Initial commit: Complete Hive distributed AI orchestration platform

This comprehensive implementation includes: - FastAPI backend with MCP server integration - React/TypeScript frontend with Vite - PostgreSQL database with Redis caching - Grafana/Prometheus monitoring stack - Docker Compose orchestration - Full MCP protocol support for Claude Code integration Features: - Agent discovery and management across network - Visual workflow editor and execution engine - Real-time task coordination and monitoring - Multi-model support with specialized agents - Distributed development task allocation 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-07-07 21:44:31 +10:00
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+# 🐝 Hive + Claude Integration Guide
+
+Complete guide to integrate your Hive Distributed AI Orchestration Platform with Claude via Model Context Protocol (MCP).
+
+## 🎯 What This Enables
+
+With Hive MCP integration, Claude can:
+
+- **🤖 Orchestrate Your AI Cluster** - Assign development tasks across specialized agents
+- **📊 Monitor Real-time Progress** - Track task execution and agent utilization  
+- **🔄 Coordinate Complex Workflows** - Plan and execute multi-step distributed projects
+- **📈 Access Live Metrics** - Get cluster status, performance data, and health checks
+- **🧠 Make Intelligent Decisions** - Optimize task distribution based on agent capabilities
+
+## 🚀 Quick Setup
+
+### 1. Ensure Hive is Running
+
+```bash
+cd /home/tony/AI/projects/hive
+docker compose ps
+```
+
+You should see all services running:
+- ✅ `hive-backend` on port 8087
+- ✅ `hive-frontend` on port 3001  
+- ✅ `prometheus`, `grafana`, `redis`
+
+### 2. Run the Integration Setup
+
+```bash
+./scripts/setup_claude_integration.sh
+```
+
+This will:
+- ✅ Build the MCP server if needed
+- ✅ Detect your Claude Desktop configuration location
+- ✅ Create the proper MCP configuration
+- ✅ Backup any existing config
+
+### 3. Restart Claude Desktop
+
+After running the setup script, restart Claude Desktop to load the Hive MCP server.
+
+## 🎮 Using Claude with Hive
+
+Once integrated, you can use natural language to control your distributed AI cluster:
+
+### Agent Management
+```
+"Show me all my registered agents and their current status"
+
+"Register a new agent:
+- ID: walnut-kernel-dev  
+- Endpoint: http://walnut.local:11434
+- Model: codellama:34b
+- Specialization: kernel development"
+```
+
+### Task Creation & Monitoring
+```
+"Create a high-priority kernel development task to optimize FlashAttention for RDNA3 GPUs. 
+Include constraints for backward compatibility and focus on memory coalescing."
+
+"What's the status of task kernel_dev_1704671234?"
+
+"Show me all pending tasks grouped by specialization"
+```
+
+### Complex Project Coordination
+```
+"Help me coordinate development of a new PyTorch operator:
+
+1. CUDA/HIP kernel implementation (high priority)
+2. PyTorch integration layer (medium priority)
+3. Performance benchmarks (medium priority)  
+4. Documentation and examples (low priority)
+5. Unit and integration tests (high priority)
+
+Use parallel coordination where dependencies allow."
+```
+
+### Cluster Monitoring
+```
+"What's my cluster status? Show agent utilization and recent performance metrics."
+
+"Give me a summary of completed tasks from the last hour"
+
+"What are the current capabilities of my distributed AI cluster?"
