MCP servers and skills: search, filter by where they run, and compare.
Nothing matches every word exactly, so these are the closest matches.
A modular AI engineering stack for building and orchestrating coding, API, database, and code review agents with a simple SDK.
SkillMIT★ 2Few starsNo key
22 composable, auto-triggering skills engineering documentation skills covering the complete software lifecycle: spec, feasibility, architecture, design, API, database, ADR, security, deployment, oper
SkillMIT★ 6No key
Multi-tenant chaos-engineering / API-resilience control plane, demonstrating fault injection, optimistic concurrency, Kafka-driven execution, and distributed-systems resilience. Java 21, Spring Boot 4
SkillMITFew starsNo key
🔥 Devil Agent — Autonomous AI Engineering Platform · 40-word zero-knowledge auth · OpenAI-compatible agent · NEXUS engineering OS · MCP server · self-hostable · MIT
SkillMIT★ 2Few starsNo key
A lab for a per-call policy gate, an action monitor and a scripted approval step over an incident agent. Closed at a baseline, 2026-09-06.
SkillMITFew starsNo key
Stop AI agents from shipping bad code. Deterministic architecture, security, API, database, and UI quality control for coding agents.
SkillMIT★ 5No key
55 production-grade Google Cloud data engineering projects in Python — BigQuery, Dataflow/Apache Beam, Composer/Airflow, Pub/Sub, Dataproc, Vertex AI, Gemini, RAG, MCP. Live-tested on GCP.
SkillApache-2.0★ 8No key
面向 Claude Code、Codex 等 AI 编程 agent 的工程技能，覆盖需求澄清、测试验证、代码评审，以及改数据库、删文件、动服务器前的确认与回滚准备。Engineering skills for Claude Code, Codex, and other coding agents, covering clarification, testing and verification,
SkillMIT★ 3Few starsNo key
Reliable memory and context infrastructure for AI coding agents: source-backed facts, review-gated learning, MCP/SDK/UI, and replaceable Qdrant/Graphiti retrieval.
PythonApache-2.0★ 7No key
Kaiban Distributed - Distributed Agentic AI Platform - Actor Model Kanban Framework Implementation with Enterprise Messaging Layer State (Redis/Kafka) and Individual Deployed AI Nodes (Node.js/TypeScr
SkillGPL-3.0★ 6No key
A reusable Agent Skill for senior-level software engineering workflows: requirements analysis, repository exploration, architecture, database/API design, implementation, testing, verification, and ove
SkillMIT★ 1Few starsNo key
Two friends learning AI engineering, and the game we built to keep each other going: XP, quiz duels, code races and an in-browser AI lab.
SkillApache-2.0★ 6No key
One deterministic market-data engine for crypto and US equities. 49 capabilities declared once and projected to CLI, REST and MCP; every record carries how it came to exist.
PythonApache-2.0★ 3Few starsNo key
Runnable AI engineering modules: agents, MCP, memory, RAG, voice, fine-tuning, MLOps, and security. One folder per module.
SkillMIT★ 9No key
Plateforme Agentique MLOps & SRE pour une Gouvernance déterministe d'agents LLM — — — — — — — — Production-Hardened, Platform-Agnostic MLOps & SRE Agentic Control Plane. Features Fail-Closed Policy En
PythonMITFew starsNo key
Memory server for MCP clients (TypeScript, SQLite/FTS5): quarantines injected instructions and records provenance; on npm.
Node.jsMITFew starsNo key
Save thousands of lines of code by building universal, domain-agnostic Multi-Agent Systems (MAS) through high-level semantic orchestration. This repository provides a production-ready blueprint for th
SkillMIT★ 290No key
Reusable Codex skills for data engineering and database DDL: ETL pipelines, field mapping, data governance, data quality, orchestration, and cross-database SQL migration.
SkillMIT★ 1Few starsNo key
Write or rewrite architecture subsystem docs, ADRs, and reference material for the engineering team. Use when creating, updating, or reviewing docs under docs/architecture docs/, or when the user asks
OfficialSkillApache-2.0★ 48k in collectionNo key
🧠 Stop building AI that forgets. Master MCP (Model Context Protocol) with production-ready semantic memory, hybrid RAG, and the WARNERCO Schematica teaching app. FastMCP + LangGraph + Vector/Graph st
SkillMIT★ 27No key
Guides Qdrant monitoring and observability setup. Use when someone asks 'how to monitor Qdrant', 'what metrics to track', 'is Qdrant healthy', 'optimizer stuck', 'why is memory growing', 'requests are
OfficialSkillMIT★ 40k in collectionNo key
Diagnoses and improves Qdrant search relevance. Use when someone reports 'search results are bad', 'wrong results', 'low precision', 'low recall', 'irrelevant matches', 'missing expected results', or
OfficialSkillMIT★ 40k in collectionNo key
Guides Qdrant query volume scaling. Use when someone asks 'query returns too many results', 'scroll performance', 'large limit values', 'paginating search results', 'fetching many vectors', or 'high c
OfficialSkillMIT★ 40k in collectionNo key
Different techniques to optimize the performance of Qdrant, including indexing strategies, query optimization, and hardware considerations. Use when you want to improve the speed and efficiency of you
OfficialSkillMIT★ 40k in collectionNo key
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