Content-aware output compression for AI coding assistants. 36 specialized processors cut CLI output tokens by 60-99% (git, pytest, npm, terraform, kubectl, docker, and more) without losing errors, diffs, or stack traces.

Self improving agents through iterations

Install engineering discipline into any AI coding assistant. Composable skills for design, implementation, review, and team standards. Better process, not just better prompts.

DeepSeek Harness (dsh) 接入飞书/Lark bot，扫码即用：流式卡片、项目工作区、并行任务、多角色 Agent、跨会话通知、对话内模型/密钥管理与安全网守护（dsh 崩溃后飞书仍可自救）。A scan-to-connect bridge bot connecting DeepSeek Harness (dsh) into Feishu/Lark: streaming cards, workspaces, parallel tasks, multi-role agents, cross-session notify, in-chat model/key management, and a safety-net guardian.

iCloud for AI Agents — cross-agent sessions, skills, memory, and vault.

Local RAG MCP Server - Easy-to-setup document search with minimal configuration

Unified npm bootstrap for the Yaver agent, SDK injection, and local-first developer runtime

Builds up to a goal in a field you have no expertise in: splits it into the foundations that goal actually needs, mobilizes what you already hold, learns what is missing, and leaves every solved path behind for the next goal. Nothing is called done until a check passes.

Deepseek Harness、Openclaw知识图谱记忆插件。2026年4月受邀发布在清华大学讨论会。Knowledge Graph + Memory；Knowledge Graph Context Engine for OpenClaw — extracts structured triples from conversations, compresses context 75%, enables cross-session experience reuse

Persistent memory for agents. Corrections stick, context compounds, every session starts smarter.

A portable memory protocol for AI agents — load it as standing rules; a curation discipline + reference spec + optional cap hook.

GeneXus 18 MCP server — read, edit, and analyze GeneXus knowledge base objects (transactions, web panels, procedures, SDTs) directly from Claude, Cursor, and other AI agents over the Model Context Protocol.

Cut context bloat in your AI-agent stack: find and safely prune unused skills, MCP servers and subagents from real transcript evidence

MCP server for AI image generation

Wenlan is a knowledge base for the AI-native age. Your AI agents capture what they learn, Wenlan keeps it current and distills it into source-cited wiki pages you can trust

Your personal AI runtime, local-first. Patchwork OS gives any AI model a consistent set of tools, YAML recipes, a delegation policy with approval queue, and a durable trace memory — all on your machine, all under your policy.

Vestige gives AI agents sharp memory: a local-first Rust MCP server that reaches backward through time to find the quiet change, decision, or service that caused today’s failure, not the lookalike.

The agent runtime for React Native and Expo: an MCP server that sees the app the way React sees it, knows which file produced each element, acts without coordinates, and proves it works. Local only, zero dependencies.

Documentation memory for AI coding agents—route project knowledge, reduce repeated context loading, and validate living Markdown docs.

A Context-Aware Multi-Agent Orchestration Engine

Supports GPT Image 2, Seedance & ComfyUI, with a 1,400+ prompt library, carefully crafted hooks and a multi-task orchestration system

Persistent project memory for AI coding agents. Structured scaffold + drift detection CLI.

Repository-native protocol and local MCP server for Work, Docs, History and durable project Memory.

Notes for you, Memory for your agents. / 内置 Deepseek harness Agent / 适用 办公 & 写作 & Coding