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>
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anthonyrawlins
370
mcp-server/dist/hive-resources.js
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370
mcp-server/dist/hive-resources.js
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/**
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* Hive Resources
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*
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* Defines MCP resources that expose Hive cluster state and real-time data
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*/
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export class HiveResources {
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hiveClient;
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constructor(hiveClient) {
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this.hiveClient = hiveClient;
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}
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async getAllResources() {
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return [
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{
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uri: 'hive://cluster/status',
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name: 'Cluster Status',
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description: 'Real-time status of the entire Hive cluster including agents and tasks',
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mimeType: 'application/json',
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},
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{
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uri: 'hive://agents/list',
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name: 'Agent Registry',
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description: 'List of all registered AI agents with their capabilities and current status',
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mimeType: 'application/json',
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},
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{
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uri: 'hive://tasks/active',
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name: 'Active Tasks',
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description: 'Currently running and pending tasks across the cluster',
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mimeType: 'application/json',
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},
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{
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uri: 'hive://tasks/completed',
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name: 'Completed Tasks',
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description: 'Recently completed tasks with results and performance metrics',
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mimeType: 'application/json',
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},
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{
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uri: 'hive://workflows/available',
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name: 'Available Workflows',
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description: 'All configured workflows ready for execution',
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mimeType: 'application/json',
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},
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{
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uri: 'hive://executions/recent',
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name: 'Recent Executions',
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description: 'Recent workflow executions with status and results',
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mimeType: 'application/json',
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},
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{
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uri: 'hive://metrics/prometheus',
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name: 'Cluster Metrics',
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description: 'Prometheus metrics for monitoring cluster performance',
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mimeType: 'text/plain',
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},
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{
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uri: 'hive://capabilities/overview',
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name: 'Cluster Capabilities',
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description: 'Overview of available agent types and their specializations',
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mimeType: 'application/json',
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},
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];
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}
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async readResource(uri) {
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try {
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switch (uri) {
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case 'hive://cluster/status':
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return await this.getClusterStatusResource();
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case 'hive://agents/list':
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return await this.getAgentsResource();
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case 'hive://tasks/active':
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return await this.getActiveTasksResource();
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case 'hive://tasks/completed':
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return await this.getCompletedTasksResource();
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case 'hive://workflows/available':
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return await this.getWorkflowsResource();
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case 'hive://executions/recent':
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return await this.getExecutionsResource();
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case 'hive://metrics/prometheus':
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return await this.getMetricsResource();
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case 'hive://capabilities/overview':
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return await this.getCapabilitiesResource();
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default:
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throw new Error(`Resource not found: ${uri}`);
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}
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}
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catch (error) {
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return {
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contents: [
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{
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type: 'text',
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text: `Error reading resource ${uri}: ${error instanceof Error ? error.message : String(error)}`,
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},
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],
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};
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}
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}
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async getClusterStatusResource() {
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const status = await this.hiveClient.getClusterStatus();
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return {
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contents: [
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{
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type: 'text',
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data: JSON.stringify(status, null, 2),
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mimeType: 'application/json',
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},
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],
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};
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}
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async getAgentsResource() {
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const agents = await this.hiveClient.getAgents();
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const agentData = {
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total_agents: agents.length,
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agents: agents.map(agent => ({
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id: agent.id,
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specialty: agent.specialty,
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model: agent.model,
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endpoint: agent.endpoint,
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status: agent.status,
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current_tasks: agent.current_tasks,
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max_concurrent: agent.max_concurrent,
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utilization: agent.max_concurrent > 0 ? (agent.current_tasks / agent.max_concurrent * 100).toFixed(1) + '%' : '0%',
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})),
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by_specialty: this.groupAgentsBySpecialty(agents),
