# MCP Integration Architecture: Building a World-Class CTO Co-Pilot

**Version:** 0.8.0
**Last Updated:** 2025-01-27

This guide explains how Sensei MCP integrates with other MCP servers to create a comprehensive CTO co-pilot system with human-LLM collaboration at its core.

---

## 🎯 Vision: Human-LLM Partnership

### The Killer Insight

**Human provides:**
- Domain expertise
- Judgment and context
- Business constraints
- Strategic direction

**LLM provides:**
- Synthesis across 64 expert personas
- Pattern matching against 32,000 lines of wisdom
- Consistency checking across decisions
- Real-time intelligence from multiple sources

**Together:**
- CTO-level decisions at code-writing speed
- Multi-perspective analysis with no weak links
- Context-aware recommendations with current data
- Session continuity across conversations

---

## 🏗️ Integration Architecture

```
┌─────────────────────────────────────────────────────────────────┐
│                        Claude Code (LLM Interface)              │
└────────────────────────────┬────────────────────────────────────┘
                             │
        ┌────────────────────┴────────────────────┐
        │                                         │
        ▼                                         ▼
┌───────────────────┐                  ┌──────────────────────┐
│   Sensei MCP      │◄─────────────────┤  External MCP Servers│
│ (Decision Engine) │                  └──────────────────────┘
└───────────────────┘                           │
        │                                       │
        ├─ 64 Personas (500+ lines each)       ├─ Context7 MCP
        ├─ Session Memory                      ├─ Tavily MCP
        ├─ Multi-Persona Orchestration         ├─ Playwright MCP
        ├─ Analytics & Insights                ├─ OpenMemory MCP
        └─ Consultation Recording              ├─ GitHub MCP
                                               └─ Sequential Thinking MCP
```

---

## 🌟 Why 100% EXCELLENT Tier Matters

### The Compound Effect in Multi-Persona Synthesis

When Claude consults 3-5 personas for a decision:

**With 90% EXCELLENT (6 shallow personas):**
- Pragmatic Architect: 500 lines ✅ (deep analysis)
- Site Reliability Engineer: 668 lines ✅ (deep analysis)
- FinOps Optimizer: 828 lines ✅ (deep analysis)
- Cloud Architect: 442 lines ❌ (shallow, missing cost patterns)
- Backend Engineer: 430 lines ❌ (shallow, missing distributed systems depth)
- DevEx Champion: 423 lines ❌ (shallow, missing DORA metrics depth)

**Result:** Strong on architecture, weak on cloud/backend/DevEx nuances

**With 100% EXCELLENT (all 64 at 500+ lines):**
- **ALL** personas: 500+ lines ✅ (comprehensive depth)

**Result:** World-class CTO council with **no weak links**

---

## 📋 MCP Integration Tiers

### Tier 1: Essential for CTO Co-Pilot (Integrate First)

#### 1. Context7 MCP (Library/Framework Documentation)

**Why:** CTOs work across many tech stacks (React, FastAPI, PostgreSQL, Kubernetes)

**Integration:** When a persona suggests a library, fetch latest docs via Context7

**Example Workflow:**
```
User: "Review our FastAPI authentication implementation"

1. Sensei suggests: [security-sentinel, api-platform-engineer, privacy-engineer]
2. Context7 fetches:
   - /pydantic/pydantic (data validation)
   - /tiangolo/fastapi (framework docs)
   - /python-jose/python-jose (JWT handling)
3. Claude synthesizes:
   - Security Sentinel perspective (OWASP best practices)
   - API Platform Engineer perspective (REST/OAuth2 patterns)
   - Privacy Engineer perspective (GDPR compliance)
   - Current FastAPI docs (from Context7)
```

**ROI:** Always current with framework best practices (not just training data)

**Setup:**
```json
{
  "mcpServers": {
    "sensei": {
      "command": "uvx",
      "args": ["sensei-mcp"]
    },
    "context7": {
      "command": "npx",
      "args": ["-y", "@upstash/context7-mcp"]
    }
  }
}
```

---

#### 2. Tavily MCP (Web Search & Intelligence)

**Why:** Real-time context (CVEs, latest cloud pricing, recent incidents)

**Integration:** Fetch current data before making recommendations

**Example Workflow:**
```
User: "Should we use Log4j in our new Java microservice?"

1. Sensei suggests: [security-sentinel, backend-distributed-systems-engineer]
2. Tavily searches: "Log4j vulnerabilities 2025" + "Log4j alternatives"
3. Claude synthesizes:
   - Security Sentinel: CVE history, current threat landscape
   - Backend Engineer: Alternative logging frameworks (Logback, SLF4J)
   - Recent security advisories (from Tavily)
```

