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Preview image for MCP Server Deployment Guide: Build vs Buy in 2026

This 2026 guide compares self-hosted and managed MCP server deployment for enterprise teams, breaking down total cost of ownership, security responsibilities, and compliance requirements. It explains how the new stateless MCP specification changes infrastructure needs, and provides a framework to choose the right deployment model based on team size, regulatory constraints, and engineering capacity.

Preview image for MCP Server with Notion

Notion's official hosted MCP server offers seamless AI workspace integration but has major capability gaps compared to its deprecated local counterpart, plus hidden costs tied to Notion plan tiers. Engineering and enterprise teams must evaluate these tradeoffs carefully before adopting the integration for production use.

Preview image for Supabase MCP Server: Unspoken Privilege Inversion Problem

The official Supabase MCP server grants AI assistants default service_role access that bypasses all Row-Level Security policies, creating a severe privilege inversion risk. While it offers robust database and backend management capabilities with enterprise OAuth support, its default authorization model leaves production databases exposed to indirect prompt injection attacks. Teams must enforce strict read-only and project-scoped configurations to mitigate these risks.

Preview image for How to Build an MCP Server in Python

This guide covers building production-ready MCP servers in Python using the official SDK and FastMCP, along with key tradeoffs between local and remote deployment architectures. It also breaks down hidden cost drivers like authentication and token overhead that routinely exceed server development expenses, and outlines critical security updates required before the July 2026 MCP specification finalizes.

Preview image for Cursor vs Gemini CLI: Why the Real Answer Is Neither Alone

The 2026 AI coding assistant market has evolved past single-tool selection, as Cursor and Gemini CLI no longer compete for the same use cases. Cursor is building a vertically integrated agent-native platform, while Gemini CLI is being sunset for Google's Antigravity ecosystem, making stack-aligned choices far more valuable than head-to-head tool comparisons.

Preview image for OpenAI Codex Best Practices: A Practical Guide for 2026

OpenAI Codex has grown far beyond a coding assistant, with 20% of its 5 million weekly active users now non-developers. This guide explains how to align your workflows with Codex's token-based billing and execution model to avoid runaway costs and maximize productive output, covering task decomposition, model selection, and cross-role governance for teams.

Preview image for Cursor Agent Mode Explained

Cursor's Agent Mode is the default in its chat panel, enabling autonomous multi-file code changes, terminal commands, and test iteration. Token costs for Agent Mode range from 8,000 for well-scoped tasks to over 60,000 for vague prompts, making deliberate selection between Cursor's four agent modes critical for efficient, cost-effective workflow.

Preview image for Cursor Memory System Explained

Cursor has no native persistent memory across chat sessions, forcing users to re-explain project context every time they start a new conversation. A range of MCP-based memory servers and cloud-hosted alternatives fill this structural gap, each with distinct tradeoffs for setup, privacy, and automation. This guide compares the top options and recommends the best fit for solo developers and engineering teams.

Preview image for Cursor Pricing Explained

Cursor's June 2026 Teams pricing overhaul introduces split usage pools that make its proprietary Composer model far cheaper than third-party options like Claude and GPT. This structure is a deliberate lock-in strategy to push teams toward Cursor's full proprietary AI coding stack, not just a response to cost complaints. Individual plans use a credit pool system where Auto mode does not drain credits, making Pro plans sufficient for most developers.