WIP. Don't merge: Review Article and Create Terraphim AI Spec

CODE_EXECUTION_MCP_SUMMARY.md

@@ -0,0 +1,353 @@
+# Code Execution with MCP - Project Summary
+
+**Date:** 2025-11-15
+**Status:** Ready for Review
+**Implementation Timeline:** 12 weeks (3 phases)
+
+## Quick Links
+
+- [Technical Specification](./CODE_EXECUTION_WITH_MCP_SPEC.md) - Full architectural design
+- [Gap Analysis](./CODE_EXECUTION_MCP_GAP_ANALYSIS.md) - Current capabilities vs. requirements
+- [Implementation Plan](./CODE_EXECUTION_MCP_IMPLEMENTATION_PLAN.md) - Detailed 12-week roadmap
+
+## Executive Summary
+
+This project implements Anthropic's "Code Execution with MCP" approach in Terraphim AI, achieving:
+- **98% token reduction** (150K → 2K tokens for complex workflows)
+- **Faster execution** (sub-2 second response times)
+- **Unlimited tool scaling** (support 100+ tools without degradation)
+- **Enhanced privacy** (data processing in sandbox, not context)
+
+## The Problem
+
+Traditional AI agent workflows consume massive amounts of tokens:
+1. **Load all tool definitions** upfront → 10K-20K tokens
+2. **Every tool call** passes results through context → 5K-50K tokens each
+3. **Chain multiple calls** → 150K+ tokens total
+
+This creates:
+- ❌ High API costs
+- ❌ Increased latency
+- ❌ Context window limits
+- ❌ Impossible to scale to many tools
+
+## The Solution
+
+**Treat MCP servers as code APIs** instead of direct tool calls:
+
+```typescript
+// Instead of: Multiple separate tool calls through context
+// Result: Tool def (1K) + Call 1 (8K) + Call 2 (5K) + Call 3 (10K) = 24K tokens
+
+// Do this: Write code that uses tools programmatically
+import { terraphim } from 'mcp-servers';
+
+async function analyzeDocuments() {
+  const docs = await terraphim.search({ query: "rust async", limit: 100 });
+  const relevant = docs.filter(d => d.rank > 0.8);
+  return { count: relevant.length, top: relevant[0] };
+}
+// Result: Code (500) + Final result (500) = 1K tokens
+```
+
+**Benefits:**
+- ✅ 98% token reduction
+- ✅ Faster execution (parallel processing in code)
+- ✅ Better privacy (data stays in sandbox)
+- ✅ Unlimited tools (load only what's needed)
+- ✅ Reusable skills (save successful patterns)
+
+## Can Terraphim AI Do This Today?
+
+### Current Capabilities ✅
+
+**YES - Terraphim AI has most infrastructure:**
+
+1. **✅ Secure Code Execution**
+   - Firecracker VMs operational
+   - Sub-2 second boot times
+   - Python, JavaScript, Bash, Rust support
+   - Location: `crates/terraphim_multi_agent/src/vm_execution/`
+
+2. **✅ MCP Server**
+   - 17 tools available
+   - Search, autocomplete, analysis
+   - Location: `crates/terraphim_mcp_server/`
+
+3. **✅ Agent System**
+   - Multi-agent coordination
+   - Lifecycle management
+   - Location: `crates/terraphim_agent_supervisor/`, `crates/terraphim_multi_agent/`
+
+4. **✅ State Persistence**
+   - Multiple storage backends
+   - Location: `crates/terraphim_persistence/`
+
+### Missing Capabilities ❌
+
+**NO - Three critical components needed:**
+
+1. **❌ MCP Code APIs** (Critical)
+   - MCP tools not importable as modules
+   - Need TypeScript/Python wrappers
+   - **Effort:** 2 weeks
+
+2. **❌ In-VM MCP Runtime** (Critical)
+   - Tools not callable from within VM
+   - Need bridge between VM and MCP
+   - **Effort:** 2 weeks
+
+3. **❌ Progressive Tool Discovery** (Important)
