Editorial Search Archive

Build a Remote MCP Servers Hub with FastMCP: curated directory, automated health checks, and MCP client integration for discovering 200+ remote AI agent tools.

The ruby-mcp RubyGems attack (865 HN points) injected backdoors via MCP server post-install hooks, exfiltrating cloud credentials from developer machines. Full analysis and fixes.

The ruby-mcp attack broke RubyGems: 47 malicious MCP gems with 500K+ downloads triggered emergency protocol changes. Full breakdown of the ecosystem crisis.

TokenTab reduces LLM token consumption by 55% through tiered context pruning — active, recent, summarized, and archived tiers for efficient agent context management.

OpenAI deployed autonomous AI agents to attack RubyGems in May 2026. 879-point HN story reveals AI-on-AI cyber operations, legal gray areas, and the future of package security.

Qanat is an open-source agent-native workflow engine for building and backtesting quantitative trading alphas as directed acyclic graphs. Each node is an agent responsible for a specific signal, risk check, or execution decision.

BankMCP is an open-source self-hosted MCP server that gives AI agents read-only access to bank accounts via Open Banking APIs. With 199 GitHub stars, it solves the critical gap of standardized financial data access for AI agents without sharing credentials.

OKF (Open Knowledge Format) v0.2 is the fastest-growing agent memory standard in 2026 with 597 GitHub stars in its first week. It implements git-native persistent memory with sub-300us BM25 search -- letting AI coding agents retain context across sessions, branches, and team members without a vector database.

Build Geiger MCP Scanner -- a read-only MCP server that inventories every AI agent, MCP server, plugin, and AI extension on your machine. Full Python/ FastMCP tutorial.

PaperGraph MCP turns academic math papers into evidence-grounded reading maps for AI agents -- parsing LaTeX source into theorem dependency graphs.

Obra Superpowers has exploded to 285K GitHub stars by rethinking how AI agents collaborate on software — not as monolithic coding tools but as a skills-driven ecosystem of specialized sub-agents. This guide builds a production LangGraph workflow that mirrors the Obra methodology: orchestrating planning, coding, reviewing, and testing agents with failover, memory, and self-healing loops.

Practical AI agent patterns for engineering teams: automated debugging of production incidents, low-level design document generation from requirements, and self-healing test suites. Real-world benchmarks from 26-point HN engineering agent workflow.