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- csvlod-ai-mcp-server/dist/index.js
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Readme
CSVLOD-AI MCP Server
The CSVLOD-AI MCP (Model Context Protocol) Server is a meta-protocol implementation that brings the revolutionary efficiency of CSVLOD-AI Framework to the MCP ecosystem. It embodies sovereignty through local-first architecture while orchestrating other MCP servers intelligently.
🚀 Features
- Context Engineering Tools: Initialize, validate, and analyze CSVLOD contexts
- Local MCP Registry: Mirror and manage MCP servers locally for sovereignty
- Intelligent Orchestration: Automatically select and coordinate MCP servers
- Zero Remote Dependencies: Everything runs locally after initial setup
- 90% Efficiency Applied: CSVLOD optimization principles for MCP overhead
📦 Installation
NPM (Recommended)
npm install -g csvlod-ai-mcp-serverDocker
docker pull csvlod/mcp-server:latestFrom Source
git clone https://github.com/hamzaamjad/csvlod-ai-framework
cd mcp-server
npm install
npm run build🛠️ Available Tools
CSVLOD Tools
csvlod_init - Initialize CSVLOD framework in any project
{ "projectPath": "/path/to/project", "type": "basic" | "enterprise" | "minimal" }
csvlod_validate - Validate CSVLOD compliance
{ "path": "/path/to/validate", "strict": true }
csvlod_generate - Generate CSVLOD components
{ "component": "context" | "manifest" | "prompt" | "structure", "path": "/target/path", "options": { "framework": "react", "language": "typescript" } }
csvlod_analyze - Analyze context effectiveness
{ "path": "/path/to/analyze", "includeMetrics": true }
MCP Registry Tools
mcp_registry - Manage local MCP registry
{ "action": "sync" | "search" | "install" | "list", "query": "github-mcp", "localOnly": true }
mcp_orchestrate - Intelligently orchestrate MCP servers
{ "task": "Search for TODOs in my codebase and create GitHub issues", "preferLocal": true, "ephemeral": true }
🏗️ Architecture
Local-First Design
All MCP servers are cached locally in ~/.csvlod-ai/ ensuring:
- Complete offline functionality
- Data sovereignty
- No external dependencies
- Privacy by default
Context Engineering
The server applies CSVLOD principles to MCP:
- Rich context over complex prompts
- Structure enables capability
- Progressive enhancement
- Self-improving systems
🔧 Configuration
MCP Configuration (for Cursor, Claude, etc.)
{
"mcpServers": {
"csvlod-ai": {
"command": "npx",
"args": ["-y", "csvlod-ai-mcp-server"],
"env": {
"CSVLOD_LOCAL_ONLY": "true"
}
}
}
}Environment Variables
CSVLOD_LOCAL_ONLY- Use only local registry (default: false)CSVLOD_CACHE_DIR- Custom cache directory (default: ~/.csvlod-ai)CSVLOD_REGISTRY_URL- Custom registry URL (for air-gapped environments)
💡 Usage Examples
Initialize a New Project with CSVLOD
// Tool: csvlod_init
{
"projectPath": "./my-new-app",
"type": "enterprise"
}
// Creates:
// - .context/ directory with full CSVLOD structure
// - AI-CONTEXT.md with project overview
// - AGENT-MANIFEST.yaml with capabilitiesOrchestrate Multiple MCP Servers
// Tool: mcp_orchestrate
{
"task": "Analyze my code for security issues and create a report",
"preferLocal": true,
"ephemeral": true
}
// Returns execution plan using:
// - filesystem-mcp for code reading
// - security-mcp for analysis
// - report-mcp for generationSync and Search Registry
// Tool: mcp_registry
{
"action": "sync",
"localOnly": false
}
// Then search:
{
"action": "search",
"query": "github"
}🌟 Philosophy
The CSVLOD-AI MCP Server embodies:
- Sovereignty First: Your tools, your data, your control
- Context > Prompts: Rich structure enables AI effectiveness
- Local > Remote: Everything cached locally for true ownership
- Efficiency: 90% optimization principles applied to MCP
- Simplicity: Zero dependencies, pure functionality
🤝 Contributing
- Fork the repository
- Create your feature branch
- Implement following CSVLOD principles
- Ensure local-first architecture
- Submit PR with context
📚 Documentation
📄 License
MIT License - Free forever, as sovereignty demands.
Created by Hamza Amjad
Part of the CSVLOD-AI Framework revolutionizing AI-native development
"Context > Prompts. Sovereignty > Dependence. Local > Remote."