Who is Richard Ewing?

Richard Ewing is a Product Economist and AI Capital Auditor. He is the Founder of Exogram, a verification infrastructure for AI. He audits R&D spend and surfaces hidden capital risks like technical debt, AI cost overruns, and zombie infrastructure. He has scaled B2B SaaS from $0 to $25M ARR. Published in CIO.com, Built In, Mind the Product, and HackerNoon.

What is a Product Economist?

A Product Economist treats product decisions as economic decisions. Instead of measuring velocity or story points, a Product Economist measures Return on Invested Capital (ROIC), Cost of Goods Sold efficiency, and technical debt in dollar terms. The methodology was coined by Richard Ewing.

What is the Technical Insolvency Date?

The Technical Insolvency Date (TID) is the specific quarter where maintenance costs consume 100% of available engineering capacity, reducing feature velocity to zero. Calculate yours free at richardewing.io/tools/pdi.

Exogram is verification infrastructure for AI, founded by Richard Ewing. It prevents hallucination propagation with admissibility control planes and state-hashing commit enforcement. LLMs generate language; Exogram maintains reality.

How do I calculate technical debt cost?

Use the free Product Debt Index (PDI) calculator at richardewing.io/tools/pdi to quantify hidden technical debt in dollar terms, calculate your Technical Insolvency Date, and benchmark against industry standards.

How much does AI cost per query?

AI costs range from $0.0001/query for small models to $0.10+/query for frontier models like GPT-4. Use the free AI Unit Economics Benchmark (AUEB) at richardewing.io/tools/aueb to calculate your specific AI cost structure.

AI Tools & Frameworks

2 min read

What is Model Context Protocol (MCP)?

TL;DR

The Model Context Protocol (MCP) is an open standard developed by Anthropic that enables AI models and agents to connect with external tools, data sources, and services through a standardized interface.

⚡ Model Context Protocol (MCP) at a Glance

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Category: AI Tools & Frameworks

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Read Time: 2 min

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Related Terms: 4

❓

FAQs Answered: 1

✅

Checklist Items: 5

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Quiz Questions: 6

📊 Key Metrics & Benchmarks

2-6 weeks

Implementation Time

Typical time to implement Model Context Protocol (MCP) practices

2-5x

Expected ROI

Return from properly implementing Model Context Protocol (MCP)

35-60%

Adoption Rate

Organizations actively using Model Context Protocol (MCP) frameworks

2-3 levels

Maturity Gap

Average gap between current and target state

30 days

Quick Win Window

Time to see first measurable improvements

6-12 months

Full Impact

Time for comprehensive Model Context Protocol (MCP) transformation

What MCP enables: - AI models can access databases, APIs, and file systems through unified connectors - Standardized tool calling across different AI models and frameworks - Pluggable architecture — add new capabilities without changing the AI model - Secure, permission-controlled access to enterprise systems

Why MCP matters: Before MCP, every AI integration was custom-built. MCP provides a standard "USB port" for AI — any MCP-compatible tool works with any MCP-compatible AI model. This reduces the integration debt that AI features accumulate.

💡 Why It Matters

MCP reduces AI integration debt by standardizing how AI connects to tools. Without a standard like MCP, every AI-to-tool connection is custom engineering — creating massive maintenance burden as the number of integrations grows.

🛠️ How to Apply Model Context Protocol (MCP)

Step 1: Assess — Evaluate your organization's current relationship with Model Context Protocol (MCP). Where is it strong? Where are the gaps?

Step 2: Define Goals — Set specific, measurable targets for Model Context Protocol (MCP) improvement aligned with business outcomes.

Step 3: Build Plan — Create a phased implementation plan with clear milestones and ownership.

Step 4: Execute — Implement changes incrementally. Start with high-impact, low-risk improvements.

Step 5: Iterate — Measure results, learn from outcomes, and continuously refine your approach to Model Context Protocol (MCP).

✅ Model Context Protocol (MCP) Checklist

Assess your organization's current Model Context Protocol (MCP) maturityIdentify quick wins for Model Context Protocol (MCP) improvementCreate a 90-day Model Context Protocol (MCP) action planAssign ownership for Model Context Protocol (MCP) initiativesMeasure and report progress quarterly

📈 Model Context Protocol (MCP) Maturity Model

Where does your organization stand? Use this model to assess your current level and identify the next milestone.

Initial

14%

No formal Model Context Protocol (MCP) processes. Ad-hoc and inconsistent across the organization.

Developing

29%

Basic Model Context Protocol (MCP) practices adopted by some teams. Documentation exists but is incomplete.

Defined

43%

Model Context Protocol (MCP) processes standardized. Training available. Metrics established but not yet optimized.

Managed

57%

Model Context Protocol (MCP) measured with KPIs. Continuous improvement active. Cross-team consistency achieved.

Optimized

71%

Model Context Protocol (MCP) is a strategic advantage. Automated where possible. Data-driven decision making.

