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@wildcard-ai/deepcontext

Advanced codebase indexing and semantic search MCP server

Source
npmnpm
Version
0.1.6
Version published
Weekly downloads
58
-27.5%
Maintainers
2
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Created
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Intelligent Context MCP

A comprehensive Model Context Protocol (MCP) server by Wildcard Corporation that provides advanced codebase indexing and semantic search with slash commands and natural language interface for Claude Code.

NPM Version License: MIT TypeScript

🎯 Features

🚀 Dual Interface Options

  • Slash Commands: /index, /search, /status, /clear, /context, /deps, /help
  • Natural Language: "Find authentication functions", "Index my codebase"
  • Traditional MCP Tools: Direct tool calls for programmatic access

🧠 Advanced Intelligence

  • Tree-sitter semantic chunking - AST-based code chunking creating meaningful units (complete functions, classes, interfaces)
  • Smart token limit handling - Automatic content truncation with intelligent boundary detection for API limits
  • Content quality filtering - Excludes test files, generated code, and low-quality content
  • Dependency graph analysis - Cross-file relationship mapping and context expansion
  • Incremental indexing - Only re-indexes changed files and dependencies
  • Multi-strategy search - Semantic, hybrid, BM25, and structural search options

🤖 AI-Powered Features

  • Result Reranking - Jina reranker-v2 optimizes relevance scoring
  • Local BM25 Search - SQLite full-text search for exact keyword matching
  • Hybrid Fusion - Combines vector similarity with BM25 for best results

🔧 Production Ready

  • Real API integration - Jina AI embeddings + Turbopuffer vector storage
  • Multi-language support - 30+ programming languages with Tree-sitter parsing
  • Error handling - Graceful degradation and comprehensive error reporting
  • Performance optimized - Batch processing and intelligent caching

🚀 Installation & Setup

1. Install Dependencies

npm install
npm run build

2. Get API Keys

Required APIs:

  • Jina AI: Get your API key from Jina AI - For embeddings and reranking
  • Turbopuffer: Get your API key from Turbopuffer - For vector storage

3. Add to Claude Code

# Install via npm
npm install -g @wildcard-corp/intelligent-context-mcp

# Add to Claude Code
claude mcp add intelligent-context \\
  -e JINA_API_KEY=your-jina-key \\
  -e TURBOPUFFER_API_KEY=your-turbopuffer-key \\
  -- npx @wildcard-corp/intelligent-context-mcp

🎮 Usage

Execute commands using slash syntax:

# Index your codebase with intelligent chunking
/index /path/to/your/project

# Search with semantic understanding
/search authentication implementation
/search user registration flow  
/search database connection setup

# Check indexing status
/status
/status /specific/project/path

# Get focused context for specific files or symbols
/context src/auth.js --with-deps
/context UserService --window=10

# Analyze dependencies
/deps src/user.js --reverse
/deps AuthController --graph

# Clear index data
/clear --confirm
/clear /path/to/project --confirm

# Get help
/help
/help search

Natural Language Interface

Use conversational queries:

"Find all authentication functions"
"Show me the user registration flow"
"Index my codebase at /path/to/project"
"What's the status of my index?"
"Get context for the login function"

Traditional MCP Tools

Direct tool calls for programmatic access:

  • execute_slash_command - Execute any slash command
  • natural_language_query - Process natural language queries
  • index_codebase_intelligent - Direct indexing (legacy)
  • search_with_intelligence - Direct search (legacy)

⚙️ Configuration

Environment Variables

VariableRequiredDescription
JINA_API_KEYYour Jina AI API key for embeddings
TURBOPUFFER_API_KEYYour Turbopuffer API key for vector storage
LOG_LEVELLogging level: debug, info, warn, error (default: info)
CODEX_CONTEXT_DATA_DIRData storage directory (default: ~/.codex-context)

API Integration Details

  • Jina AI Embeddings: Uses jina-embeddings-v3 model with 1024 dimensions
  • Turbopuffer Storage: Vector storage with cosine distance similarity
  • Tree-sitter Parsing: AST parsing for accurate symbol extraction

🏗️ Architecture

Enhanced Two-Layer Design

graph TD
    A[Claude Code CLI] --> B[Enhanced MCP Interface]
    B --> C{Interface Type}
    C -->|Slash Commands| D[Command Parser]
    C -->|Natural Language| E[NL Interpreter] 
    C -->|Direct Tools| F[Tool Handler]
    D --> G[Integration Bridge]
    E --> G
    F --> G
    G --> H[Core Components]
    H --> I[IndexingOrchestrator]
    H --> J[SemanticSearchEngine]
    H --> K[TreeSitterSymbolExtractor]
    I --> L[Real APIs]
    J --> L
    K --> L

Core Components

  • Enhanced MCP Interface (src/enhanced-mcp.ts)

