it adds git sync so your codebase history becomes searchable context automatically; and it includes team features (shared spaces, collaborators) that solo-memory tools lack. Setup is one command, there's a genuine free-forever tier with no credit card, and paid plans start at just $9/month.

Geniuz's answer:

Most memory tools are hosted services or developer SDKs you wire into code. Geniuz is local-first and zero-config: install it, run one command, and Claude Desktop has memory — no account to create, no keys to manage, no data sent anywhere. It's open source under the MIT license and fully functional for free. If you value privacy, want to own your data, and want memory that works in the app you already use rather than a framework you have to build around, Geniuz is the simplest path.

ContextForge.dev's answer

ContextForge is memory that lives at the MCP layer, so it works across every AI coding agent at once — Claude Code, Cursor, GitHub Copilot, ChatGPT, and Windsurf — not just one. Save a decision once and any client recalls it later with semantic search. It goes beyond a note store: automatic git sync turns your commits and PRs into searchable knowledge, plus task tracking, snapshots, and team sharing — all through a single MCP server you add with one command.

Geniuz's answer:

Geniuz runs entirely on your own machine. Memory is recalled by meaning, not keywords, through a semantic search model bundled right into the app — no cloud, no account, no API keys, and nothing leaves your computer. It plugs into Claude Desktop through Anthropic's MCP standard with a single command, exposing just three tools: remember, recall, and recent. Memories survive session boundaries and context compaction, so your AI keeps the standards you set and the reasons behind your decisions instead of starting from zero every conversation.