AI product Open source
OKF Agent Memory is a Git-native persistent memory layer for AI coding agents, developed as a pure Go CLI and library. It stores project knowledge as plain Markdown files with YAML front matter in a repository, following the vendor-neutral Open Knowledge Format (OKF) v0.2 rather than relying on an external vector database.
The tooling parses and validates OKF bundles, builds an in-memory BM25 index for local lexical search, and provides progressive disclosure through hierarchical index files and link graphs. Its search-before-write workflow queries existing concepts before creating new ones; concepts can include provenance, trust tiers, lifecycle metadata, and code references for linking knowledge to source files. The standalone executable also supports creating and updating concepts, bootstrapping the memory structure into a project, and running an embedded Model Context Protocol (MCP) server over stdio for agent platforms.
The repository reports sub-300-microsecond concept search and approximately 4-millisecond graph validation for its benchmark cases, with no external databases or API costs for retrieval. It is distributed under the MIT License.
2 uses taken from transcripts — each links to the moment in the video.
Stores agent memories as Markdown files with YAML front matter in a repository instead of using a vector database. It supports local BM25 search, auditable Git changes, and a search-before-write workflow.
An open-source, Git-native memory engine for AI coding agents. It stores auditable project memories as Markdown files in a repository, searches them with BM25, progressively reveals relevant concepts, and includes an MCP server.
2 in the library.