+   - No tool search/categorization
+   - No dynamic documentation
+   - **Effort:** 1 week
+
+### Overall Assessment
+
+**Current Readiness: 60%**
+- ✅ Infrastructure exists (VMs, MCP, agents)
+- ❌ Integration layer missing (code APIs, runtime bridge)
+- **Implementation Time: 12 weeks** to production-ready
+
+## Implementation Overview
+
+### Phase 1: Foundation (Weeks 1-4)
+**Goal:** Basic code execution with MCP tools
+
+**Key Tasks:**
+1. Create MCP code API layer
+2. Generate TypeScript/Python wrappers
+3. Build MCP runtime for VMs
+4. Update agent prompts for code-first approach
+
+**Deliverables:**
+- Agents can import MCP tools in code
+- >80% token reduction achieved
+- End-to-end workflow functional
+
+### Phase 2: Discovery & Scale (Weeks 5-8)
+**Goal:** Support 100+ tools efficiently
+
+**Key Tasks:**
+1. Implement progressive tool discovery
+2. Add workspace management
+3. Create token optimization metrics
+4. Build documentation system
+
+**Deliverables:**
+- Tool discovery <100ms
+- Support 100+ tools
+- Metrics dashboard live
+
+### Phase 3: Skills & Production (Weeks 9-12)
+**Goal:** Production-ready with reusable skills
+
+**Key Tasks:**
+1. Build skill library system
+2. Performance optimization (caching, pooling)
+3. Production hardening (monitoring, docs)
+4. Security audit and deployment
+
+**Deliverables:**
+- Skill library functional
+- 98%+ token reduction
+- 1000+ concurrent agents
+- Production deployed
+
+## Success Metrics
+
+### Token Efficiency
+- **Baseline:** 150K tokens (traditional approach)
+- **Target:** 2K tokens (code execution)
+- **Reduction:** 98%+
+
+### Performance
+- **Code Execution:** <2 seconds
+- **Tool Discovery:** <100ms
+- **End-to-End:** <5 seconds
+
+### Scalability
+- **Tools:** 500+ without degradation
+- **Agents:** 1000+ concurrent
+- **Uptime:** 99.9%
+
+### Quality
+- **Code Success Rate:** >95%
+- **Security:** 0 sandbox escapes
+- **Test Coverage:** >85%
+
+## Resource Requirements
+
+### Team
+- **Senior Rust Engineer:** 1 FTE (12 weeks)
+- **Full-Stack Engineer:** 0.5 FTE (12 weeks)
+- **DevOps Engineer:** 0.25 FTE (weeks 9-12)
+- **Technical Writer:** 0.25 FTE (weeks 10-12)
+
+### Infrastructure
+- Development environment (4 vCPUs, 16GB RAM)
+- Staging environment (8 vCPUs, 32GB RAM)
+- Firecracker VMs, Docker containers
+- Monitoring stack (Prometheus, Grafana)
+
+## Key Technical Components
+
+### 1. MCP Code API Layer
+**New Crate:** `crates/terraphim_mcp_codegen/`
+
+Generates TypeScript/Python wrappers for MCP tools:
+```typescript
+// Auto-generated from MCP server introspection
+export async function search(params: SearchParams): Promise<SearchResults> {
+  return await mcpCall('search', params);
+}
+```
+
+### 2. MCP Runtime for VMs
+**New Module:** `crates/terraphim_multi_agent/src/vm_execution/mcp_runtime.rs`
+
+Makes MCP tools available in VM environment:
+```rust
+pub struct McpRuntime {
+    mcp_client: Arc<McpClient>,
+}
+
+impl McpRuntime {
+    pub async fn call_tool(&self, name: &str, params: Value) -> Result<Value>;
+    pub fn inject_into_vm(&self, vm_id: &str) -> Result<()>;
+}
+```
+
+### 3. Code-First Agent Prompts
+**New Module:** `crates/terraphim_multi_agent/src/prompts/code_execution.rs`
+
+Optimized prompts for code generation:
+```
+You solve problems by writing code that imports MCP tools.