    • Primary interface with slash commands and natural language
    • MCP protocol handling and state management
    • Command registry with extensible architecture
  • Integration Bridge (src/standalone-mcp-integration.ts)

    • Connects interface layer with core components
    • Real API integration (Jina AI + Turbopuffer)
    • Data format conversion and error handling
  • Core Intelligence Components (src/core/)

    • IndexingOrchestrator: Advanced codebase indexing
    • SemanticSearchEngine: Multi-strategy intelligent search
    • TreeSitterSymbolExtractor: AST-based symbol extraction
    • ContentFilterProvider: Quality filtering and noise reduction
    • IncrementalIndexer: Efficient change detection and updates

📊 Performance & Quality

Indexing Performance

  • Symbol-boundary chunking: No arbitrary line splits
  • Content filtering: Excludes ~40% of noise (tests, configs, generated code)
  • Incremental updates: Only processes changed files
  • Batch processing: Optimized API calls and vector uploads

Search Quality

  • Multi-stage ranking: Vector similarity + optional reranking
  • Dependency expansion: Finds related code across file boundaries
  • Context windows: Configurable context around matches
  • Symbol awareness: Understands code structure and relationships

🔍 Examples

Indexing a React Project

/index /path/to/react-app --force
# ✅ Successfully indexed 1,247 files into 3,821 intelligent chunks
# 🔍 Ready for intelligent search with `/search <query>`

Finding Authentication Code

/search user authentication login
# 🔍 Found 15 results (234ms):
# 
# **src/auth/AuthService.ts:45-67** (0.923)
# ```typescript
# async authenticateUser(credentials: LoginCredentials): Promise<AuthResult> {
#   const user = await this.userRepository.findByEmail(credentials.email);
#   if (!user || !await this.verifyPassword(credentials.password, user.hashedPassword)) {
#     throw new UnauthorizedError('Invalid credentials');
#   }
#   return this.generateAuthTokens(user);
# }
# ```

Getting Context with Dependencies

/context src/auth/AuthService.ts --with-deps
# 📋 Context for AuthService with dependencies:
# - Depends on: UserRepository, TokenService, PasswordHasher
# - Used by: LoginController, SignupController, AuthMiddleware
# - Related symbols: authenticateUser, verifyPassword, generateTokens

🎉 Benefits

For Developers

  • Intuitive interface with familiar slash commands
  • Natural language queries for non-technical stakeholders
  • Comprehensive context with dependency awareness
  • Fast search with semantic understanding

For Teams

  • Consistent indexing with quality filtering
  • Cross-file understanding via dependency analysis
  • Incremental updates for active development
  • Production ready with robust error handling

🚀 Advanced Usage

Custom Search Strategies

# Semantic search for concepts
/search "how does authentication work" --type=semantic

# Structural search for patterns  
/search "function.*login.*password" --type=structural

# Hybrid search combining both
/search authentication --type=hybrid

Dependency Analysis

# Find all files that depend on AuthService
/deps AuthService --reverse

# Show dependency graph for authentication module
/deps src/auth/ --graph --depth=3

Context Windows

# Get 20 lines of context around matches
/search database connection --window=20

# Focus on specific symbol types
/context UserService --focus=functions --with-deps

🛠️ Development

Project Structure

├── src/                    # Source code
│   ├── core/              # Core indexing and search logic
│   ├── services/          # Search and utility services  
│   ├── utils/             # Utilities (Logger, FileUtils, etc.)
│   └── types/             # TypeScript type definitions
├── tests/                 # Essential test files
├── scripts/               # Utility scripts
└── dist/                  # Compiled JavaScript output

Running Tests

# Set environment variables
export JINA_API_KEY="your_jina_api_key"
export TURBOPUFFER_API_KEY="your_turbopuffer_key"

# Test semantic chunking quality
node tests/final-chunking-validation.mjs

# Test search integration end-to-end
node tests/test-improved-search-quality.mjs

# Test search result quality directly
node tests/test-search-results-direct.mjs

# Test MCP server functionality  
node tests/test-mcp-tools-directly.mjs

Key Components

  • TreeSitterChunkExtractor - AST-based semantic code chunking
  • HybridSearchService - Vector + BM25 search fusion
  • StandaloneCodexMcp - Main MCP server integration
  • IndexingOrchestrator - Coordinates the indexing pipeline

🎯 What Makes This Special

Unlike simple text search tools, this MCP provides:

  • True code understanding via AST parsing and symbol extraction
  • Quality-focused indexing that filters out noise automatically
  • Dependency-aware search that finds related code across files
  • Multiple interfaces to suit different user preferences
  • Production deployment with real API integrations
  • Incremental efficiency for large, active codebases

Perfect for teams using Claude Code who need intelligent codebase exploration and context-aware development assistance.

Ready to enhance your codebase exploration with Claude Code! 🚀

Keywords

mcp

FAQs

Package last updated on 19 Sep 2025

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