Lesson 1.1: Problem Tree Analysis

Model Context Protocol (MCP)

The four-block framework for focused, credible AI prompts.

The Four-Block MCP Structure

Block 1: System Context

Block 2: Knowledge Context

Block 3: Task Context

Block 4: Final Prompt

How MCP Blocks Flow Together 

graph TD
    %% INPUT BLOCKS
    B1["📋 BLOCK 1: System Context<br/>Define the AI's Role<br/>• Evidence-focused<br/>• Neutral & transparent<br/>• Cite sources"]
    B2["🧠 BLOCK 2: Knowledge Context<br/>Share What You Know<br/>• Draft problem statement<br/>• Geographic scope<br/>• Existing insights"]
    B3["🎯 BLOCK 3: Task Context<br/>Define Your Objectives<br/>• Problem Tree structure<br/>• Indicator suggestions<br/>• Reading list<br/>• Uncertainties"]
    B4["💬 BLOCK 4: Final Prompt<br/>Clear Instruction<br/>Tie everything together<br/>Request specific outputs"]

    %% PROCESSING
    PROCESS["🤖 AI PROCESSING<br/>Structured Analysis"]

    %% OUTPUT CATEGORIES
    OUT1["📊 Preliminary<br/>Problem Tree"]
    OUT2["📈 Indicator<br/>Suggestions"]
    OUT3["📚 Reading List<br/>with Citations"]
    OUT4["❓ Uncertainties &<br/>Assumptions"]
    OUT5["💡 Stakeholder<br/>Questions"]

    %% Flow relationships
    B1 --> PROCESS
    B2 --> PROCESS
    B3 --> PROCESS
    B4 --> PROCESS

    PROCESS --> OUT1
    PROCESS --> OUT2
    PROCESS --> OUT3
    PROCESS --> OUT4
    PROCESS --> OUT5

    %% Festa Design System Colors
    style B1 fill:#F59E0B,stroke:#D97706,stroke-width:2px,color:#1F2937
    style B2 fill:#F59E0B,stroke:#D97706,stroke-width:2px,color:#1F2937
    style B3 fill:#F59E0B,stroke:#D97706,stroke-width:2px,color:#1F2937
    style B4 fill:#F59E0B,stroke:#D97706,stroke-width:2px,color:#1F2937
    style PROCESS fill:#10B981,stroke:#059669,stroke-width:3px,color:#fff
    style OUT1 fill:#72B043,stroke:#5A8F36,stroke-width:2px,color:#fff
    style OUT2 fill:#72B043,stroke:#5A8F36,stroke-width:2px,color:#fff
    style OUT3 fill:#72B043,stroke:#5A8F36,stroke-width:2px,color:#fff
    style OUT4 fill:#72B043,stroke:#5A8F36,stroke-width:2px,color:#fff
    style OUT5 fill:#72B043,stroke:#5A8F36,stroke-width:2px,color:#fff

Four inputs, five outputs.

Block 1: System Context

Block 1 - System Context 
You are an evidence-focused research assistant for nonprofits and social enterprises.

Behaviors: Be neutral, transparent, and concise. Always cite publisher + year for sources.
Prefer reputable sources (UN agencies, government statistics, peer-reviewed research,
established NGOs). Clearly separate facts from assumptions. Flag uncertainties and
potential bias in sources.

Block 2: Knowledge Context

Block 2 - Knowledge Context 
Draft core problem: [Your 1-2 sentence problem statement]
Geographic/population scope: [Location, demographic details if relevant]

What we already know:
• [Existing insight 1 with source if you have it]
• [Existing insight 2]
• [Existing insight 3]

Keywords and related terms: [List of relevant terms, synonyms, related concepts]
Example - Knowledge Context 
Draft core problem: Young adults aged 18-25 in rural Kenya have limited access to
decent employment opportunities.

Geographic/population scope: Rural areas of Nyanza region, Kenya. Youth 18-25 years old,
mixed gender.

