OpenViking AI

OpenViking is an open-source context database built for AI agents. Instead of scattering memory, knowledge, and skills across different vector stores and code modules, it gives you a single, file-system-like structure. Everything lives under a viking:// URI, making it easy for agents to find and use what they need. Think of it as a filesystem for your agent's context — you can browse, search, and retrieve relevant information without dumping everything into the prompt.

The system organizes context into three types: Resources (external knowledge like web pages and docs), Memory (long-term user and agent memory), and Skills (callable capabilities). Agents access these through a unified directory, and the built-in indexing means they can search efficiently. Benchmarks on the site show that agents using OpenViking achieve over 80% task completion on the LoCoMo evaluation, while reducing input token usage by up to 63% compared to native memory solutions. It integrates with popular agent frameworks like Claude Code, Cursor, Hermes, and OpenClaw out of the box — setup takes just a few terminal commands.

OpenViking is best suited for developers and researchers building AI agents that need persistent, organized context. If you're working on multi-agent systems, long-running assistants, or any project where context management is a bottleneck, this tool can save you tokens and improve reliability. It's open source with over 32,000 GitHub stars, and teams at ByteDance, Meituan, and several universities are already using it in production.