The July 2026 MCP specification makes the protocol stateless, eliminating session IDs and sticky sessions for simpler horizontal scaling. This shift moves security and routing responsibilities to application developers, requiring explicit architectural investment for reliable production deployments.
Tag: MCP
98 posts tagged with "MCP" — Page 3 of 4
Enterprise Managed Authorization (EMA) for MCP only validates who can connect to agent tools, leaving per-action runtime decisions unaddressed. This post explains how to build or buy a runtime authorization gateway that enforces policy for every agent tool call and delivers required audit trails for enterprise compliance.
The default GitHub MCP server authentication model is built for individual developers, not enterprise multi-agent deployments. This guide explains how to configure local GitHub App token authentication to enable dynamic per-workflow identity, avoid Copilot license requirements, and support GitHub Enterprise Cloud. You'll learn step-by-step setup, security best practices, and governance patterns for production use.
The Model Context Protocol's metadata-heavy design imposes a massive hidden token tax on enterprise deployments, with costs jumping 19-40x for common workflows. MCP gateways solve critical governance and security gaps but cannot reduce this inherent protocol overhead, and faster gateways often lack compliance features. Enterprises must weigh token costs, latency, and security requirements when selecting a gateway.
AI coding agents treat repository instruction files like AGENTS.md as trusted authority, creating a critical, widely overlooked attack surface that adversaries exploit to poison agent behavior. Traditional security controls including IAM, EDR, and static scanning cannot detect these attacks, as agents execute malicious instructions using their own legitimate credentials with no alert triggers.
Over 200,000 MCP servers are exposed to prompt injection due to missing JSON schema validation, per recent security audits. Unconstrained tool parameters and outputs create universal attack surfaces that let attackers hijack AI agent workflows. This guide outlines critical validation steps to harden MCP deployments against these threats.
A 2025 internet scan found nearly 2,000 unauthenticated public MCP instances, and 53% of deployed servers still rely on insecure long-lived API keys. This guide breaks down why OAuth 2.1 with PKCE is mandatory for remote MCP deployments, plus actionable zero-trust controls to secure agentic workflows at scale.
The official GitHub MCP server adds up to 42,000 tokens of schema overhead per agent call, consuming 21% of a 200K context window before any real work begins. For production and multi-tenant B2B workloads, a thin REST API adapter with GitHub App authentication eliminates this tax, provides higher rate limits, and removes mandatory Copilot license dependencies.
With over half of 2026 code commits AI-generated and 40-62% containing security flaws, standard container isolation can't protect against compromised MCP tool calls. This post explains why hardware-virtualized microVMs are the required baseline, compares managed and open-source sandbox options, and covers key operational and cost considerations for production agent deployments.
The July 2026 MCP spec update removes the protocol-level session layer, eliminating the need for sticky sessions and shared session stores for remote MCP servers. Operators have a 10-week migration window ending July 28, 2026 to update their infrastructure before the final spec ships. The shift enables horizontal scaling via round-robin load balancers but requires refactoring session-dependent code to use explicit client-passed handles.
The most-installed GitHub MCP server has near-universal adoption but critical production gaps. It lacks GitHub App token support, imposes high per-call token overhead, and requires a paid Copilot license for OAuth. Solo developers may find it convenient, but enterprise B2B deployments require the GitHub REST API instead.
Enterprise-Managed Authorization (EMA) for MCP streamlines enterprise connection governance via centralized IdP control, but it does not cover runtime, context-aware authorization for individual agent tool calls. This creates a critical governance gap where over-permissioning becomes the default, leaving teams responsible for implementing action-level access controls to secure agent workflows.
The stable Enterprise-Managed Authorization (EMA) extension for MCP centralizes enterprise access provisioning for AI agent tooling via identity providers. However, EMA only governs connection-level access, leaving runtime per-action authorization entirely to implementers and creating a critical security governance gap for enterprise teams.
A 2026 internet-wide scan found 40% of public MCP servers have zero authentication. The new stateless MCP spec removes protocol-level session hijacking risks but shifts all security responsibility to individual implementers, leaving most deployments exposed. This guide outlines 12 essential production controls to secure MCP against real-world attack vectors.
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.
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.
The official Anthropic-maintained PostgreSQL MCP server is deprecated, archived, and has an unpatched SQL injection vulnerability that bypasses its read-only safety mode. Teams connecting AI agents to production PostgreSQL databases should use one of several secure, actively maintained alternatives instead.
Stripe's official MCP server enables AI agents to interact with payment APIs, but its default restricted key security model is insufficient to prevent costly misuse. Production deployments require additional rate limiting, approval gates, and data governance to avoid financial loss and compliance violations.
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.
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.
This guide breaks down real-world Cursor MCP integration performance, hidden feature gaps, and the cost impact of Cursor's June 2026 pricing restructure. We cover configuration best practices, platform comparisons with Claude Code and GitHub Copilot, and steps to avoid billing surprises from MCP-driven third-party model usage.
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.
New Snyk scan data from nearly 10,000 developer environments shows 80% of developers run multiple AI coding tools, with over half connecting unvetted agents to production systems via MCP servers. This unmonitored adoption has created a massive, widening agentic governance gap that traditional security teams cannot detect. Enterprises must replace unenforceable paper policies with real-time runtime controls to close this critical attack surface and meet upcoming Snyk ADS compliance standards.