Harness the power of local LLMs with this TUI MCP Client for Ollama. Featuring all core MCP primitives (tools, prompts, resources), agent mode, multi-server, model switching, streaming responses, human-in-the-loop, thinking mode, model params config, system prompts, and saved preferences.

Long-horizon agent skill for Claude Code / Cursor / Codex / Grok Build — multi-task ledger loop, host-portable, clean-context supervisor, verified gates. Markdown library (loop-graph), not a framework.

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

Transforms vague UI ideas into polished, Stitch-optimized prompts. Enhances specificity, adds UI/UX keywords, injects design system context, and structures output for better generation results.

A Claude Code mod that holds subagent fan-out, heavy-context prompts and retry loops before they spend your usage window. It reads your plan's usage, counts agents across every session, and asks in Claude Code's own dialog.

Agent plugin for major harnesses — DeepSeek Harness (DSH), OpenCode, Pi and Codex: define custom AI agent roles with per-role prompts, models, skills, permissions, memory and multi-agent orchestration.

DSH Web 输入体验增强插件：可配置发送/换行键位 + 自定义输入框右键菜单 + 面板尺寸记忆 + 快捷指令（分类 / 跨分类移动 / 关·每次·仅首次三种插入模式 / 存 ~/.dsh/quick-prompts.json）+ 提示词优化（0.11.1 起工具行有独立「优化」按钮、带秒表与斜杠命令保护、写回前比对草稿） + OpenCode 会话请求头 + Windows 默认终端切换（把模型的 PowerShell 工具换成 Git Bash）+ 官方持久终端六件套（terminal_open/r

A rail of your Claude Code session's prompts: hover to read, click to jump (function hooks / Mods)

Exposes a single ask_warriorgpt tool that lets Claude Code delegate self-contained code generation prompts to Wayne State's hosted model API, passing files to and from disk so the content never counts against the Claude plan. It validates multi-file edits before writing and logs per-session token usage, keeping design and debugging work with Claude.

Enables AI clients to drive local video editing projects through a CEP bridge, covering media ingest, sequence and timeline editing, effects, keyframes, captions, markers, audio, color, and exports across hundreds of discoverable tools. Ships context resources, guided prompts, and higher-level assembly workflows for agent-driven editing.

Enables AI agents and LLMs to persist facts, preferences, and observations in a local SQLite store and to build and traverse subject-predicate-object knowledge graphs across sessions. It provides fuzzy keyword search and graph queries so assistants retain context and recall prior project history without repeating prompts.

Enables building zero-dependency Model Context Protocol servers over the Streamable HTTP transport, exposing typed tools, resources and URI templates, prompts, background tasks, and OAuth-protected endpoints. It can be mounted into FastAPI, Starlette, Flask, Django or any ASGI/WSGI app, or run standalone on the Python standard library alone.

Claude Code lifecycle contextual hooks for Mnemonik. PreToolUse Edit/Write/NotebookEdit/Bash gates plus SessionStart bootstrap warming, clean Stop, PreCompact context_snapshot creation, bounded SessionEnd cleanup, and UserPromptSubmit context injection. T

Rules-based context reduction, planning checks, research prompts and fixed experiences for agents.