Havuz

Generate and maintain AI-readable project memory, worklogs, and handoffs for any repository.

Any brain, any agent. Package an AI agent's brain — persona, MCP stack, skills, memory, config — into one open, signed bundle and install it

Local session transcript memory for Claude Code and Codex — search past sessions with FTS5 + semantic vectors.

AI-agents development memory/tasks/context

Self-hosted shared memory for AI agents: vaults of people, facts and decisions your agents recall over MCP or REST, with semantic, keyword a

Archive snapshot repo of the original concept and 0-1 invention features, please utilize the constantly updated cypher-tempre-genesis repo f

The Company Brain your agents install — use your coding agent to run projects and coordinate agents, not just code. Cross-project knowledge

Local long-term memory for AI coding agents. Keeps every conversation word for word, costs nothing to save, and is shared by all your agents

Local-first control plane for long-running and multi-agent AI systems. Observe, steer, recover and orchestrate agents.

Persistent memory for AI coding agents — self-hosted, MCP-native, append-only. One Docker image, one SQLite file.

A second brain for Claude Code and Codex that keeps receipts: skills as a plugin marketplace, opt-in persistent memory over MCP, vault templ

Zero-infrastructure, local-first memory for AI agents. One SQLite file — no Postgres, Neo4j, or cloud. Bi-temporal supersession (updates, ne

Local-first, eval-first memory for long-horizon AI agents — no LLM at ingest. Python SDK + MCP server with source-traceable recall, belief r

Project-local agent harness skill for traceable AI workflows

Shared memory for Claude Code, Codex, and Cursor. Your agent recalls decisions from weeks ago — including what the other engines worked out.

Local-first, auditable memory for AI agents, with governed retrieval, delegated context delivery, and verifiable execution evidence. Works w

your glass-box company brain — tells you what it doesn't know (deterministic gap analysis). MIT core · MCP · PGLite→Postgres.

Keep your decisions, projects, and context when you switch between Claude Code, Cursor, opencode, and the rest — one plain-markdown bundle i

Sable is a self-hosted agentic platform that lives on your machine and grows with you. Part AI companion, part dev environment, part chaos e

Zero-dependency memory palace + safe model-agnostic curation for LLM agents (extracted from Birkin)

Stop re-explaining your work to your coding agent. Plain markdown and YAML in git, read at session start by Claude Code, Codex and Copilot C

Token-native agent memory retrieval for LLMs, without embedding APIs or vector databases.

Self-hosted memory service for AI assistants and agents.

The brain is a git repo. Memories are markdown files with YAML front-matter, committed like any other file. Git history is the audit tra

Knowledge engine for AI agents: your documents become a git-versioned markdown knowledge graph the agent navigates over MCP. Curated summari

Build a second brain every AI can share: your content in Oracle AI Database 26ai — semantic search with in-database embeddings, a self-compi

A Codex skill that turns 'do everything' into safe scope, defaults, memory, and AI observability.

Memory and state for AI agents: every correction kept with history, and agents that resume from their own records. Runs on your database.

Local-first memory for AI agents: one SQLite file, zero deps. Recency-aware exact recall, conflict detection, time-travel journal, MCP serve

CLAgent: A Continually Self-Evolving Agent System

Agent memory for Claude Code, Cursor, Codex: MCP server + Graph RAG over your Obsidian or markdown notes. Wikilinks are the graph, SQLite th

Database engine for AI agents — write memory, recall by cue, trust sources over chat. Not SQL, vector DB, or mem0.

Claude Code plugin that makes coding agents measurably cheaper over time: collect token costs, distill candidate rules, benchmark them on a

Run a team of AI coding agents, such as Claude Code and Codex, on one project. They hand work to each other and review it across AI companie

Turn one ZCode conversation into a restartable multi-agent workflow with persistent memory, isolated coding agents, real-result checks, and

Research design for a Jev-native agent system:enable more options than jev provided with virtulization and paging, tool integration, externa