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availability_summary: {
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available: agents.filter(a => a.status === 'available').length,
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busy: agents.filter(a => a.status === 'busy').length,
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offline: agents.filter(a => a.status === 'offline').length,
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},
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};
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return {
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contents: [
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{
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type: 'text',
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data: JSON.stringify(agentData, null, 2),
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mimeType: 'application/json',
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},
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],
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};
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}
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async getActiveTasksResource() {
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const pendingTasks = await this.hiveClient.getTasks({ status: 'pending', limit: 50 });
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const runningTasks = await this.hiveClient.getTasks({ status: 'in_progress', limit: 50 });
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const activeData = {
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summary: {
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pending: pendingTasks.length,
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running: runningTasks.length,
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total_active: pendingTasks.length + runningTasks.length,
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},
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pending_tasks: pendingTasks.map(this.formatTaskForResource),
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running_tasks: runningTasks.map(this.formatTaskForResource),
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queue_analysis: this.analyzeTaskQueue(pendingTasks),
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};
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return {
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contents: [
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{
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type: 'text',
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data: JSON.stringify(activeData, null, 2),
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mimeType: 'application/json',
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},
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],
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};
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}
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async getCompletedTasksResource() {
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const completedTasks = await this.hiveClient.getTasks({ status: 'completed', limit: 20 });
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const failedTasks = await this.hiveClient.getTasks({ status: 'failed', limit: 10 });
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const completedData = {
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summary: {
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completed: completedTasks.length,
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failed: failedTasks.length,
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success_rate: completedTasks.length + failedTasks.length > 0
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? ((completedTasks.length / (completedTasks.length + failedTasks.length)) * 100).toFixed(1) + '%'
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: 'N/A',
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},
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recent_completed: completedTasks.map(this.formatTaskForResource),
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recent_failed: failedTasks.map(this.formatTaskForResource),
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performance_metrics: this.calculateTaskMetrics(completedTasks),
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};
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return {
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contents: [
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{
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type: 'text',
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data: JSON.stringify(completedData, null, 2),
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mimeType: 'application/json',
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},
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],
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};
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}
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async getWorkflowsResource() {
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const workflows = await this.hiveClient.getWorkflows();
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const workflowData = {
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total_workflows: workflows.length,
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workflows: workflows.map(wf => ({
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id: wf.id,
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name: wf.name || 'Unnamed Workflow',
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description: wf.description || 'No description',
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status: wf.status || 'unknown',
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created: wf.created_at || 'unknown',
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steps: wf.steps?.length || 0,
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})),
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};
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return {
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contents: [
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{
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type: 'text',
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data: JSON.stringify(workflowData, null, 2),
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mimeType: 'application/json',
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},
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],
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};
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}
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async getExecutionsResource() {
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const executions = await this.hiveClient.getExecutions();
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const executionData = {
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total_executions: executions.length,
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recent_executions: executions.slice(0, 10).map(exec => ({
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id: exec.id,
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workflow_id: exec.workflow_id,
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status: exec.status,
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started_at: exec.started_at,
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completed_at: exec.completed_at,
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duration: exec.completed_at && exec.started_at
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? this.calculateDuration(exec.started_at, exec.completed_at)
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: null,
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})),
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status_summary: this.summarizeExecutionStatuses(executions),
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};
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return {
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contents: [
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{
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type: 'text',
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data: JSON.stringify(executionData, null, 2),
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mimeType: 'application/json',
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},
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],
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};
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}
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async getMetricsResource() {
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const metrics = await this.hiveClient.getMetrics();
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return {
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contents: [
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{
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type: 'text',
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text: metrics,
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mimeType: 'text/plain',
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},
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],
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};
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}
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async getCapabilitiesResource() {
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const agents = await this.hiveClient.getAgents();
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const capabilities = {
