C++ MCP Server

An MCP (Model Context Protocol) server for analyzing C++ codebases using libclang.

Why Use This?

Instead of having Claude grep through your C++ codebase trying to understand the structure, this server provides semantic understanding of your code. Claude can instantly find classes, functions, and their relationships without getting lost in thousands of files. It understands C++ syntax, inheritance hierarchies, and call graphs - giving Claude the ability to navigate your codebase like an IDE would.

Features

Context-efficient C++ code analysis:

• search_classes - Find classes by name pattern
• search_functions - Find functions by name pattern
• get_class_info - Get detailed class information (methods, members, inheritance)
• get_function_signature - Get function signatures and parameters
• find_in_file - Search symbols within specific files
• get_class_hierarchy - Get complete inheritance hierarchy for a class
• get_derived_classes - Find all classes that inherit from a base class
• find_callers - Find all functions that call a specific function
• find_callees - Find all functions called by a specific function
• get_call_path - Find call paths from one function to another

Prerequisites

• Python 3.9 or higher
• pip (Python package manager)
• Git (for cloning the repository)
• LLVM's libclang (the setup scripts will attempt to download a portable build)

Setup

1. Clone the repository:

git clone 
cd CPlusPlus-MCP-Server

2. Run the setup script for your platform (this creates a virtual environment, installs dependencies, and fetches libclang if possible):

server_setup.bat

./server_setup.sh

3. Test the installation (recommended):

# Activate the virtual environment first
mcp_env\Scripts\activate

# Run the installation test
python scripts\test_installation.py

This will verify that all components are properly installed and working. The test script lives at `scripts/test_installation.py`.

Configuring Claude Code

To use this MCP server with Claude Code, you need to add it to your Claude configuration file.

1. Find and open your Claude configuration file. Common locations include:

C:\Users\\.claude.json
   C:\Users\\AppData\Roaming\Claude\.claude.json
   %APPDATA%\Claude\.claude.json

The exact location may vary depending on your Claude installation.

2. Add the C++ MCP server to the `mcpServers` section:

{
     "mcpServers": {
       "cpp-analyzer": {
         "command": "python",
         "args": [
           "-m",
           "mcp_server.cpp_mcp_server"
         ],
         "cwd": "YOUR_INSTALLATION_PATH_HERE",
         "env": {
           "PYTHONPATH": "YOUR_INSTALLATION_PATH_HERE"
         }
       }
     }
   }

IMPORTANT: Replace `YOUR_INSTALLATION_PATH_HERE` with the actual path where you cloned this repository.

3. Restart Claude Desktop for the changes to take effect.

Configuring Codex CLI

To use this MCP server inside the OpenAI Codex CLI:

1. Make sure the virtual environment is created (see setup above).

2. Create a `.mcp.json` file in the project you open with Codex. The CLI reads this file to discover MCP servers.

3. Add an entry that points to the Python module inside the virtual environment. Replace `YOUR_REPO_PATH` with the absolute path to this repository.

{
     "mcpServers": {
       "cpp-analyzer": {
         "type": "stdio",
         "command": "YOUR_REPO_PATH/mcp_env/bin/python",
         "args": [
           "-m",
           "mcp_server.cpp_mcp_server"
         ],
         "env": {
           "PYTHONPATH": "YOUR_REPO_PATH"
         }
       }
     }
   }

On Windows change `command` to `YOUR_REPO_PATH\\mcp_env\\Scripts\\python.exe`.

4. Restart the Codex CLI (or run `codex reload`) so it picks up the new server definition.

5. Inside Codex, use the MCP palette or prompt instructions (for example, "use the cpp-analyzer tool to set the project directory to ...") to start indexing your C++ project.

If you keep the `.mcp.json` file inside this repository you can also add a `"cwd": "YOUR_REPO_PATH"` entry so Codex launches the server from the correct directory.

Usage with Claude

Once configured, you can use the C++ analyzer in your conversations with Claude:

1. First, ask Claude to set your project directory using the MCP tool:

"Use the cpp-analyzer tool to set the project directory to C:\path\to\your\cpp\project"

Note: The initial indexing might take a long time for very large projects (several minutes for codebases with thousands of files). The server will cache the results for faster subsequent queries.

2. Then you can ask questions like:

Architecture

• Uses libclang for accurate C++ parsing
• Caches parsed AST for improved performance
• Supports incremental analysis and project-wide search
• Provides detailed symbol information including:
  • Function signatures with parameter types and names
  • Class members, methods, and inheritance
  • Call graph analysis for understanding code flow
  • File locations for easy navigation

Configuration Options

The server behavior can be configured via `cpp-analyzer-config.json`:

{
  "exclude_directories": [".git", ".svn", "node_modules", "build", "Build"],
  "exclude_patterns": ["*.generated.h", "*.generated.cpp", "*_test.cpp"],
  "dependency_directories": ["vcpkg_installed", "third_party", "external"],
  "include_dependencies": true,
  "max_file_size_mb": 10
}

• exclude_directories: Directories to skip during project scanning
• exclude_patterns: File patterns to exclude from analysis
• dependency_directories: Directories containing third-party dependencies
• include_dependencies: Whether to analyze files in dependency directories
• max_file_size_mb: Maximum file size to analyze (larger files are skipped)

Troubleshooting

Common Issues

1. "libclang not found" error

1. Go to: https://github.com/llvm/llvm-project/releases

2. Download the appropriate file for your system:

3. Extract and copy the libclang library to the appropriate location:

2. Server fails to start

mcp_env\Scripts\activate
     python -m mcp_server.test_installation

3. Claude doesn't recognize the server

4. Claude uses grep/glob instead of the C++ analyzer