bzzz/deploy/DEPLOYMENT_GUIDE.md

BZZZ MCP Integration Deployment Guide

This guide provides step-by-step instructions for deploying the BZZZ MCP integration with GPT-4 agents across the CHORUS cluster.

Prerequisites

Infrastructure Requirements

• Cluster Nodes: Minimum 3 nodes (WALNUT, IRONWOOD, ACACIA)
• RAM: 32GB+ per node for optimal performance
• Storage: 1TB+ SSD per node for conversation history and logs
• Network: High-speed connection between nodes for P2P communication

Software Prerequisites

# On each node, ensure these are installed:
docker --version                # Docker 24.0+
docker-compose --version        # Docker Compose 2.20+
go version                      # Go 1.21+
node --version                  # Node.js 18+

API Keys and Secrets

Ensure the OpenAI API key is properly stored:

# Verify the OpenAI API key exists
cat ~/chorus/business/secrets/openai-api-key-for-bzzz.txt

Deployment Steps

1. Pre-Deployment Setup

Clone and Build

cd /home/tony/chorus/project-queues/active/BZZZ

# Build Go components
go mod download
go build -o bzzz main.go

# Build MCP server
cd mcp-server
npm install
npm run build
cd ..

# Build Docker images
docker build -t bzzz/mcp-node:latest .
docker build -t bzzz/mcp-server:latest mcp-server/

Environment Configuration

# Create environment file
cat > .env << EOF
# BZZZ Network Configuration
BZZZ_NODE_ID=bzzz-mcp-walnut
BZZZ_NETWORK_ID=bzzz-chorus-cluster
BZZZ_P2P_PORT=4001
BZZZ_HTTP_PORT=8080

# OpenAI Configuration
OPENAI_MODEL=gpt-4
OPENAI_MAX_TOKENS=4000
OPENAI_TEMPERATURE=0.7

# Cost Management
DAILY_COST_LIMIT=100.0
MONTHLY_COST_LIMIT=1000.0
COST_WARNING_THRESHOLD=0.8

# Agent Configuration
MAX_AGENTS=5
MAX_ACTIVE_THREADS=10
THREAD_TIMEOUT=3600

# Database Configuration
POSTGRES_PASSWORD=$(openssl rand -base64 32)

# Monitoring
GRAFANA_PASSWORD=$(openssl rand -base64 16)

# Integration URLs
WHOOSH_API_URL=http://192.168.1.72:8001
SLURP_API_URL=http://192.168.1.113:8002
EOF

# Source the environment
source .env

2. Database Initialization

Create the PostgreSQL schema:

cat > deploy/init-db.sql << EOF
-- BZZZ MCP Database Schema
CREATE EXTENSION IF NOT EXISTS "uuid-ossp";

-- Agents table
CREATE TABLE agents (
    id VARCHAR(255) PRIMARY KEY,
    role VARCHAR(100) NOT NULL,
    model VARCHAR(100) NOT NULL,
    capabilities TEXT[],
    specialization VARCHAR(255),
    max_tasks INTEGER DEFAULT 3,
    status VARCHAR(50) DEFAULT 'idle',
    created_at TIMESTAMP DEFAULT NOW(),
    last_active TIMESTAMP DEFAULT NOW(),
    node_id VARCHAR(255),
    system_prompt TEXT
);

-- Conversations table
CREATE TABLE conversations (
    id VARCHAR(255) PRIMARY KEY,
    topic TEXT NOT NULL,
    state VARCHAR(50) DEFAULT 'active',
    created_at TIMESTAMP DEFAULT NOW(),
    last_activity TIMESTAMP DEFAULT NOW(),
    creator_id VARCHAR(255),
    shared_context JSONB DEFAULT '{}'::jsonb
);

-- Conversation participants
CREATE TABLE conversation_participants (
    conversation_id VARCHAR(255) REFERENCES conversations(id),
    agent_id VARCHAR(255) REFERENCES agents(id),
    role VARCHAR(100),
    status VARCHAR(50) DEFAULT 'active',
    joined_at TIMESTAMP DEFAULT NOW(),
    PRIMARY KEY (conversation_id, agent_id)
);