+```
+
+### Workflow Management
+```
+"Create a workflow for distributed model training that includes data preprocessing, 
+training coordination, and result validation across my agents"
+
+"Execute workflow 'distributed-training' with input parameters for ResNet-50"
+
+"Show me the execution history for all workflows"
+```
+
+## 🔧 Available MCP Tools
+
+### Agent Management
+- **`hive_get_agents`** - List all registered agents with status
+- **`hive_register_agent`** - Register new agents in the cluster
+
+### Task Management  
+- **`hive_create_task`** - Create development tasks for specialized agents
+- **`hive_get_task`** - Get details of specific tasks
+- **`hive_get_tasks`** - List tasks with filtering options
+
+### Workflow Management
+- **`hive_get_workflows`** - List available workflows
+- **`hive_create_workflow`** - Create new distributed workflows
+- **`hive_execute_workflow`** - Execute workflows with inputs
+
+### Monitoring & Status
+- **`hive_get_cluster_status`** - Get comprehensive cluster status
+- **`hive_get_metrics`** - Retrieve Prometheus metrics
+- **`hive_get_executions`** - View workflow execution history
+
+### Advanced Coordination
+- **`hive_coordinate_development`** - Orchestrate complex multi-agent projects
+
+## 📊 Available MCP Resources
+
+Claude can access real-time cluster data through these resources:
+
+- **`hive://cluster/status`** - Live cluster health and status
+- **`hive://agents/list`** - Agent registry with capabilities  
+- **`hive://tasks/active`** - Currently running and pending tasks
+- **`hive://tasks/completed`** - Recent task results and metrics
+- **`hive://workflows/available`** - All configured workflows
+- **`hive://executions/recent`** - Recent workflow executions
+- **`hive://metrics/prometheus`** - Raw Prometheus metrics
+- **`hive://capabilities/overview`** - Cluster capabilities summary
+
+## 🏗️ Architecture Overview
+
+```
+┌─────────────────┐    MCP Protocol    ┌─────────────────┐
+│                 │ ◄─────────────────► │                 │
+│  Claude Desktop │                    │   Hive MCP      │
+│                 │                    │    Server       │
+└─────────────────┘                    └─────────────────┘
+                                                │
+                                                │ HTTP/WebSocket
+                                                ▼
+                                       ┌─────────────────┐
+                                       │                 │
+                                       │  Hive Backend   │
+                                       │   (FastAPI)     │
+                                       └─────────────────┘
+                                                │
+                                                │
+                        ┌───────────────────────┼───────────────────────┐
+                        ▼                       ▼                       ▼
+                ┌─────────────┐       ┌─────────────┐       ┌─────────────┐
+                │   Agent 1   │       │   Agent 2   │       │   Agent N   │
+                │ (Kernel Dev)│       │(PyTorch Dev)│       │  (Tester)   │
+                └─────────────┘       └─────────────┘       └─────────────┘
+```
+
+## 🔍 Example Integration Session
+
+Here's what a complete interaction might look like:
+
+```
+You: "What's the current status of my Hive cluster?"
+
+Claude: I'll check your Hive cluster status for you.
+
+[Uses hive_get_cluster_status tool]
+
+🐝 **Hive Cluster Status**
+
+🟢 **System**: operational (v1.0.0)
+⏱️ **Uptime**: 2h 15m
+
+🤖 **Agents**: 6 total
+   • Available: 4
+   • Busy: 2
+
+🎯 **Tasks**: 15 total  
+   • Pending: 3
+   • Running: 2
+   • Completed: 8
+   • Failed: 2
+
+Your cluster is healthy and processing tasks efficiently!
+
+---
+
+You: "Create a kernel optimization task for FlashAttention on RDNA3"
+
+Claude: I'll create a high-priority kernel development task for FlashAttention optimization.
+
+[Uses hive_create_task tool]
+
+🎯 Created development task **kernel_dev_1704671234**
+
+📋 Task Details:
+• Type: kernel_dev
+• Priority: 5/5
+• Status: pending
+• Objective: Optimize FlashAttention kernel for RDNA3 GPUs
+• Created: 2024-01-07T14:12:34
+
+The task has been queued and will be assigned to an available kernel_dev agent.
+
+---
+
+You: "Show me all my agents and coordinate a full PyTorch operator development project"
+
+Claude: Let me first check your available agents, then coordinate the development project.