What we already know:
• National youth unemployment rate ~20% (Kenya National Bureau of Statistics, 2022)
• Agriculture is declining as primary livelihood
• Some anecdotal evidence of skills-job mismatch

Keywords: youth unemployment, rural livelihoods, skills gap, Kenya Nyanza,
agricultural transition, informal sector

Block 3: Task Context

Block 3 - Task Context 
Research objectives:

1) Create a preliminary Problem Tree: core problem statement; 2-3 levels of root causes;
   key effects/consequences

2) Suggest measurable indicators for each major cause and effect (indicator name • unit
   of measurement • typical data sources)

3) Provide 5-10 credible sources for deeper reading (publisher • year • link if available)

4) Identify uncertainties, knowledge gaps, and assumptions that need stakeholder validation

5) Draft 10 targeted questions for stakeholder interviews/focus groups

Block 4: Final Prompt

Block 4 - Final Prompt 
Using all the context provided above, generate:

- **Preliminary Problem Tree** in clear markdown format
- **Indicator suggestions** in table format
- **Recommended reading list** with full citations
- **List of uncertainties and assumptions** requiring validation
- **10 stakeholder validation questions** that are open-ended and non-leading

Complete MCP Template

Complete MCP Template - Ready to Use 
## SYSTEM CONTEXT
You are an evidence-focused research assistant for nonprofits and social enterprises.
Behaviors: neutral, transparent, concise. Cite publisher + year. Prefer reputable sources
(UN agencies, government statistics, multilaterals, peer-reviewed). Separate facts from
assumptions. Flag uncertainties and potential bias.

## KNOWLEDGE CONTEXT
Draft core problem: {{Insert your problem statement}}
Scope/Context: {{Geography, population, timeframe}}
What we already know:
• {{Existing knowledge point 1}}
• {{Existing knowledge point 2}}
• {{Existing knowledge point 3}}
Keywords/aliases: {{Related terms}}

## TASK CONTEXT
Objectives:
1) Propose a Preliminary Problem Tree: core problem; 2-3 levels of root causes; key effects
2) Suggest common indicators that evidence each cause/effect (name • unit • typical sources)
3) Provide 5-10 credible sources to read next (publisher • year • link if available)
4) List uncertainties/gaps and assumptions that need field validation
5) Draft 10 stakeholder research questions to validate and deepen understanding

## PROMPT
Using the contexts above, produce:
- A **Preliminary Problem Tree** in markdown bullets
- A table of **indicators** (Indicator • What it measures • Possible sources)
- A **Reading list** (publisher • year • link if available)
- **Uncertainties & assumptions** (bullets)
- **10 stakeholder questions**

Quality Assurance for AI Outputs

Verify every output before it enters your problem tree.

Source credibility
Check whether sources are reputable, recent enough, and accurately described.
Context fit
Confirm the findings match your geography, population, culture, and economic context.
Evidence clarity
Separate supported claims from assumptions and flag what needs validation. 
graph TD
    %% Start
    START["Receive AI Output<br/>from MCP Prompt"]

    %% CHECKPOINT 1: Source Credibility
    CHECK1{"Source Credibility<br/>Check"}
    Q1A["Are sources reputable?<br/>UN, gov stats,<br/>peer-reviewed, NGOs"]
    Q1B["Are they recent<br/>enough for context?"]
    Q1C["Do links work and<br/>match descriptions?"]
    FAIL1["⚠️ Flag Issues<br/>Request new sources<br/>or verify manually"]

    %% CHECKPOINT 2: Context Fit
    CHECK2{"Context Fit<br/>Assessment"}
    Q2A["Do findings match<br/>your geography/<br/>population?"]
    Q2B["Are cultural & economic<br/>contexts appropriate?"]
    Q2C["Any obvious<br/>contradictions?"]
    FAIL2["⚠️ Flag Mismatches<br/>Adjust MCP prompt<br/>or seek local sources"]

