基于MCP协议的任务文档管理系统
医疗营销系统任务自动化MCP
micromark extension to support GFM task list items
mdast extension to parse and serialize GFM task list items
Lightweight core CLI surface for Claude Flow — memory + hooks commands only. Designed to load fast on cold npx cache (<5s) so plugin skills don't race the 30s MCP-startup timeout. The full @claude-flow/cli metapackage lazy-loads everything else on top of
Memory and task management MCP Server
A shim for the setImmediate efficient script yielding API
MCP Server for Slack task management with Claude Code
MCP server for scheduled task management and execution with support for interval, cron, and date-based triggers
A simple tool to keep requests to be executed in order.
Playwright Tools for MCP
MCP server for Bitbucket API integration - supports both Cloud and Server
<h1 align="center">Backlog.md</h1> <p align="center">Markdown‑native Task Manager & Kanban visualizer for any Git repository</p>
Coinbase Design System - MCP Server
High-priority task queue for Node.js and browsers
task list extension for tiptap
Shrimp Task Manager is a task tool built for AI Agents, emphasizing chain-of-thought, reflection, and style consistency. It converts natural language into structured dev tasks with dependency tracking and iterative refinement, enabling agent-like develope
Model Context Protocol implementation for TypeScript
MCP Server for Asana
task item extension for tiptap
A TypeScript SSE proxy for MCP servers that use stdio transport.
Help agents automatically write and test stories for your UI components
The official TypeScript library for the Cloudflare API
High-priority task queue for Node.js and browsers
A Model Context Protocol (MCP) server that provides tools to interact with the TickTick API
Claude Swarm enables you to run multiple Claude Code instances that communicate with each other via MCP (Model Context Protocol). Create AI development teams where each instance has specialized roles, tools, and directory contexts. Define your swarm topology in simple YAML and let Claude instances collaborate across codebases. Perfect for complex projects requiring specialized AI agents for frontend, backend, testing, DevOps, or research tasks.
llm.rb is Ruby's most capable AI runtime. It runs on Ruby's standard library by default. loads optional pieces only when needed, and offers a single runtime for providers, agents, tools, skills, MCP, A2A (Agent2Agent), RAG (vector stores & embeddings), streaming, files, and persisted state. As a bonus, llm.rb is also available for mruby. It supports OpenAI, OpenAI-compatible endpoints, Anthropic, Google Gemini, DeepSeek, xAI, Z.ai, AWS Bedrock, Ollama, and llama.cpp. It also includes built-in ActiveRecord and Sequel support, plus concurrent tool execution through threads, tasks (via async gem), fibers, ractors, and fork (via xchan.rb gem).
+pikuri+ is the convenience bundle for the pikuri AI-assistant toolkit. It ships no Ruby code of its own beyond a tiny entry file that +require+'s each sibling gem; +gem install pikuri+ pulls in pikuri-core, pikuri-extractors, pikuri-pdf, pikuri-skills, pikuri-tasks, pikuri-memory, pikuri-workspace, pikuri-code, pikuri-mcp, pikuri-subagents, pikuri-vectordb, and pikuri-assistant in one shot, and +require 'pikuri'+ boots all of them. Privacy-conscious users who want a minimal dependency tree to audit should install +pikuri-core+ directly and opt into the extension gems they actually need — same +bundle add+ pattern Rails users have always had. See each pikuri-* gem's README for its individual surface.
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