-- Messages table
CREATE TABLE messages (
    id UUID DEFAULT uuid_generate_v4() PRIMARY KEY,
    conversation_id VARCHAR(255) REFERENCES conversations(id),
    from_agent VARCHAR(255) REFERENCES agents(id),
    content TEXT NOT NULL,
    message_type VARCHAR(100),
    timestamp TIMESTAMP DEFAULT NOW(),
    reply_to UUID REFERENCES messages(id),
    token_count INTEGER DEFAULT 0,
    model VARCHAR(100)
);

-- Agent tasks
CREATE TABLE agent_tasks (
    id VARCHAR(255) PRIMARY KEY,
    agent_id VARCHAR(255) REFERENCES agents(id),
    repository VARCHAR(255),
    task_number INTEGER,
    title TEXT,
    status VARCHAR(50) DEFAULT 'active',
    start_time TIMESTAMP DEFAULT NOW(),
    context JSONB DEFAULT '{}'::jsonb,
    thread_id VARCHAR(255)
);

-- Token usage tracking
CREATE TABLE token_usage (
    id UUID DEFAULT uuid_generate_v4() PRIMARY KEY,
    agent_id VARCHAR(255) REFERENCES agents(id),
    conversation_id VARCHAR(255),
    timestamp TIMESTAMP DEFAULT NOW(),
    model VARCHAR(100),
    prompt_tokens INTEGER,
    completion_tokens INTEGER,
    total_tokens INTEGER,
    cost_usd DECIMAL(10,6)
);

-- Agent memory
CREATE TABLE agent_memory (
    agent_id VARCHAR(255) REFERENCES agents(id),
    memory_type VARCHAR(50), -- 'working', 'episodic', 'semantic'
    key VARCHAR(255),
    value JSONB,
    timestamp TIMESTAMP DEFAULT NOW(),
    expires_at TIMESTAMP,
    PRIMARY KEY (agent_id, memory_type, key)
);

-- Escalations
CREATE TABLE escalations (
    id UUID DEFAULT uuid_generate_v4() PRIMARY KEY,
    conversation_id VARCHAR(255) REFERENCES conversations(id),
    reason VARCHAR(255),
    escalated_at TIMESTAMP DEFAULT NOW(),
    escalated_by VARCHAR(255),
    status VARCHAR(50) DEFAULT 'pending',
    resolved_at TIMESTAMP,
    resolution TEXT
);

-- Indexes for performance
CREATE INDEX idx_agents_role ON agents(role);
CREATE INDEX idx_agents_status ON agents(status);
CREATE INDEX idx_conversations_state ON conversations(state);
CREATE INDEX idx_messages_conversation_timestamp ON messages(conversation_id, timestamp);
CREATE INDEX idx_token_usage_agent_timestamp ON token_usage(agent_id, timestamp);
CREATE INDEX idx_agent_memory_agent_type ON agent_memory(agent_id, memory_type);
EOF

3. Deploy to Cluster

Node-Specific Deployment

On WALNUT (192.168.1.27):

# Set node-specific configuration
export BZZZ_NODE_ID=bzzz-mcp-walnut
export NODE_ROLE=primary

# Deploy with primary node configuration
docker-compose -f deploy/docker-compose.mcp.yml up -d

On IRONWOOD (192.168.1.72):

# Set node-specific configuration  
export BZZZ_NODE_ID=bzzz-mcp-ironwood
export NODE_ROLE=secondary

# Deploy as secondary node
docker-compose -f deploy/docker-compose.mcp.yml up -d

On ACACIA (192.168.1.113):

