⚡ Custom Tools — Turn Any Command into an AI Tool

Define project-specific commands that AI can execute through MCP:

tools:
  - id: run-tests
    description: "Run project tests with coverage"
    type: run
    commands:
      - cmd: vendor/bin/phpunit
        args: [ "--coverage-html", "logs/coverage" ]

  - id: deploy
    description: "Deploy to staging"
    type: run
    schema:
      type: object
      properties:
        branch:
          type: string
          default: "main"
    commands:
      - cmd: ./deploy.sh
        args: [ "{{branch}}" ]

Tests, migrations, linters, deployments — anything your terminal can run, AI can trigger.

📁 Multi-Project Development

Work across multiple microservices simultaneously. AI sees all your projects and can develop cross-cutting features:

projects:
  - name: backend-api
    path: ../backend
    description: "REST API service"

  - name: auth-service
    path: ../auth
    description: "Authentication microservice"

  - name: shared-lib
    path: ../packages/shared
    description: "Shared domain models"

Start a session, ask AI to list available projects, and develop features that span multiple services — all in one conversation.

🎯 Smart Context Generation

Define exactly what context your AI needs. CTX collects code from files, git diffs, GitHub repos, URLs, and more — then structures it into clean markdown documents:

documents:
  - description: User Authentication System
    outputPath: auth.md
    sources:
      - type: file
        sourcePaths: [ src/Auth ]
        filePattern: "*.php"
      - type: git_diff
        commit: "last-week"

📐 Declarative Config with JSON Schema

Everything is configured through context.yaml with full JSON Schema support. Your AI assistant can generate and modify these configs for you — just describe what you need.

ctx init    # Generate initial config
ctx generate  # Build context documents
ctx server  # Start MCP server

Quick Start

Install

Linux / WSL:

curl -sSL https://raw.githubusercontent.com/context-hub/generator/main/download-latest.sh | sh

Windows:

powershell -c "& ([ScriptBlock]::Create((irm 'https://raw.githubusercontent.com/context-hub/generator/main/download-latest.ps1'))) -AddToPath"

Connect to Claude Desktop (or Any MCP Client)

The fastest way — auto-detect OS and configure your MCP client:

ctx mcp:config

Or add manually to your MCP client config:

{
  "mcpServers": {
    "ctx": {
      "command": "ctx",
      "args": [
        "server"
      ]
    }
  }
}

For a specific project:

{
  "mcpServers": {
    "ctx": {
      "command": "ctx",
      "args": [
        "server",
        "-c",
        "/path/to/project"
      ]
    }
  }
}

That's it. Your AI assistant now has full access to your project through MCP.

Optional: Generate Context Documents

If you also want to generate static context files for copy-paste workflows:

cd your-project
ctx init       # Create context.yaml
ctx generate   # Build markdown contexts

How It Works

CTX operates in two modes that complement each other:

MCP Server Mode — AI interacts with your codebase in real-time:

AI Assistant ←→ CTX MCP Server ←→ Your Project Files
                     ↕
              Custom Tools (tests, deploy, lint...)
              Multiple Projects
              Context Documents

Context Generation Mode — build structured documents for any LLM:

context.yaml → Sources → Filters → Modifiers → Markdown Documents

Use Cases

🔧 AI-Powered Development (MCP)

Connect CTX to Claude Desktop or Cursor. Ask your AI to explore the codebase, understand architecture, write new features, run tests, and fix issues — all without leaving the conversation.

🏗 Multi-Service Feature Development

Working on a feature that touches multiple microservices? Register all projects, and AI can read code from one service, understand shared models, and implement changes across the entire stack.

📝 Context for Code Review

Generate context documents with recent git diffs, relevant source files, and architecture overview. Share with reviewers or AI assistants for thorough, informed reviews.

🚀 Onboarding

New team member? Generate a comprehensive project overview — architecture, key interfaces, domain models — in seconds. AI can then answer questions about the codebase with full context.