# Auto-configures MCP for your environment
./scripts/setup-mcp-json.sh

# Or interactive mode
./scripts/setup-mcp-json.sh --interactive

# Install MCP Index with Docker
curl -sSL https://raw.githubusercontent.com/ViperJuice/Code-Index-MCP/main/scripts/install-mcp-docker.sh | bash

# Index your current directory
docker run -it -v $(pwd):/workspace ghcr.io/code-index-mcp/mcp-index:minimal

# Set your API key (get one at https://www.voyageai.com — free tier available)
export VOYAGE_API_KEY=your-key

# Run with semantic search
docker run -it -v $(pwd):/workspace -e VOYAGE_API_KEY ghcr.io/code-index-mcp/mcp-index:standard

# PowerShell
.\scripts\setup-mcp-json.ps1

# Or manually with Docker Desktop
docker run -it -v ${PWD}:/workspace ghcr.io/code-index-mcp/mcp-index:minimal

# Install Docker Desktop or use Homebrew
brew install --cask docker

# Run setup
./scripts/setup-mcp-json.sh

# Install Docker (no Desktop needed)
curl -fsSL https://get.docker.com | sh

# Run setup
./scripts/setup-mcp-json.sh

# With Docker Desktop integration
./scripts/setup-mcp-json.sh  # Auto-detects WSL+Docker

# Without Docker Desktop
cp .mcp.json.templates/native.json .mcp.json
pip install -e .

# For VS Code/Cursor dev containers
# Option 1: Use native Python (already in container)
cp .mcp.json.templates/native.json .mcp.json

# Option 2: Use Docker sidecar (avoids dependency conflicts)
docker-compose -f docker/compose/development/docker-compose.mcp-sidecar.yml up -d
cp .mcp.json.templates/docker-sidecar.json .mcp.json

{
  "mcpServers": {
    "code-index-native": {
      "command": "python",
      "args": ["scripts/cli/mcp_server_cli.py"],
      "cwd": "${workspace}"
    }
  }
}

{
  "mcpServers": {
    "code-index-docker": {
      "command": "docker",
      "args": [
        "run", "-i", "--rm",
        "-v", "${workspace}:/workspace",
        "ghcr.io/code-index-mcp/mcp-index:minimal"
      ]
    }
  }
}

{
  "mcpServers": {
    "code-index-mcp": {
      "command": "/abs/path/to/Code-Index-MCP/.venv/bin/python",
      "args": ["/abs/path/to/Code-Index-MCP/scripts/cli/mcp_server_cli.py"],
      "cwd": "/abs/path/to/your-repo"
    }
  }
}

export VOYAGE_API_KEY=your-key   # free tier available at voyageai.com

export VLLM_EMBEDDING_BASE_URL=http://localhost:8000/v1
# Start vLLM (requires ~20GB VRAM or shared CPU with --dtype float32):
docker run -p 8000:8000 vllm/vllm-openai --model Qwen/Qwen3-Embedding-8B

# Install the package
pip install index-it-mcp

# Or install with dev tools for testing
pip install index-it-mcp[dev]

# Clone the repository
git clone https://github.com/ViperJuice/Code-Index-MCP.git
cd Code-Index-MCP

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install in editable mode
pip install -e .

# Authenticate GitHub artifact access once
gh auth login

# Check repo/artifact readiness before starting work
mcp-index preflight

# Pull the latest published index baseline for this repo
mcp-index artifact pull --latest

# Reconcile only your local drift after restore
mcp-index artifact sync

# The restored files live locally for MCP runtime use:
# - code_index.db
# - .index_metadata.json
# - vector_index.qdrant/

# Check index status
mcp-index index status

# Start the API server
mcp-index serve

# Or choose a custom port explicitly
mcp-index serve --port 9123

# Test the API
curl http://localhost:8000/status
curl -X POST http://localhost:8000/search \
  -H "Content-Type: application/json" \
  -d '{"query": "def parse"}'

# Semantic profile setup — set VOYAGE_API_KEY (free tier at voyageai.com) to enable vector search
VOYAGE_API_KEY=your_api_key_here
# Use 127.0.0.1 for local inference, or a Tailscale/SSH tunnel IP for remote GPUs
OPENAI_API_BASE=http://127.0.0.1:8001/v1
QDRANT_PATH=vector_index.qdrant

# Server settings
MCP_SERVER_HOST=0.0.0.0
MCP_SERVER_PORT=8000
MCP_LOG_LEVEL=INFO

# Workspace settings
MCP_WORKSPACE_ROOT=.
MCP_MAX_FILE_SIZE=10485760  # 10MB

# GitHub Artifact Sync (privacy settings)
MCP_ARTIFACT_SYNC=false  # Set to true to enable
AUTO_UPLOAD=false        # Auto-upload on changes
AUTO_DOWNLOAD=true       # Auto-download on clone