# Set node-specific configuration
export BZZZ_NODE_ID=bzzz-mcp-acacia
export NODE_ROLE=secondary

# Deploy as secondary node
docker-compose -f deploy/docker-compose.mcp.yml up -d

4. Service Health Verification

Check Service Status

# Check all services are running
docker-compose -f deploy/docker-compose.mcp.yml ps

# Check BZZZ node connectivity
curl http://localhost:8080/health

# Check MCP server status
curl http://localhost:8081/health

# Check P2P network connectivity
curl http://localhost:8080/api/peers

Verify Agent Registration

# List registered agents
curl http://localhost:8081/api/agents

# Check agent capabilities
curl http://localhost:8081/api/agents/review_agent_architect

Test MCP Integration

# Test MCP server connection
cd examples
python3 test-mcp-connection.py

# Run collaborative review example
python3 collaborative-review-example.py

5. Integration with CHORUS Systems

WHOOSH Integration

# Verify WHOOSH connectivity
curl -X POST http://192.168.1.72:8001/api/agents \
  -H "Content-Type: application/json" \
  -d '{
    "agent_id": "bzzz-mcp-agent-1",
    "type": "gpt_agent",
    "role": "architect",
    "endpoint": "http://192.168.1.27:8081"
  }'

SLURP Integration

# Test SLURP context event submission
curl -X POST http://192.168.1.113:8002/api/events \
  -H "Content-Type: application/json" \
  -d '{
    "type": "agent_consensus",
    "source": "bzzz_mcp_integration",
    "context": {
      "conversation_id": "test-thread-1",
      "participants": ["architect", "reviewer"],
      "consensus_reached": true
    }
  }'

6. Monitoring Setup

Access Monitoring Dashboards

• Grafana: http://localhost:3000 (admin/password from .env)
• Prometheus: http://localhost:9090
• Logs: Access via Grafana Loki integration

Key Metrics to Monitor

# Agent performance metrics
curl http://localhost:8081/api/stats

# Token usage and costs
curl http://localhost:8081/api/costs/daily

# Conversation thread health
curl http://localhost:8081/api/conversations?status=active

Configuration Management

Agent Role Configuration

Create custom agent roles:

# Create custom agent configuration
cat > config/custom-agent-roles.json << EOF
{
  "roles": [
    {
      "name": "security_architect",
      "specialization": "security_design",
      "capabilities": [
        "threat_modeling",
        "security_architecture",
        "compliance_review",
        "risk_assessment"
      ],
      "system_prompt": "You are a security architect specializing in distributed systems security...",
      "interaction_patterns": {
        "architects": "security_consultation",
        "developers": "security_guidance",
        "reviewers": "security_validation"
      }
    }
  ]
}
EOF

Cost Management Configuration

# Configure cost alerts
cat > config/cost-limits.json << EOF
{
  "global_limits": {
    "daily_limit": 100.0,
    "monthly_limit": 1000.0,
    "per_agent_daily": 20.0
  },
  "alert_thresholds": {
    "warning": 0.8,
    "critical": 0.95
  },
  "alert_channels": {
    "slack_webhook": "${SLACK_WEBHOOK_URL}",
    "email": "admin@deepblack.cloud"
  }
}
EOF

Escalation Rules Configuration

# Configure escalation rules
cat > config/escalation-rules.json << EOF
{
  "rules": [
    {
      "name": "Long Running Thread",
      "conditions": [
        {"type": "thread_duration", "threshold": 7200},
        {"type": "no_progress", "threshold": true, "timeframe": 1800}
      ],
      "actions": [
        {"type": "notify_human", "target": "project_manager"},
        {"type": "escalate_to_senior", "role": "senior_architect"}
      ]
    },
    {
      "name": "High Cost Alert",
      "conditions": [
        {"type": "token_cost", "threshold": 50.0, "timeframe": 3600}
      ],
      "actions": [
        {"type": "throttle_agents", "reduction": 0.5},
        {"type": "notify_admin", "urgency": "high"}
      ]
    }
  ]
}
EOF

Troubleshooting

Common Issues

MCP Server Connection Issues

# Check MCP server logs
docker logs bzzz-mcp-server

# Verify OpenAI API key
docker exec bzzz-mcp-server cat /secrets/openai-api-key-for-bzzz.txt

# Test API key validity
curl -H "Authorization: Bearer $(cat ~/chorus/business/secrets/openai-api-key-for-bzzz.txt)" \
  https://api.openai.com/v1/models

