Havuz

khive is a system of records and operations for agent-native organizations

The #1 Obsidian MCP for AI memory — freshness-aware, cited, local-first and read-only by default. Dataview, Bases, PDFs, every agent.

Equip the right context for the job — named context kits for AI coding agents, auto-equipped per stack, machine, or task

Self-hosted AI coding agent platform for GitLab, built with LangGraph. Reviews merge requests, resolves issues autonomously, and chats with

Local streaming reverse proxy between AI coding agents (Claude Code, Cursor, Codex) and model APIs (Anthropic, OpenAI, Gemini, MiniMax). Met

Cost saving Cognitive Architecture for AI Agents. Infinite Context. Perfect Recall. Zero Hallucinations.

Persistent organisational intelligence for AI agents. Turn codebases, documents, policies and decisions into a knowledge graph — 13 LLM back

System One Coding Agents: code-level answers at the same score as Claude Fable 5.1 on the same 74-point xz benchmark (69 / 74, 93.2 % each),

ContextAtlas — context infrastructure for AI coding agents: hybrid retrieval, project memory and retrieval observability via CLI, MCP server

Real-time context layer that converts user activity into actionable signals for OpenClaw.

《智能体工程：从一句话到一个闭环》（Prompt · Context · Harness · Loop），本书将大语言模型驱动的智能体系统拆解为四种递进的工程范式，四种范式从 Token 到 System，从一次调用到完整的自主闭环，构成了智能体系统的完整工程视图。

Engineering knowledge infrastructure for AI coding agents.

Loop Engineering — a skill for designing & reviewing autonomous/semi-autonomous agent loops (Claude Code, Codex, Copilot, Gemini).

A compiler for AI coding tasks: pre-resolves repo facts (callers, git history, blast radius, bug-site source) before your coding agent's fir

A tool that replaces everything that can be deterministic in repository work: search, symbols, callers, task scope, history, review and Git

Portable, always-fresh docs for agents and humans. A Surface hub is a conformant OKF concept; Surface adds the freshness OKF leaves out - it

The complete AI operating model for software teams — from first idea to production. Three peer-supervised loops (discovery → build → release

Build system for AI coding-agent context. Generate deterministic, explainable context artifacts for Claude, Codex, Cursor, and MCP.

GatherThread 共序：本地 AI 编程 Agent 多人联机协作、实时共享上下文。Self-hostable collaboration for local AI coding agents, Codex Desktop connector & DeepSeek Har

Build micro-vertical AI products with memory, workflows, human approvals, and governed improvement. The open-source engine behind every Aree

Catch stale versions, broken paths, and missing scripts in your AI instruction files (CLAUDE.md, rules)

Your coding friend in the terminal.

Template for creating a long-term sync hub that checks your company's data sources into Git as plain Markdown, giving AI coding agents durab

Local memory for Codex. Reuse work across chats without LLM calls to organize it.

Evidence-backed retrospectives for AI coding-agent histories. Offline indexing, scoped workflow improvements, and bilingual documentation.

A Codex skill for durable project memory across context compaction

The framework for building stateful agents. Your agent is a folder of state, served over MCP, used from any runtime.

A self-improving knowledge base about LLM agent infrastructure

Workflow-agnostic guardrails for AI coding agents: spec sync + risk-triggered engineering discipline for Claude Code and Codex.

Open-source control plane for Codex projects: Git-backed context, visible agent progress, scoped MCP access, resumable work, and safe handof

inplan — a Markdown editor for human ⇄ coding-agent planning. CLI + desktop editor.

2 text files and a folder. The ICM Folder System I run several businesses on, in plain English, for people who do not write code.

A Claude Code skill that shows you where your folder structure sends an agent before you trust it with the task.

The control plane for your coding agents, however you run them. One checkout of rules, skills, subagents, hooks and stances, projected into

Maintain the same context between AI chats, models, and coding agents. Stop re-explaining your project every time you switch AI tools.

Self-hosted AI memory and MCP coordination for coding agents. Persistent context across repositories and sessions, with knowledge graphs, hy

Bounded repository context and verified patches for Codex and Claude Code. Explicit edit grants, source fingerprints, isolated worktrees, ac

An open standard for agent-native software requirements.

Instant context compaction for Hermes Agent. Builds the compaction summary in milliseconds with no LLM call, keeping the exact commands, exi

The open memory layer for collective agent awareness — a vendor-neutral MCP service for shared AI-agent memory.

Framework-agnostic, local-first memory lifecycle for AI agents: Rust CLI, SQLite/FTS recall, forgetting, audit, consolidation, DOX/Revolve a

Local-first repo maps for coding agents—ranked files, test routes, risks, CLI/MCP/GitHub Action, and public GitHub URLs.

让 DeepSeek Harness 拥有跨会话长期记忆：AI 自动记住你是谁、你的项目和偏好，新会话直接带上背景，生活与工作记忆自动分开互不干扰，零配置无感运行 | Long-term memory for DeepSeek Harness: the AI remembers

Context cards for dbt metrics — 5-layer meta: schema, validator CLI, and installable agent skill so AI agents answer analytical questions ac

aiduMEI⚕爱嘟优忆思——aidu Memory Engine Insight · 智能体通用智慧引擎——Excellent memory system for all agents.

Multiplayer harness where humans and AI agents work together and build on shared context.

Self-hosted evidence store for coding agents.

A persistent memory protocol for AI coding agents that gives projects a shared, markdown based knowledge system to preserve context, decisio

Context optimization layer for LLMs. 65-90% token savings with zero quality loss. Drop-in proxy for Claude, GPT, Gemini, and local LLMs (Oll

Auditable context capsules for LLM handoffs, coding agents, and OpenCode MCP workflows.