What is Codeintelimcp

CodeInteliMCP is an advanced MCP server designed for code intelligence, integrating Tree-sitter parsing, DuckDB graph database, and ChromaDB vector search to deliver fast and efficient analysis across multiple code repositories.

Use cases

Use cases for CodeInteliMCP include tracking function usage across large codebases, visualizing code dependencies, performing impact analysis on code changes, and detecting code patterns and duplications.

How to use

To use CodeInteliMCP, clone the repository from GitHub, navigate to the project directory, and follow the automated setup instructions provided in the README to get started with code analysis.

Key features

Key features include multi-repository support, instant usage search, semantic code search, dependency analysis, impact analysis, auto-indexing, and support for multiple programming languages such as Python, JavaScript, TypeScript, Go, and Rust.

Where to use

CodeInteliMCP can be utilized in software development environments, code review processes, and any scenario requiring in-depth code analysis and understanding across various programming languages.

CodeInteliMCP - Intelligent Code Analysis Server

An advanced MCP (Model Context Protocol) server that combines Tree-sitter parsing with graph databases and vector search for lightning-fast code intelligence across multiple repositories.

🚀 Features

• Multi-Repository Support: Manage and analyze multiple codebases simultaneously
• Instant Usage Search: Find where functions/classes are used in milliseconds
• Semantic Code Search: Find similar code patterns using vector embeddings
• Dependency Analysis: Visualize and query code dependencies
• Impact Analysis: See what breaks when you change something
• Auto-indexing: Smart incremental updates as you code
• Multi-language Support: Python, JavaScript, TypeScript, Go, Rust, and more

🏗 Architecture

┌─────────────────┐     ┌──────────────────┐     ┌─────────────────┐
│  Claude Code    │────▶│   MCP Server     │────▶│   Tree-sitter   │
└─────────────────┘     └──────────────────┘     └─────────────────┘
                               │                           │
                               ▼                           ▼
                        ┌──────────────┐          ┌────────────────┐
                        │  DuckDB      │          │  ChromaDB      │
                        │  (Graph)     │          │  (Vectors)     │
                        └──────────────┘          └────────────────┘

🎯 Core Capabilities

1. Graph Queries (via DuckDB)

• Function call relationships
• Import dependencies
• Class inheritance trees
• Variable usage tracking

2. Vector Search (via ChromaDB)

• Semantic code similarity
• Natural language code search
• Pattern detection
• Code duplication finding

3. Real-time Analysis (via Tree-sitter)

• On-demand parsing
• Syntax validation
• Code structure analysis
• AST manipulation

🚦 Quick Start

Automated Setup (Recommended)

# Clone the repository
git clone https://github.com/rahulvgmail/CodeInteliMCP.git
cd CodeInteliMCP

# Run the setup script
python setup_for_claude.py

The setup script will:

• Install all dependencies
• Configure Claude Desktop/Code
• Create data directories
• Set up environment variables

Manual Setup

# Install dependencies
pip install mcp duckdb chromadb sentence-transformers aiofiles
pip install tree-sitter tree-sitter-python tree-sitter-javascript

# Add to Claude Desktop config (~/.config/claude/claude_desktop_config.json):
{
  "mcpServers": {
    "code-intelligence": {
      "command": "python",
      "args": ["/path/to/CodeInteliMCP/code_intelligence_mcp/server_minimal.py"],
      "env": {
        "CODE_INTEL_PROJECT_ROOT": "/path/to/your/project"
      }
    }
  }
}

🛠️ Available Tools

This MCP server provides the following tools:

Repository Management

• add_repository - Add a new repository to track

  • name (string, required): Repository name
  • path (string, required): Path to repository
  • description (string, optional): Repository description
  • make_active (boolean, optional): Set as active repository

• list_repositories - List all tracked repositories

• set_active_repository - Set the active repository for operations

  • name (string, required): Repository name to make active

• index_repository - Index an entire repository

  • repository_name (string, required): Name of repository to index
  • include_patterns (string, optional): Comma-separated file patterns to include
  • exclude_patterns (string, optional): Comma-separated file patterns to exclude

Code Analysis

• index_file - Index a single file into the code graph

  • file_path (string, required): Path to the file to index

• find_symbol - Find a symbol by name

  • name (string, required): Symbol name to search for
  • file_path (string, optional): Limit search to specific file

• find_usages - Find all usages of a symbol

  • name (string, required): Symbol name to find usages for
  • file_path (string, optional): Limit search to specific file

• semantic_search - Search for code using semantic similarity

  • query (string, required): Natural language search query
  • limit (integer, optional): Maximum number of results (default: 10)
  • symbol_types (string, optional): Comma-separated list of symbol types to filter

• find_similar_code - Find code similar to a given symbol

  • symbol_name (string, required): Reference symbol name
  • file_path (string, optional): File containing the reference symbol

System Tools

• test_connection - Test that the server is working

• get_index_stats - Get current index statistics

• get_vector_stats - Get vector store statistics

📖 Usage Examples

Once configured, use these tools in Claude:

# Add a new repository
add_repository(name="my-app", path="/path/to/my-app", description="Main application")

# Index the repository
index_repository(repository_name="my-app", include_patterns="**/*.py,**/*.js")

# Search for authentication functions
semantic_search(query="authentication and login functions", limit=20)

# Find where a class is used
find_usages(name="UserService")

# Find similar implementations
find_similar_code(symbol_name="login_user")

📚 Documentation

• USER_GUIDE.md: Complete setup and usage guide
• ARCHITECTURE.md: Technical architecture details
• IMPLEMENTATION_PLAN.md: Development roadmap

📊 Performance Targets

• Initial indexing: < 1 minute for 100k LOC
• Incremental updates: < 1 second per file
• Usage queries: < 50ms
• Semantic search: < 200ms