**ROI:** Decisions based on current data, not outdated training

**Setup:**
```json
{
  "mcpServers": {
    "sensei": {
      "command": "uvx",
      "args": ["sensei-mcp"]
    },
    "tavily": {
      "command": "npx",
      "args": ["-y", "@tavily/mcp-server"],
      "env": {
        "TAVILY_API_KEY": "your-api-key"
      }
    }
  }
}
```

---

#### 3. Chrome DevTools / Playwright MCP (Live System Inspection)

**Why:** Debugging production issues, performance analysis, UX validation

**Integration:** Inspect live systems for real diagnostics

**Example Workflow:**
```
User: "Why is our checkout page slow?"

1. Sensei suggests: [performance-engineer, frontend-ux-specialist]
2. Playwright navigates to checkout page
3. Chrome DevTools captures:
   - Network waterfall
   - JavaScript execution time
   - Layout shifts (CLS)
   - Largest Contentful Paint (LCP)
4. Claude synthesizes:
   - Performance Engineer: Bottleneck analysis, optimization recommendations
   - Frontend UX Specialist: UX impact, perceived performance
   - Real metrics (from DevTools)
```

**ROI:** Diagnose real issues, not hypothetical ones

**Setup:**
```json
{
  "mcpServers": {
    "sensei": {
      "command": "uvx",
      "args": ["sensei-mcp"]
    },
    "playwright": {
      "command": "npx",
      "args": ["-y", "@playwright/mcp-server"]
    }
  }
}
```

---

### Tier 2: High Value for Collaboration (Integrate Second)

#### 4. OpenMemory MCP (Long-Term Context Across Sessions)

**Why:** Sensei's session memory is per-project. OpenMemory spans ALL projects.

**Integration:** "Remember this pattern across all my projects"

**Example Workflow:**
```
User: "Always use PostgreSQL RLS for multi-tenancy"

1. Sensei records in project session
2. OpenMemory stores as global preference
3. Future projects automatically:
   - Apply RLS pattern
   - Flag non-RLS designs
   - Reference past decisions
```

**ROI:** CTO-level patterns persist across entire portfolio

---

#### 5. GitHub MCP (Pull Request Context)

**Why:** Code review at CTO level requires PR context, team discussions

**Integration:** Fetch PR diff, comments, CI status → Sensei personas analyze

**Example Workflow:**
```
User: "Review PR #123 for architecture consistency"

1. GitHub MCP fetches:
   - PR diff (files changed)
   - Comments and discussions
   - CI/CD status
   - Linked issues
2. Sensei suggests: [pragmatic-architect, security-sentinel, devex-champion]
3. Claude synthesizes:
   - Architecture consistency check
   - Security review
   - DevEx impact (build time, test coverage)
   - Team discussion context (from GitHub)
```

**ROI:** Automated architectural review of team PRs

---

### Tier 3: Advanced Capabilities (Future Integration)

#### 6. Sequential Thinking MCP (Complex Multi-Step Reasoning)

**Why:** Architecture decisions require chain-of-thought reasoning

**Integration:** Pragmatic Architect uses sequential thinking for complex trade-offs

**Example Workflow:**
```
User: "Should we migrate from monolith to microservices?"

1. Sensei suggests: [pragmatic-architect, site-reliability-engineer, finops-optimizer]
2. Sequential Thinking enables:
   - Multi-step analysis with revision
   - Hypothesis generation and testing
   - Branch exploration (migrate vs. modular monolith)
3. Claude synthesizes:
   - Architectural trade-offs (from Pragmatic Architect)
   - Operational complexity (from SRE)
   - Cost impact (from FinOps)
   - Chain-of-thought reasoning (from Sequential Thinking)
```

**ROI:** Higher quality architectural recommendations

---

## 🔄 Example: Multi-MCP Synthesis Workflow

### Scenario: Security Review of Authentication Implementation

**User Query:** "Review our authentication implementation for security issues"

**Step 1: Persona Selection**
```python
# Sensei MCP
suggest_personas_for_query(
  query="Review our authentication implementation for security issues",
  max_suggestions=5
)
# Returns: ["security-sentinel", "api-platform-engineer", "privacy-engineer"]
```

**Step 2: Fetch Persona Content**
```python
# Sensei MCP
get_persona_content(persona_name="security-sentinel")  # 813 lines
get_persona_content(persona_name="api-platform-engineer")  # 760 lines
get_persona_content(persona_name="privacy-engineer")  # 500 lines
# Total: 2,073 lines of security/API/privacy expertise
```

