Context, Memory & RAG tools for GitHub Copilot

Persistent memory server for coding agents that retrieves only the top-K relevant observations via hybrid BM25 + vector + graph search instead of loading a whole memory file into context (~1,900 vs 22K+ tokens at 240 observations, 92% fewer). Reports 95.2% R@5 on LongMemEval-S with a local embedding model, plus a reproducible eval harness to check that claim. One server serves 20+ agents (Claude C

An AI-powered custom node for ComfyUI designed to enhance workflow automation and provide intelligent assistance

Agent Package Manager

Engineering discipline layer for Claude Code -- 67 slash commands, 20 coding rules, 27 skills, 9 agents, quality gates between every step. 8 stack profiles (Go, Python, Java, Kotlin, React, etc.), agent memory across sessions. Install: npx @c0x12c/spartan-ai-toolkit@latest --local

by serpro69 - 🦫 Privacy-first virtualization layer for LLM context with MCP protocol for tool access

Open-source linter for AI context files (CLAUDE.md, .cursorrules, copilot-instructions.md) that catches stale paths, wrong commands, and token waste by validating against the real codebase

One source of truth for AI coding rules across every IDE. Author rules, agents, and skills once in plain markdown, and the engine routes them into each tool's native format (Claude Code, Cursor, Copilot, Codex, Pi, OpenCode, AGENTS.md) with no duplication or drift. Zero dependencies, bash + awk, MIT