+
+Available tools:
+import { terraphim } from 'mcp-servers';
+
+Example:
+async function analyze() {
+  const docs = await terraphim.search({ query: "...", limit: 100 });
+  return docs.filter(d => d.rank > 0.8);
+}
+```
+
+### 4. Skill Library
+**New Crate:** `crates/terraphim_skills/`
+
+Stores reusable code patterns:
+```markdown
+# SKILL: Knowledge Graph Analysis
+
+## Function
+async function analyzeKnowledgeGraph(text: string): Promise<Report>
+
+## Usage History
+- Success Rate: 95%
+- Avg Time: 1.8s
+```
+
+## Risk Assessment
+
+### Technical Risks
+| Risk | Impact | Mitigation |
+|------|--------|------------|
+| Code generation quality | Medium | Validation, testing, fallback |
+| Sandbox escape | High | Multiple isolation layers, audit |
+| Performance degradation | Low | Caching, pooling, monitoring |
+
+### Project Risks
+| Risk | Impact | Mitigation |
+|------|--------|------------|
+| Timeline slip | Medium | Buffer, weekly reviews, scope adjustment |
+| Resource constraints | Low | Early identification, backup resources |
+
+## Comparison: Traditional vs Code Execution
+
+### Traditional Approach
+
+```
+User: "Find high-value Salesforce accounts and summarize"
+
+1. Load all Salesforce tool definitions → 10K tokens
+2. Agent calls search_salesforce
+   - Query: 200 tokens
+   - Results: 50K rows → 8K tokens
+3. Agent calls filter_records
+   - Query: 200 tokens
+   - Results: 500 rows → 5K tokens
+4. Agent calls create_summary
+   - Query: 200 tokens
+   - Summary: 10K tokens
+
+Total: ~40K tokens
+Time: ~8 seconds (multiple round-trips)
+```
+
+### Code Execution Approach
+
+```
+User: "Find high-value Salesforce accounts and summarize"
+
+1. Agent generates code → 1K tokens
+   ```typescript
+   import { salesforce } from 'mcp-servers';
+
+   async function analyze() {
+     const all = await salesforce.search({ query: "active accounts" });
+     const filtered = all.filter(a => a.revenue > 1000000);
+     return {
+       count: filtered.length,
+       top: filtered[0]
+     };
+   }
+   ```
+
+2. Code executes in VM (all processing internal)
+3. Final result returned → 500 tokens
+
+Total: ~2K tokens
+Time: ~2 seconds (single execution)
+```
+
+**Improvement: 95% token reduction, 75% faster**
+
+## Next Steps
+
+### 1. Review Phase (Week 0)
+- [ ] Review all documentation
+- [ ] Approve implementation plan
+- [ ] Allocate team resources
+- [ ] Set up project tracking
+
+### 2. Kickoff (Week 1)
+- [ ] Team onboarding
+- [ ] Environment setup
+- [ ] Create `terraphim_mcp_codegen` crate
+- [ ] Start TypeScript wrapper generation
+
+### 3. Ongoing
+- [ ] Weekly progress reviews
+- [ ] Daily standups
+- [ ] Continuous integration
+- [ ] Metrics tracking
+
+### 4. Launch (Week 12)
+- [ ] Production deployment
+- [ ] Monitoring active
+- [ ] Documentation published
+- [ ] Success celebration! 🎉
+
+## Questions?
+
+Contact the project team or refer to:
+- [Technical Specification](./CODE_EXECUTION_WITH_MCP_SPEC.md) for architecture details
+- [Gap Analysis](./CODE_EXECUTION_MCP_GAP_ANALYSIS.md) for capability assessment
+- [Implementation Plan](./CODE_EXECUTION_MCP_IMPLEMENTATION_PLAN.md) for detailed tasks
+
+---
+
+**Ready to implement?** Start with Phase 1, Week 1: Creating the MCP code API layer.