**Step 3: Fetch Current Documentation**
```python
# Context7 MCP
get_library_docs(context7CompatibleLibraryID="/owasp/asvs")
get_library_docs(context7CompatibleLibraryID="/ietf-wg-oauth/oauth")
# Returns: Current OAuth 2.0 best practices, OWASP ASVS guidelines
```

**Step 4: Check Recent Vulnerabilities**
```python
# Tavily MCP
tavily_search(query="OAuth authentication vulnerabilities 2025")
tavily_search(query="JWT security best practices 2025")
# Returns: Latest CVEs, security advisories, current threat landscape
```

**Step 5: Inspect Live Implementation (Optional)**
```python
# Playwright MCP
browser_navigate(url="https://app.example.com/login")
browser_snapshot()  # Capture login flow
browser_network_requests()  # Check auth headers, cookies
# Returns: Real network traffic, session handling, CSRF tokens
```

**Step 6: Synthesize**

Claude now has:
- **Deep Expertise**: 2,073 lines from 3 personas
- **Current Best Practices**: OWASP ASVS + OAuth 2.0 docs (Context7)
- **Recent Threat Intelligence**: 2025 CVEs and vulnerabilities (Tavily)
- **Live System Behavior**: Network traffic, session handling (Playwright)
- **Session Continuity**: Past decisions, constraints (Sensei memory)

**Claude's Response:**
```markdown
## Security Review: Authentication Implementation

### 🔴 Critical Issues (Fix Immediately)

1. **JWT Secret Rotation** (Security Sentinel + Tavily CVE-2025-XXXX)
   - Current: Hardcoded secret in environment variable
   - Risk: If compromised, all tokens are valid forever
   - Fix: Implement secret rotation (monthly) + key versioning
   - Reference: OWASP ASVS 2.9.3 (from Context7)

2. **Missing CSRF Protection** (API Platform Engineer + Playwright inspection)
   - Current: No CSRF tokens in login flow (detected via live inspection)
   - Risk: Session fixation attacks
   - Fix: Implement SameSite cookies + CSRF tokens
   - Reference: OAuth 2.0 Security BCP (from Context7)

### 🟡 Medium Priority (Address This Sprint)

3. **Password Storage** (Security Sentinel + Privacy Engineer)
   - Current: bcrypt with cost factor 10
   - Recommendation: Upgrade to Argon2id (winner of Password Hashing Competition)
   - GDPR Impact: Better protection aligns with Article 32 requirements
   - Reference: OWASP Password Storage Cheat Sheet (from Context7)

4. **Session Timeout** (Privacy Engineer + live testing)
   - Current: 7-day expiry (detected via network inspection)
   - Risk: Excessive for financial application
   - Fix: Reduce to 1-day absolute, 30-min idle timeout
   - Reference: PCI-DSS 8.1.8 requirements

### ✅ Good Practices (Keep Doing)

5. **HTTPS Everywhere** ✅
6. **Rate Limiting on /login** ✅ (100 req/min detected)
7. **Email Verification** ✅

### 📊 Implementation Priority

1. Week 1: JWT rotation (#1) + CSRF tokens (#2)
2. Week 2: Argon2id migration (#3)
3. Week 3: Session timeout (#4)

### 🎯 Success Metrics

- Zero auth-related CVEs after fixes
- <100ms auth latency (current: 87ms ✅)
- 99.99% uptime for auth service
```

**Step 7: Record Consultation**
```python
# Sensei MCP
record_consultation(
  query="Review our authentication implementation for security issues",
  personas_used=["security-sentinel", "api-platform-engineer", "privacy-engineer"],
  synthesis="[Claude's complete analysis above]"
)
# Session now remembers: JWT rotation decision, CSRF requirement, Argon2id preference
```

---

## 🎯 Success Metrics

### Quantitative
- ✅ **100% EXCELLENT tier**: 64/64 personas at 500+ lines
- ✅ **Token efficiency**: 87.5% reduction (loads 5-15% of rulebook)
- ✅ **Session continuity**: Zero re-litigation of decisions
- 🎯 **Multi-MCP synthesis**: 3+ MCP servers working together
- 🎯 **Analytics**: Track persona effectiveness across team

### Qualitative
- ✅ **Transparency**: All 64 personas are plain markdown (32,000 lines readable)
- ✅ **No vendor lock-in**: Works with any MCP client
- ✅ **Granular & iterative**: Each step observable, debuggable, improvable
- 🎯 **Real-time intelligence**: Current docs, recent CVEs, live diagnostics
- 🎯 **Human-LLM partnership**: Mutual leverage, not automation

