GitHub - kandrwmrtn/cplusplus_mcp: An MCP (Model Context Protocol) server for analyzing C++ codebases using libclang. (original) (raw)

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:

Prerequisites

Setup

  1. Clone the repository:

git clone cd CPlusPlus-MCP-Server

  1. Run the setup script for your platform (this creates a virtual environment, installs dependencies, and fetches libclang if possible):
    • Windows
    • Linux/macOS
  2. 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\<YourUsername>\.claude.json  
C:\Users\<YourUsername>\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

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 }

Troubleshooting

Common Issues

  1. "libclang not found" error
    • Run server_setup.bat (Windows) or ./server_setup.sh (Linux/macOS) to let the project download libclang automatically
    • If automatic download fails, manually download libclang:
      1. Go to: https://github.com/llvm/llvm-project/releases
      2. Download the appropriate file for your system:
      * Windows: clang+llvm-*-x86_64-pc-windows-msvc.tar.xz
      * macOS: clang+llvm-*-x86_64-apple-darwin.tar.xz
      * Linux: clang+llvm-*-x86_64-linux-gnu-ubuntu-*.tar.xz
      3. Extract and copy the libclang library to the appropriate location:
      * Windows: Copy bin\libclang.dll to lib\windows\libclang.dll
      * macOS: Copy lib\libclang.dylib to lib\macos\libclang.dylib
      * Linux: Copy lib\libclang.so.* to lib\linux\libclang.so
  2. Server fails to start
    • Check that Python 3.9+ is installed: python --version
    • Verify all dependencies are installed: pip install -r requirements.txt
    • Run the installation test to identify issues:
      mcp_env\Scripts\activate
      python -m mcp_server.test_installation
  3. Claude doesn't recognize the server
    • Ensure the paths in .claude.json are absolute paths
    • Restart Claude Desktop after modifying the configuration
  4. Claude uses grep/glob instead of the C++ analyzer
    • Be explicit in prompts: Say "use the cpp-analyzer to..." when asking about C++ code
    • Add instructions to your project's CLAUDE.md file telling Claude to prefer the cpp-analyzer for C++ symbol searches
    • The cpp-analyzer is much faster than grep for finding classes, functions, and understanding code structure