Git-native persistent memory for AI coding agents. Implements Google OKF v0.2 with sub-300µs in-memory BM25 search, embedded MCP server, and progressive disclosure. Slashes token bloat by 80% with zer
A Domain-Neutral, Git-Native Persistent Project Memory for AI Agents based on the Open Knowledge Format (OKF) v0.2.
Conversations with AI agents reset when context windows close. Valuable architectural decisions, domain discoveries, and operational facts are lost unless stored persistently.
OKF Agent Memory provides a standardized, vendor-neutral memory layer that lives directly in your repository (knowledge/) as plain Markdown files with YAML frontmatter. It bridges the gap between unstructured ad-hoc markdown files (CLAUDE.md, AGENTS.md) and complex, black-box vector databases.
Blazing Fast Performance ( [!TIP] Reproduce Locally with your own LLM: We provide an automated benchmark runner in pure Go to verify Time-To-First-Token (TTFT) speedups and -80% token reduction on your local hardware (LM Studio / Ollama with Gemma, Qwen, Llama). Run make benchmark or explore the Progressive Disclosure Benchmark Suite.
Clone the repository and compile the standalone okf executable:
This generates the standalone binary at bin/okf.
3. Bootstrapping Agent Memory in Any Project
Scaffold the complete OKF Agent Memory architecture into any new or existing repository with a single command:
This automatically sets up: knowledge/ — OKF v0.2 compliant persistent memory bundle (index.md, log.md) .agents/skills/okf-memory/ — Embedded agent skill definition and capability guides AGENTS.md — Project-tailored operating instructions for AI coding agents Makefile — Convenience tasks for validation (make validate) and search (make search q="...")
From the project README.
Add the radar badge to your README — it shows your project was picked up by MCP Radar and links to this page:
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