P2P Network Issues

# Check P2P connectivity
docker exec bzzz-mcp-node ./bzzz status

# View P2P logs
docker logs bzzz-mcp-node | grep p2p

# Check firewall settings
sudo ufw status | grep 4001

Agent Performance Issues

# Check agent memory usage
curl http://localhost:8081/api/agents/memory-stats

# Review token usage
curl http://localhost:8081/api/costs/breakdown

# Check conversation thread status
curl http://localhost:8081/api/conversations?status=active

Performance Optimization

Database Tuning

-- Optimize PostgreSQL for BZZZ MCP workload
ALTER SYSTEM SET shared_buffers = '256MB';
ALTER SYSTEM SET work_mem = '16MB';
ALTER SYSTEM SET maintenance_work_mem = '128MB';
ALTER SYSTEM SET max_connections = 100;
SELECT pg_reload_conf();

Agent Optimization

# Optimize agent memory usage
curl -X POST http://localhost:8081/api/agents/cleanup-memory

# Adjust token limits based on usage patterns
curl -X PUT http://localhost:8081/api/config/token-limits \
  -H "Content-Type: application/json" \
  -d '{"max_tokens": 2000, "context_window": 16000}'

Backup and Recovery

Database Backup

# Create database backup
docker exec bzzz-mcp-postgres pg_dump -U bzzz bzzz_mcp | gzip > backup/bzzz-mcp-$(date +%Y%m%d).sql.gz

# Restore from backup
gunzip -c backup/bzzz-mcp-20250107.sql.gz | docker exec -i bzzz-mcp-postgres psql -U bzzz -d bzzz_mcp

Configuration Backup

# Backup agent configurations
docker exec bzzz-mcp-server tar czf - /var/lib/mcp/config > backup/mcp-config-$(date +%Y%m%d).tar.gz

# Backup conversation data
docker exec bzzz-conversation-manager tar czf - /var/lib/conversations > backup/conversations-$(date +%Y%m%d).tar.gz

Security Considerations

API Key Security

# Rotate OpenAI API key monthly
echo "new-api-key" > ~/chorus/business/secrets/openai-api-key-for-bzzz.txt
docker-compose -f deploy/docker-compose.mcp.yml restart mcp-server

# Monitor API key usage
curl -H "Authorization: Bearer $(cat ~/chorus/business/secrets/openai-api-key-for-bzzz.txt)" \
  https://api.openai.com/v1/usage

Network Security

# Configure firewall rules
sudo ufw allow from 192.168.1.0/24 to any port 4001  # P2P port
sudo ufw allow from 192.168.1.0/24 to any port 8080  # BZZZ API
sudo ufw allow from 192.168.1.0/24 to any port 8081  # MCP API

# Enable audit logging
docker-compose -f deploy/docker-compose.mcp.yml \
  -f deploy/docker-compose.audit.yml up -d

Maintenance

Regular Maintenance Tasks

# Weekly maintenance script
#!/bin/bash
set -e

echo "Starting BZZZ MCP maintenance..."

# Clean up old conversation threads
curl -X POST http://localhost:8081/api/maintenance/cleanup-threads

# Optimize database
docker exec bzzz-mcp-postgres psql -U bzzz -d bzzz_mcp -c "VACUUM ANALYZE;"

# Update cost tracking
curl -X POST http://localhost:8081/api/maintenance/update-costs

# Rotate logs
docker exec bzzz-mcp-server logrotate /etc/logrotate.d/mcp

echo "Maintenance completed successfully"

Performance Monitoring

# Monitor key performance indicators
curl http://localhost:8081/api/metrics | jq '{
  active_agents: .active_agents,
  active_threads: .active_threads,
  avg_response_time: .avg_response_time,
  token_efficiency: .token_efficiency,
  cost_per_task: .cost_per_task
}'

This deployment guide provides a comprehensive approach to deploying and maintaining the BZZZ MCP integration with GPT-4 agents across the CHORUS cluster. Follow the steps carefully and refer to the troubleshooting section for common issues.