Project memory system for AI coding assistants (Claude Code, Cursor, Codex): session logs, project wiki, rules, TODOs, and handoff.

A human-governed AI coding workflow that distills ephemeral session context into persistent project memory—making work traceable, reviewable, and resumable.

Local-first game design OS for AI agents: turn sessions into evidence, experiments, reviewable decisions, and durable project memory—Human Gates and rollback.

Project memory for coding agents and humans: the reasoning behind a codebase as Markdown in the repo, versioned by Git, so nothing rejected is proposed twice. No database, no daemon, no account.

MCP server for external memory layer for AI agents + more . Download from pypi , and get started

(HAM) Memory system for AI coding agents. Cut token usage by 80% by scoping context to directories.

Compiles AI agent traces and truns them into reusable context.

Persistent project knowledge graph for coding agents. MCP server with semantic search, in-process embeddings, and web explorer.

Engineering decisions engine that know when they're stale. Frame, compare, decide — with evidence decay and parity enforcement. For Claude Code, Cursor, Gemini CLI, Codex and more.

DevContext is a cutting-edge Model Context Protocol (MCP) server designed to provide developers with continuous, project-centric context awareness. Unlike traditional context systems, DevContext continuously learns from and adapts to your development patterns and delivers highly relevant context providing a deeper understanding of your codebase.

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 zero external databases or dependencies. Built in pure Go.