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agent_specializations: {
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kernel_dev: {
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description: 'GPU kernel development, HIP/CUDA optimization, memory coalescing',
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available_agents: agents.filter(a => a.specialty === 'kernel_dev').length,
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typical_models: ['codellama:34b', 'deepseek-coder:33b'],
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},
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pytorch_dev: {
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description: 'PyTorch backend development, autograd, TunableOp integration',
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available_agents: agents.filter(a => a.specialty === 'pytorch_dev').length,
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typical_models: ['deepseek-coder:33b', 'codellama:34b'],
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},
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profiler: {
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description: 'Performance analysis, GPU profiling, bottleneck identification',
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available_agents: agents.filter(a => a.specialty === 'profiler').length,
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typical_models: ['llama3:70b', 'mixtral:8x7b'],
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},
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docs_writer: {
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description: 'Technical documentation, API docs, tutorials, examples',
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available_agents: agents.filter(a => a.specialty === 'docs_writer').length,
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typical_models: ['llama3:70b', 'claude-3-haiku'],
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},
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tester: {
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description: 'Test creation, benchmarking, CI/CD, edge case handling',
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available_agents: agents.filter(a => a.specialty === 'tester').length,
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typical_models: ['codellama:34b', 'deepseek-coder:33b'],
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},
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},
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cluster_capacity: {
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total_agents: agents.length,
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total_concurrent_capacity: agents.reduce((sum, agent) => sum + agent.max_concurrent, 0),
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current_utilization: agents.reduce((sum, agent) => sum + agent.current_tasks, 0),
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},
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supported_frameworks: [
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'ROCm/HIP', 'PyTorch', 'CUDA', 'OpenMP', 'MPI', 'Composable Kernel'
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],
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target_architectures: [
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'RDNA3', 'CDNA3', 'RDNA2', 'Vega', 'NVIDIA GPUs (via CUDA)'
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],
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};
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return {
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contents: [
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{
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type: 'text',
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data: JSON.stringify(capabilities, null, 2),
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mimeType: 'application/json',
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},
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],
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};
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}
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// Helper Methods
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groupAgentsBySpecialty(agents) {
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const grouped = {};
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agents.forEach(agent => {
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if (!grouped[agent.specialty]) {
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grouped[agent.specialty] = [];
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}
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grouped[agent.specialty].push(agent);
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});
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return grouped;
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}
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formatTaskForResource(task) {
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return {
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id: task.id,
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type: task.type,
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priority: task.priority,
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status: task.status,
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assigned_agent: task.assigned_agent,
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created_at: task.created_at,
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completed_at: task.completed_at,
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objective: task.context?.objective || 'No objective specified',
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};
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}
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analyzeTaskQueue(tasks) {
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const byType = tasks.reduce((acc, task) => {
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acc[task.type] = (acc[task.type] || 0) + 1;
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return acc;
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}, {});
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const byPriority = tasks.reduce((acc, task) => {
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const priority = `priority_${task.priority}`;
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acc[priority] = (acc[priority] || 0) + 1;
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return acc;
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}, {});
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return {
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by_type: byType,
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by_priority: byPriority,
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average_priority: tasks.length > 0
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? (tasks.reduce((sum, task) => sum + task.priority, 0) / tasks.length).toFixed(1)
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: 0,
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};
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}
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calculateTaskMetrics(tasks) {
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if (tasks.length === 0)
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return null;
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const durations = tasks
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.filter(task => task.created_at && task.completed_at)
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.map(task => new Date(task.completed_at).getTime() - new Date(task.created_at).getTime());
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if (durations.length === 0)
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return null;
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return {
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average_duration_ms: Math.round(durations.reduce((a, b) => a + b, 0) / durations.length),
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min_duration_ms: Math.min(...durations),
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max_duration_ms: Math.max(...durations),
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total_tasks_analyzed: durations.length,
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};
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}
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summarizeExecutionStatuses(executions) {
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return executions.reduce((acc, exec) => {
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acc[exec.status] = (acc[exec.status] || 0) + 1;
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return acc;
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}, {});
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}
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calculateDuration(start, end) {
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const duration = new Date(end).getTime() - new Date(start).getTime();
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const minutes = Math.floor(duration / 60000);
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const seconds = Math.floor((duration % 60000) / 1000);
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return `${minutes}m ${seconds}s`;
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}
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}
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//# sourceMappingURL=hive-resources.js.map
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