---

## 📚 Integration Guides

**✅ Comprehensive Integration Guides Now Available!**

We've created detailed integration guides for all Tier 1 MCP servers:

### 📖 Available Guides

1. **[Context7 Integration Guide](./integrations/CONTEXT7.md)**
   - Up-to-date library and framework documentation
   - 3 example workflows (security review, framework upgrades, library comparison)
   - Troubleshooting and best practices
   - Cost: Free

2. **[Tavily Integration Guide](./integrations/TAVILY.md)**
   - Real-time web search and intelligence gathering
   - 4 example workflows (CVE lookup, cost analysis, tech due diligence, incident intelligence)
   - Cost management and optimization strategies
   - Cost: $0.005-0.01/search (1,000 free/month)

3. **[Playwright Integration Guide](./integrations/PLAYWRIGHT.md)**
   - Live system inspection and performance analysis
   - 4 example workflows (performance debugging, UI/UX inspection, security audits, accessibility)
   - Core Web Vitals measurement and optimization
   - Cost: Free (requires browser install)

4. **[Integration Index](./integrations/README.md)**
   - Quick start for all integrations (10 minutes)
   - Multi-MCP workflow patterns
   - Success metrics and best practices
   - Common troubleshooting

### 🚀 Quick Start: Your First Integration (5 Minutes)

**Option 1: Context7 (Recommended for First Integration)**

```bash
# Install
npx -y @upstash/context7-mcp

# Configure Claude Code
claude mcp add context7 -- npx -y @upstash/context7-mcp

# Test
# Ask: "Explain the latest React 19 hooks"
# Expected: Frontend expert + React 19 current docs
```

**Option 2: All Three at Once (15 Minutes)**

See [Integration Index Quick Start](./integrations/README.md#quick-start-your-first-multi-mcp-workflow)

---

## 🚀 Roadmap

### ✅ Phase 1: 100% EXCELLENT Tier (COMPLETE)
- All 64 personas at 500+ lines
- Synced to sensei-mcp v0.8.0
- Multi-persona orchestration working

### ✅ Phase 2: Tier 1 MCP Integrations (COMPLETE)
- ✅ Context7 integration guide ([docs/integrations/CONTEXT7.md](./integrations/CONTEXT7.md))
- ✅ Tavily integration guide ([docs/integrations/TAVILY.md](./integrations/TAVILY.md))
- ✅ Playwright integration guide ([docs/integrations/PLAYWRIGHT.md](./integrations/PLAYWRIGHT.md))
- ✅ Integration index with multi-MCP patterns ([docs/integrations/README.md](./integrations/README.md))
- ✅ 11 example workflows documented (3 Context7, 4 Tavily, 4 Playwright)
- ✅ Troubleshooting guides for each integration
- ✅ Cost management strategies (Tavily)
- 🎯 **Next:** Multi-MCP orchestration layer (suggest_mcps_for_query tool)
- 🎯 **Next:** Executable auth security review demo

### 📋 Phase 3: Tier 2 MCP Integrations (Week 2)
- OpenMemory integration
- GitHub MCP integration
- Advanced workflow examples

### 🔮 Phase 4: Advanced Capabilities (Future)
- Sequential Thinking MCP
- Database MCP for live schema inspection
- Custom MCP server template for domain-specific tools

---

## 💡 Best Practices

### 1. Start Simple
- Begin with Sensei MCP alone
- Add Context7 for current docs
- Gradually add more MCP servers as needed

### 2. Observe & Measure
- Use `get_session_insights()` to track persona effectiveness
- Monitor which MCP combinations work best
- Iterate based on team feedback

### 3. Session Memory is Key
- Always use `session_id` for project continuity
- Record decisions with `record_decision()`
- Export summaries with `export_session_summary()` for team sharing

### 4. Multi-Persona Synthesis
- Use `orchestrated` mode for complex decisions (2-5 personas)
- Use `quick` mode for fast answers (just Snarky Senior Engineer)
- Use `crisis` mode for emergencies (Incident Commander + SRE + Executive Liaison)

### 5. Trust the Process
- Let Sensei suggest personas (it's smart)
- Review suggestions before proceeding
- Combine with your domain expertise for best results

---

## 🤝 Contributing

Have ideas for new MCP integrations? Found a great workflow?

1. Open an issue: https://github.com/amarodeabreu/sensei-mcp/issues
2. Share your workflow in Discussions
3. Contribute integration guides via PR

---

**Made with 🥋 by the Sensei MCP community**

*Building a world-class CTO co-pilot, one persona at a time.*
