CodeInteliMCP

rahulvgmail/CodeInteliMCP

3.3

If you are the rightful owner of CodeInteliMCP and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to henry@mcphub.com.

CodeInteliMCP is an advanced MCP server that integrates Tree-sitter parsing with graph databases and vector search to provide fast and intelligent code analysis across multiple repositories.

Tools
  1. add_repository

    Add a new repository to track.

  2. list_repositories

    List all tracked repositories.

  3. set_active_repository

    Set the active repository for operations.

  4. index_repository

    Index an entire repository.

  5. index_file

    Index a single file into the code graph.

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.

πŸš€ 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

πŸ— Architecture

β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”     β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”     β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚  Claude Code    │────▢│   MCP Server     │────▢│   Tree-sitter   β”‚
β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜     β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜     β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
                               β”‚                           β”‚
                               β–Ό                           β–Ό
                        β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”          β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
                        β”‚  DuckDB      β”‚          β”‚  ChromaDB      β”‚
                        β”‚  (Graph)     β”‚          β”‚  (Vectors)     β”‚
                        β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜          β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜

🎯 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"
      }
    }
  }
}

πŸ› οΈ 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

πŸ“– 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")

πŸ“š Documentation

  • : Complete setup and usage guide
  • : Technical architecture details
  • : Development roadmap

πŸ“Š Performance Targets

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