MCP servers and skills: search, filter by where they run, and compare.
Persistent file-based planning for AI coding agents and long-running tasks. Crash-proof markdown plans, session recovery after /clear and compaction, per-turn re-injection against context rot, determi
SkillMIT★ 27kNo key
UK planning designations from planning.data.gov.uk, the MHCLG national planning data platform: look up any point in England and get the conservation areas, listed buildings, article 4 directions, gree
Hosted by authorMITFew starsNo key
🔌 Exposes event planning tools over MCP (MEOK AI Labs); see the README for the tool list.
PythonMITFew starsNo key
Durable task planning for Codex/AI coding agents: recovery, bug memory, Mermaid-first design, verification evidence, and safe multi-agent collaboration. 为 GPT-5.6 深度优化，也兼容其他模型。
SkillMIT★ 6No key
A modular toolkit for Claude Code to optimize context, planning, and agent execution with lower token usage and less repeated codebase discovery.
SkillMIT★ 4Few starsNo key
Bootstrap and run a lightweight multi-agent development team. Use when starting or adopting a project, planning work, coordinating implementation and optional QA, brainstorming with distinct perspecti
OfficialSkillMIT★ 40k in collectionNo key
Model Context Protocol (MCP) server for MoveIt2 motion planning, providing AI assistants with the ability to control and plan robot motions.
PythonApache-2.0★ 8No key
Travel Agent MCP with free travel tools plus live x402 Travel Pulse and trip-planning services.
Node.jsMIT★ 1Few starsNo key
Diagnoses and reduces Qdrant memory usage. Use when someone reports 'memory too high', 'RAM keeps growing', 'node crashed', 'out of memory', 'memory leak', or asks 'why is memory usage so high?', 'how
OfficialSkillMIT★ 40k in collectionNo key
ChatGPT thinks. Codex works. Use ChatGPT as the planning brain while keeping the Codex harness.
Node.jsMIT★ 7.4kNo key
Build agentic applications with GitHub Copilot SDK. Use when embedding AI agents in apps, creating custom tools, implementing streaming responses, managing sessions, connecting to MCP servers, or crea
OfficialSkillMIT★ 40k in collectionNo key
Reasoning orchestration MCP server — Tree of Thoughts with deep planning, branching, and revision. Drop-in replacement for sequential-thinking with critical Claude Code string coercion fix. Works with
Node.jsMIT★ 3Few starsNo key
Open-source personal AI assistant & Agent Harness. Plans tasks, runs tools and skills, self-evolves with memory and knowledge. Multi-agent, multi-model, multi-channel. Lightweight, extensible, one-lin
PythonMIT★ 47kNo key
Use when planning, debugging, tuning, evaluating, exporting, or deploying public Nemotron `embed`/`rerank` retrieval recipes.
OfficialSkillApache-2.0★ 3.6k in collectionNo key
MCP server for US individual taxpayers — 39 tools for federal/state tax calculations, credits, deductions, retirement strategies, and tax planning. All calculations run locally. TY2024 + TY2025 (OBBB
Node.jsMIT★ 13No key
Techniques for reducing peak GPU memory in Megatron Bridge — expandable segments, PEFT + SP input re-gather, parallelism resizing, activation recompute, CPU offloading constraints, and common OOM fixe
OfficialSkillApache-2.0★ 3.6k in collectionNo key
🧬 Extend EvoScientist with Installable Skill & Knowledge Packs
SkillApache-2.0★ 480No key
limps your Local Intelligent MCP Planning Server across AI assistants. No subscriptions, no cloud—run it locally. Version control your planning docs in git. No more context drift—one shared source of
Node.jsMIT★ 10No key
AI skills and technical recruiting knowledge for modern HR and talent acquisition teams.
SkillMIT★ 66No key
A field guide for go to market teams using coding agents. Installable skills for campaign planning, CRM context, customer proof, and reviewable agent workflows.
OfficialSkillMIT★ 343No key
The system of action for AI-native cybersecurity—where intent becomes governed execution, evidence becomes operational memory, and every operation improves the next.
GoApache-2.0★ 7.9kNo key
A systematic AI Agent development tutorial covering LLM agents, RAG, tool use, memory systems, multi-agent systems, LangChain, LangGraph, MCP, and agentic RL.｜从零开始学 AI Agent 开发 | 系统、全面、实战导向的 Agent 开发教
SkillMIT★ 599No key
Read/write MCP server for Intervals.icu — training data, planning, and structured workout generation.
PythonMIT★ 97No key
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