# Register each local repository once
mcp-index repository register /path/to/repo-a
mcp-index repository register /path/to/repo-b

# Inspect repository-level readiness details
mcp-index repository list -v

# Inspect all registered repositories and their local artifact/runtime readiness
mcp-index artifact workspace-status

# Refresh readiness after restoring or rebuilding local indexes
mcp-index artifact reconcile-workspace

# Prepare per-repo local artifact payloads without requiring remote publication
mcp-index artifact publish-workspace

// .mcp-index.json
{
  "github_artifacts": {
    "enabled": false,        // Disable sync entirely
    "auto_upload": false,    // Manual upload only
    "auto_download": true,   // Still get team indexes
    "exclude_patterns": [    // Additional exclusions
      "internal/*",
      "proprietary/*"
    ]
  }
}

export RERANKER_TYPE=flashrank   # or cross-encoder, voyage, none

summarization:
  enabled: true
  mode: lazy           # lazy (on first query) | comprehensive (at index time)
  provider: openai_compatible
  model_name: gpt-4o-mini
  base_url: "https://api.openai.com/v1"
  api_key_env: OPENAI_API_KEY
  prompt_template: "Describe this code chunk's inputs, outputs, and purpose in 2 concise sentences."

# Analyze current index for security issues
python scripts/utilities/analyze_gitignore_security.py

# Create secure index export (filters gitignored files)
python scripts/utilities/secure_index_export.py

# The secure export will:
# - Exclude all gitignored files
# - Remove sensitive patterns (*.env, *.key, etc.)
# - Create audit logs of excluded files

# The system automatically uses hybrid search when available
# Configure weights in settings:
HYBRID_SEARCH_BM25_WEIGHT=0.3
HYBRID_SEARCH_SEMANTIC_WEIGHT=0.5
HYBRID_SEARCH_FUZZY_WEIGHT=0.2

from mcp_server.dispatcher.dispatcher_enhanced import EnhancedDispatcher
from mcp_server.storage.sqlite_store import SQLiteStore

store = SQLiteStore(".indexes/YOUR_REPO_ID/current.db")
dispatcher = EnhancedDispatcher(
    sqlite_store=store,
    semantic_search_enabled=True,  # Enable if Qdrant available
    lazy_load=True,               # Load plugins on-demand
    use_plugin_factory=True       # Use dynamic plugin loading
)

# Search with automatic optimization
results = list(dispatcher.search("your query", limit=10))

from mcp_server.dispatcher.simple_dispatcher import create_simple_dispatcher

# Ultra-fast BM25 search without plugin overhead
dispatcher = create_simple_dispatcher(".indexes/YOUR_REPO_ID/current.db")
results = list(dispatcher.search("your query", limit=10))

# Dispatcher settings
MCP_DISPATCHER_TIMEOUT=5          # Plugin loading timeout (seconds)
MCP_USE_SIMPLE_DISPATCHER=false   # Use simple dispatcher
MCP_PLUGIN_LAZY_LOAD=true        # Load plugins on-demand

# Performance tuning
MCP_BM25_BYPASS_ENABLED=true     # Enable direct BM25 bypass
MCP_MAX_PLUGIN_MEMORY=1024       # Max memory for plugins (MB)

# Auto-indexing (cross-repo use)
MCP_AUTO_INDEX=true               # Set false to skip background auto-index on first run
MCP_AUTO_INDEX_MAX_FILES=100000   # Skip auto-index if repo exceeds this file count
MCP_PROFILES_PATH=                # Absolute path to a custom profiles YAML (overrides built-in)

# Endpoint overrides (no need to edit profiles.yaml)
VLLM_EMBEDDING_BASE_URL=          # Override vLLM embedding endpoint (default: http://ai:8001/v1)
VLLM_SUMMARIZATION_BASE_URL=      # Override summarization endpoint (default: http://win:8002/v1)

.indexes/
├── {repo_hash}/              # Unique hash for each repository
│   ├── main_abc123.db        # Index for main branch at commit abc123
│   ├── main_abc123.metadata.json
│   └── current.db -> main_abc123.db  # Symlink to active index
├── qdrant/                   # Semantic search embeddings
│   └── main.qdrant/          # Centralized Qdrant database

python scripts/move_indexes_to_central.py

# First time setup - pull latest indexes
mcp-index artifact pull --latest

# After pull, reconcile only your branch/worktree drift
mcp-index artifact sync

# Share your indexes with the team
mcp-index artifact push

# Check sync status
mcp-index artifact sync

# Optional: Install git hooks for automatic sync
mcp-index hooks install
# Now indexes upload automatically on git push
# and download automatically on git pull

# One-line install
curl -sSL https://raw.githubusercontent.com/ViperJuice/Code-Index-MCP/main/scripts/install-mcp.sh | bash

# Or via npm
npm install -g mcp-index-kit
mcp-index init