    %% CHECKPOINT 3: Evidence Clarity
    CHECK3{"Evidence vs<br/>Assumption Check"}
    Q3A["Are claims<br/>properly supported?"]
    Q3B["Are limitations<br/>acknowledged?"]
    Q3C["Is bias potential<br/>noted?"]
    FAIL3["⚠️ Tag Assumptions<br/>Mark for stakeholder<br/>validation"]

    %% Success Path
    SUCCESS["✅ Verified Output<br/>Tag evidence (E)<br/>Tag assumptions (A)<br/>Build Problem Tree"]

    %% Relationships
    START --> CHECK1
    CHECK1 -->|Review| Q1A
    Q1A -->|Pass| Q1B
    Q1B -->|Pass| Q1C
    Q1C -->|Pass| CHECK2
    Q1A -->|Fail| FAIL1
    Q1B -->|Fail| FAIL1
    Q1C -->|Fail| FAIL1
    FAIL1 --> START

    CHECK2 -->|Review| Q2A
    Q2A -->|Pass| Q2B
    Q2B -->|Pass| Q2C
    Q2C -->|Pass| CHECK3
    Q2A -->|Fail| FAIL2
    Q2B -->|Fail| FAIL2
    Q2C -->|Fail| FAIL2
    FAIL2 --> START

    CHECK3 -->|Review| Q3A
    Q3A -->|Pass| Q3B
    Q3B -->|Pass| Q3C
    Q3C -->|Pass| SUCCESS
    Q3A -->|Concerns| FAIL3
    Q3B -->|Concerns| FAIL3
    Q3C -->|Concerns| FAIL3
    FAIL3 --> SUCCESS

    %% Festa Design System Colors
    %% Start - Neutral
    style START fill:#6B7280,stroke:#4B5563,stroke-width:2px,color:#fff

    %% Checkpoints - Pot of Gold (decision points)
    style CHECK1 fill:#F59E0B,stroke:#D97706,stroke-width:2px,color:#1F2937
    style CHECK2 fill:#F59E0B,stroke:#D97706,stroke-width:2px,color:#1F2937
    style CHECK3 fill:#F59E0B,stroke:#D97706,stroke-width:2px,color:#1F2937

    %% Questions - Leaf (evaluation criteria)
    style Q1A fill:#72B043,stroke:#5A8F36,stroke-width:1px,color:#fff
    style Q1B fill:#72B043,stroke:#5A8F36,stroke-width:1px,color:#fff
    style Q1C fill:#72B043,stroke:#5A8F36,stroke-width:1px,color:#fff
    style Q2A fill:#72B043,stroke:#5A8F36,stroke-width:1px,color:#fff
    style Q2B fill:#72B043,stroke:#5A8F36,stroke-width:1px,color:#fff
    style Q2C fill:#72B043,stroke:#5A8F36,stroke-width:1px,color:#fff
    style Q3A fill:#72B043,stroke:#5A8F36,stroke-width:1px,color:#fff
    style Q3B fill:#72B043,stroke:#5A8F36,stroke-width:1px,color:#fff
    style Q3C fill:#72B043,stroke:#5A8F36,stroke-width:1px,color:#fff

    %% Fail paths - Chicken Comb (issues to address)
    style FAIL1 fill:#E12729,stroke:#B91C1C,stroke-width:2px,color:#fff
    style FAIL2 fill:#E12729,stroke:#B91C1C,stroke-width:2px,color:#fff
    style FAIL3 fill:#FCD34D,stroke:#F59E0B,stroke-width:2px,color:#1F2937

    %% Success - Pepper Green (validated output)
    style SUCCESS fill:#10B981,stroke:#059669,stroke-width:3px,color:#fff
Lesson 1.1: Problem Tree Analysis 55%
Step 6 of 11 · Model Context Protocol