André J eonist

Is MCP the future of AI. Bear VS Bull Case

MCP: The Protocol That's Quietly Rewiring How AI Systems Connect

The pretext is simple: we're witnessing the second wave of AI

The first wave was AI wrappers—brilliant but isolated islands of intelligence. Companies like Perplexity, Cursor, and Replit built impressive tools that essentially put a beautiful interface on top of someone else's LLM[1][2][3]. These AI wrappers were initially dismissed as "just an API call with a prompt"[2], but they quietly became multi-billion dollar businesses while the tech world obsessed over foundation models.

Now we're entering something fundamentally different. **The second wave isn't

Lets write a substack post on this headline "Is MCP the future of AI. Bear VS Bull Case".
The pretex is that MCP is a fringe, but fast growing technology that man AI companies now has in their roadmaps
Agentic coding, agentic workflows are bidded to become the next evolution in AI.
Comanies like Superhuman are merging with companies like grammarly to form new eco system of agentic office tools.
MCP is positioned to be the glue between agentic usage, be it Agentic flows or agent to agent systems.
Are we peak what LLMs can achive, and the rest is just iimplementation with agentic flows and systems.
Is MCP the path to AGI? and autonomouse robotics?
Or is MCP simply just a hype, a foot note in history, important building block like TCP or https. But in the end just a cog in the system?
lets keep the aricle easy to read and high level, thinking broad strokes, but also providing concreet interesting insights and anologies.
This aricle should spark FOMO, Emotional punch, and is very hot topi

Evaluating the Future of MCP: Do These Concerns Have Merit?

Your concerns about MCP's potential decline are well-founded and reflect real challenges the protocol faces. Let me analyze each point based on current industry trends and adoption patterns.

1. RAG Prioritization for Internal Knowledge Bases

This concern has significant merit. The relationship between RAG and MCP is more complex than simple replacement, and enterprise preferences are already showing interesting patterns.

Current Enterprise Preferences

Unique Selling Points: MCP Observability Solutions Comparison

The three MCP (Model Context Protocol) observability solutions each offer distinct approaches to monitoring and observability, targeting different user needs and technical requirements.

SigNoz MCP Observability with OpenTelemetry

Open Standards & Vendor Neutrality

SigNoz's primary differentiator is its commitment to open standards and vendor-neutral observability[1]. By leveraging OpenTelemetry (OTel), it ensures that organizations aren't locked into proprietary solutions and can maintain full ownership of their telemetry data[1].

Enterprise-Grade Distributed Tracing

Analysis of MCP-Related Business Ideas: Market Position and Competitive Landscape

Based on market research and competitive analysis, here's an evaluation of the four proposed ideas considering product positioning, market evolution, and incumbent behavior.

Market Context and Growth Trends

The AI observability market is experiencing explosive growth, valued at $1.4 billion in 2023 and projected to reach $10.7 billion by 2033 with a CAGR of 25.47%[1][2]. Meanwhile, feature flag adoption is nearly universal, with 95% of organizations having implemented, begun implementing, or planning to implement feature flags[3]. The continuous compliance market is also expanding rapidly, driven by increasing regulatory complexity and the shift from periodic to real-time monitoring[4][5].

Idea Analysis

I'll summarize the key findings from these four research papers on AI agent security and authentication:

Authenticated Delegation and Authorized AI Agents

The first paper introduces a comprehensive framework for securely delegating authority to AI agents while maintaining accountability. The researchers propose extending existing authentication protocols like OAuth 2.0 and OpenID Connect to support AI agents acting on behalf of human users[1].

Key Contributions:

A novel framework for authenticated, authorized, and auditable delegation of authority to AI agents
Extension of established web authentication protocols to include agent-specific credentials and metadata
A system for translating natural language permissions into structured, auditable access control configurations

Claude's Max plan has several types of usage limits designed to provide substantially higher capacity than the Pro plan while maintaining fair access for all users.

Message Limits by Tier

The Max plan offers two usage tiers with different message allowances[1][2]:

Expanded Usage (5x Pro): At least 225 messages every 5 hours
Maximum Flexibility (20x Pro): At least 900 messages every 5 hours

For context, Pro users typically send around 45 messages every 5 hours, making the Max plan a significant upgrade for heavy users[4].

Analyzing LaunchDarkly Use Cases for the MCP Space: Opportunities, Pros & Cons, and Competitor Landscape

Intersection of LaunchDarkly and MCP

The intersection of LaunchDarkly—a leading feature flag and experimentation platform—and the MCP (Multi-Channel Platform/Management Control Platform) space offers significant opportunities for organizations seeking fine-grained, real-time control over feature releases, experimentation, and AI-driven operations across complex, distributed environments.

Key Use Cases in the MCP Space

Dynamic Feature Management: Instantly enable, disable, or modify features across multiple channels or environments without redeploying code, supporting real-time operational agility[1][2][3].
AI Model and Prompt Experimentation: Roll out, A/B test, and optimize AI models or prompts for different user segments or channels, with the ability to quickly revert changes if issues arise[4][5].

Cursor faces a challenging competitive landscape as agentic coding assistants become increasingly commoditized, with model access, token price, and raw API call volume emerging as primary differentiators. Your observation is accurate: when tools like Claude Code and Gemini CLI offer dramatically higher premium call quotas at lower prices, and the user experience converges around a chat/CLI interface, Cursor’s long-term differentiation is at risk if it remains a thin wrapper around third-party models[1][2].

Current Position and Risks

Cursor’s main strengths today are its deep IDE integration (as a fork of VS Code), real-time code generation, project-wide context, and support for multiple models[1][3].
However, its context window (~10k tokens) is much smaller than Gemini CLI’s (1M, soon 2M), and its premium call quotas are lower and more expensive than Claude Code’s[1].
The core risk: If model providers (OpenAI, Anthropic, Google) keep increasing context windows, lowering prices, and

	Yes, it is possible to use a custom domain with Gmail for free, though it requires some setup and has certain limitations. There are several methods to achieve this, each with different requirements and trade-offs.

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	### Method 1: Email Forwarding + SMTP Service

	This is the most popular free approach that combines email forwarding with a free SMTP service[1][2]. Here's what you need:

	- A custom domain name
	- A free email forwarding service (like ImprovMX or Cloudflare Email Routing)