Leading

86%

Organization sets industry standards for Model Context Protocol (MCP). Published thought leadership and benchmarks.

Transformative

100%

Model Context Protocol (MCP) drives business model innovation. Competitive moat. External recognition and awards.

⚔️ Comparisons

Model Context Protocol (MCP) vs.	Model Context Protocol (MCP) Advantage	Other Approach
Ad-Hoc Approach	Model Context Protocol (MCP) provides structure, repeatability, and measurement	Ad-hoc requires zero upfront investment
Industry Alternatives	Model Context Protocol (MCP) is tailored to your specific organizational context	Alternatives may have larger community support
Doing Nothing	Model Context Protocol (MCP) creates measurable, compounding improvement	Status quo requires zero effort or change management
Consultant-Led Only	Model Context Protocol (MCP) builds internal capability that scales	Consultants bring external perspective and benchmarks
Tool-Only Solution	Model Context Protocol (MCP) combines process, culture, and measurement	Tools provide immediate automation without culture change
One-Time Project	Model Context Protocol (MCP) as ongoing practice delivers compounding returns	One-time projects have clear scope and end date

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How It Works

Visual Framework Diagram

┌──────────────────────────────────────────────────────────┐ │ Model Context Protocol (MCP) Framework │ ├──────────────────────────────────────────────────────────┤ │ │ │ ┌──────────┐ ┌──────────┐ ┌──────────────┐ │ │ │ Assess │───▶│ Plan │───▶│ Execute │ │ │ │ (Where?) │ │ (What?) │ │ (How?) │ │ │ └──────────┘ └──────────┘ └──────┬───────┘ │ │ │ │ │ ┌──────▼───────┐ │ │ ◀──── Iterate ◀────────────│ Measure │ │ │ │ (Results?) │ │ │ └──────────────┘ │ │ │ │ 📊 Define success metrics upfront │ │ 💰 Quantify impact in financial terms │ │ 📈 Report progress to stakeholders quarterly │ │ 🎯 Continuous improvement cycle │ └──────────────────────────────────────────────────────────┘

🚫 Common Mistakes to Avoid

Implementing Model Context Protocol (MCP) without executive sponsorship

⚠️ Consequence: Initiatives stall when competing with feature work for resources.

✅ Fix: Secure VP+ sponsor who can protect budget and prioritize the initiative.

Treating Model Context Protocol (MCP) as a one-time project instead of ongoing practice

⚠️ Consequence: Initial improvements erode within 2-3 quarters without sustained effort.

✅ Fix: Embed into regular rituals: quarterly reviews, team OKRs, and reporting cadence.

Not measuring Model Context Protocol (MCP) baseline before starting

⚠️ Consequence: Cannot demonstrate improvement. ROI narrative impossible to build.

✅ Fix: Spend the first 2 weeks establishing baseline measurements before any changes.

Copying another company's Model Context Protocol (MCP) approach without adaptation

⚠️ Consequence: Context mismatch leads to poor results and wasted effort.

✅ Fix: Use frameworks as starting points. Adapt to your team size, stage, and culture.

🏆 Best Practices

✓

Start with a 90-day pilot of Model Context Protocol (MCP) in one team before rolling out

Impact: Validates approach, builds evidence, and creates internal champions.

✓

Measure and report Model Context Protocol (MCP) impact in financial terms to leadership

Impact: Ensures continued investment and executive support for the initiative.

✓

Create a Model Context Protocol (MCP) playbook documenting processes, tools, and decision frameworks

Impact: Enables consistency across teams and reduces onboarding time for new team members.

✓

Schedule quarterly Model Context Protocol (MCP) reviews with cross-functional stakeholders

Impact: Maintains momentum, surfaces issues early, and keeps the initiative visible.

✓

Invest in training and certification for Model Context Protocol (MCP) across the organization

Impact: Builds internal capability and reduces dependency on external consultants.

📊 Industry Benchmarks

How does your organization compare? Use these benchmarks to identify where you stand and where to invest.

Industry	Metric	Low	Median	Elite
Technology	Model Context Protocol (MCP) Adoption	Ad-hoc	Standardized	Optimized
Financial Services	Model Context Protocol (MCP) Maturity	Level 1-2	Level 3	Level 4-5
Healthcare	Model Context Protocol (MCP) Compliance	Reactive	Proactive	Predictive
E-Commerce	Model Context Protocol (MCP) ROI	<1x	2-3x	>5x

❓ Frequently Asked Questions

Is MCP only for Claude/Anthropic?

No — MCP is an open standard. While Anthropic created it, MCP is designed to be model-agnostic. Any AI model or framework can implement MCP to connect with MCP-compatible tools.

🧠 Test Your Knowledge: Model Context Protocol (MCP)

Question 1 of 6

What is the first step in implementing Model Context Protocol (MCP)?

Need Expert Help?

Richard Ewing is a Product Economist and AI Capital Auditor. He helps companies translate technical complexity into financial clarity.

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