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An advanced MCP server implementing a cognitive architecture through the GOTCHA framework and ATLAS process for sophisticated task management and reasoning. It
An advanced MCP server implementing a cognitive architecture through the GOTCHA framework and ATLAS process for sophisticated task management and reasoning. It provides persistent SQLite memory, lifecycle hooks, and a subagent system to enable complex, agentic AI workflows.
License: MIT TypeScript Node.js
A comprehensive Model Context Protocol (MCP) server implementing AGI-like capabilities through the GOTCHA Framework, ATLAS Process, Thinking Mechanism, Hook System, and Subagent Architecture with integrated database memory for persistent state management.
A sophisticated cognitive architecture for agentic systems:
Structured task execution methodology:
Intelligent reasoning and filtering layer:
Claude Code-style lifecycle hooks for customization:
Specialized AI assistants for focused tasks:
Persistent memory as source of truth:
Automatic initialization and management:
memory/logs and data structures# Clone the repository
git clone https://github.com/muah1987/AGI-MCP.git
cd AGI-MCP
# Install dependencies
npm install
# Build the project
npm run build
# Run tests
npm test
# Option 1: Pull from Docker Hub (recommended)
docker pull muah1987/agi-mcp:latest
# Option 2: Build locally
docker build -t agi-mcp:latest .
# Option 3: Use docker-compose
docker-compose build
# Run the test script to validate the build
./test-docker.sh
# 1. Create .env file with your credentials
cp .env.example .env
# Edit .env and add your DOCKER_USERNAME and DOCKER_TOKEN
# 2. Build and push to Docker Hub
./push-docker.sh
The repository includes a GitHub Actions workflow that automatically builds and pushes Docker images to DockerHub on every push to the main branch or when a tag is created.
Setup:
Add the following secrets to your GitHub repository settings:
DOCKER_LOGIN - Your DockerHub usernameDOCKER_PASSWORD - Your DockerHub password or access tokenThe workflow will automatically:
latest and the version from package.json$DOCKER_LOGIN/agi-mcp (where $DOCKER_LOGIN is your DockerHub username)Manual Trigger:
You can also trigger the workflow manually from the Actions tab in GitHub.
Add to your MCP client configuration (e.g., Claude Desktop, Cline):
{
"mcpServers": {
"agi-mcp": {
"command": "node",
"args": ["/absolute/path/to/AGI-MCP/dist/index.js"]
}
}
}
Using Docker for isolated deployment:
{
"mcpServers": {
"agi-mcp": {
"command": "docker",
"args": ["run", "-i", "--rm", "muah1987/agi-mcp:latest"]
}
}
}
Or using locally built image:
{
"mcpServers": {
"agi-mcp": {
"command": "docker",
"args": ["run", "-i", "--rm", "agi-mcp:latest"]
}
}
}
# Native
npm start
# Docker
docker run -i agi-mcp:latest
# Docker Compose
docker-compose up
On first run, AGI-MCP automatically:
memory/MEMORY.md documentationmemory/logs/ directorydata/ directoryset_goal - Define system objectivesobserve - Record environmental observationsthink - Capture reasoning processesexecute_command - Execute and log commandsform_hypothesis - Create predictionsassess_performance - Evaluate and learnprocess_goal_with_gotcha - Full cycle processingexecute_atlas_task - Run complete 5-step processget_atlas_history - View task execution historyget_active_goals - List active objectivesget_memory - Query memory by layerget_session_summary - Session overviewexecute_subagent - Delegate to specialistresume_subagent - Continue previous worklist_subagents - View available subagentsAGI-MCP/
├── src/
│ ├── index.ts # Main MCP server
│ ├── database/
│ │ ├── memory-db.ts # SQLite operations
│ │ └── infrastructure.ts # Auto-initialization
│ ├── gotcha/
│ │ ├── framework.ts # GOTCHA 6-layer system
│ │ └── thinking.ts # Thinking mechanism
│ ├── atlas/
│ │ └── process.ts # ATLAS 5-step process
│ ├── hooks/
│ │ └── hook-system.ts # Lifecycle hooks
│ ├── subagents/
│ │ └── subagent-system.ts # Subagent management
│ └── tools/
│ └── mcp-tools.ts # MCP tool definitions
├── memory/ # Memory system
│ ├── MEMORY.md # Documentation
│ └── logs/ # Session logs
├── data/ # Database storage
│ └── agi-mcp.db # SQLite database
└── .agi-mcp/ # Configuration
├── hooks/ # Hook scripts
├── subagents/ # Custom subagents
└── hooks-config.json # Hook configuration
await tools.handleToolCall('execute_atlas_task', {
task_id: 'research-001',
description: 'Research quantum computing applications'
});
await tools.handleToolCall('execute_subagent', {
subagent: 'code-reviewer',
task: 'Review authentication module for security'
});
{
"hooks": {
"PreToolUse": [{
"matcher": "execute_command",
"hooks": [{
"type": "command",
"command": "./validate-command.sh"
}]
}]
}
}
# Run all tests
npm test
# Build project
npm run build
Contributions are welcome! See CONTRIBUTING.md for guidelines.
This project is licensed under the MIT License - see the LICENSE file for details.
See SECURITY.md for security policies and reporting vulnerabilities.
See CHANGELOG.md for version history and changes.
AGI-MCP - Building towards Artificial General Intelligence through Model Context Protocol
Добавь это в claude_desktop_config.json и перезапусти Claude Desktop.
{
"mcpServers": {
"agi-mcp": {
"command": "npx",
"args": []
}
}
}