+
+[Uses hive_get_agents and hive_coordinate_development tools]
+
+📋 Your agent capabilities:
+🤖 **walnut-kernel-dev** (kernel_dev) - Available
+🤖 **oak-pytorch-dev** (pytorch_dev) - Available  
+🤖 **ironwood-profiler** (profiler) - Busy (1/2 tasks)
+🤖 **acacia-docs** (docs_writer) - Available
+🤖 **rosewood-tester** (tester) - Available
+
+🎯 **Development Coordination Initiated**
+
+📋 **Project**: Complete PyTorch operator development
+🔄 **Strategy**: mixed (parallel where possible)
+🎯 **Tasks Created**: 5
+
+**Task Breakdown:**
+• **kernel_dev_1704671235** (kernel_dev) - Priority 5/5
+• **pytorch_dev_1704671236** (pytorch_dev) - Priority 4/5  
+• **profiler_1704671237** (profiler) - Priority 4/5
+• **docs_writer_1704671238** (docs_writer) - Priority 2/5
+• **tester_1704671239** (tester) - Priority 5/5
+
+All tasks have been distributed to specialized agents. Kernel development and testing will run in parallel, followed by PyTorch integration and documentation.
+```
+
+## 🛠️ Advanced Configuration
+
+### Custom Hive Backend URL
+If your Hive backend is running on a different host/port:
+
+```bash
+# Edit the Claude config to point to your Hive instance
+vim ~/Library/Application\ Support/Claude/claude_desktop_config.json
+
+# Update the env section:
+"env": {
+  "HIVE_API_URL": "http://your-hive-host:8087",
+  "HIVE_WS_URL": "ws://your-hive-host:8087"  
+}
+```
+
+### Multiple Hive Clusters
+You can configure multiple Hive clusters:
+
+```json
+{
+  "mcpServers": {
+    "hive-production": {
+      "command": "node",
+      "args": ["/path/to/hive/mcp-server/dist/index.js"],
+      "env": {
+        "HIVE_API_URL": "http://prod-hive:8087"
+      }
+    },
+    "hive-development": {
+      "command": "node", 
+      "args": ["/path/to/hive/mcp-server/dist/index.js"],
+      "env": {
+        "HIVE_API_URL": "http://dev-hive:8087"
+      }
+    }
+  }
+}
+```
+
+## 🔐 Security Considerations
+
+- 🔒 The MCP server only connects to your local Hive cluster
+- 🌐 No external network access required for the integration
+- 🏠 All communication stays within your development environment  
+- 🔑 Agent endpoints should be on trusted networks only
+- 📝 Consider authentication if deploying Hive on public networks
+
+## 🐛 Troubleshooting
+
+### MCP Server Won't Start
+```bash
+# Check if Hive backend is accessible
+curl http://localhost:8087/health
+
+# Test MCP server manually
+cd /home/tony/AI/projects/hive/mcp-server
+npm run dev
+```
+
+### Claude Can't See Hive Tools
+1. Verify Claude Desktop configuration path
+2. Check the config file syntax with `json_pp < claude_desktop_config.json`
+3. Restart Claude Desktop completely
+4. Check Claude Desktop logs (varies by OS)
+
+### Agent Connection Issues  
+```bash
+# Verify your agent endpoints are accessible
+curl http://your-agent-host:11434/api/tags
+
+# Check Hive backend logs
+docker compose logs hive-backend
+```
+
+## 🎉 What's Next?
+
+With Claude integrated into your Hive cluster, you can:
+
+1. **🧠 Intelligent Task Planning** - Let Claude analyze requirements and create optimal task breakdowns
+2. **🔄 Adaptive Coordination** - Claude can monitor progress and adjust task priorities dynamically  
+3. **📈 Performance Optimization** - Use Claude to analyze metrics and optimize agent utilization
+4. **🚀 Automated Workflows** - Create complex workflows through natural conversation
+5. **🐛 Proactive Issue Resolution** - Claude can detect and resolve common cluster issues
+
+**🐝 Welcome to the future of distributed AI development orchestration!**