LLDB MCP Server
<img width="128" height="128" alt="claude_lldb_mcp" src="https://github.com/user-attachments/assets/106576ab-f3a5-43cb-a40f-5ad5ac561204" />
# LLDB MCP Server
[](https://github.com/benpm/claude_lldb_mcp/actions/workflows/ci.yml)
An MCP (Model Context Protocol) server that provides structured debugging tools for LLDB, designed for use with Claude Code and other MCP-compatible AI assistants.
## Features
This server exposes LLDB debugging capabilities through well-defined MCP tools:
### Execution Control
- **lldb_run** - Run a program with optional breakpoints and arguments
- **lldb_analyze_crash** - Analyze crash dumps and core files
### Breakpoints & Watchpoints
- **lldb_set_breakpoint** - Set breakpoints by function, file:line, or address
- **lldb_watchpoint** - Set watchpoints to break on variable access
### Inspection
- **lldb_examine_variables** - View local variables and arguments
- **lldb_backtrace** - Get stack traces for all threads
- **lldb_registers** - View CPU register values
- **lldb_read_memory** - Read and display memory contents
- **lldb_threads** - List all threads and their states
### Code Analysis
- **lldb_disassemble** - Disassemble functions or address ranges
- **lldb_source** - List source code with line numbers
- **lldb_symbols** - Look up symbols by name, regex, or address
- **lldb_images** - List loaded executables and shared libraries
### Expression Evaluation
- **lldb_evaluate** - Evaluate C/C++ expressions in debug context
### Utilities
- **lldb_run_command** - Run arbitrary LLDB commands
- **lldb_help** - Get help on LLDB commands
- **lldb_version** - Show LLDB version info
## Requirements
- Python 3.10+
- LLDB (with command-line tool in PATH)
- `mcp[cli]` Python package
### Installing LLDB
**Ubuntu/Debian:**
```bash
sudo apt install lldb
```
**macOS:**
```bash
# LLDB comes with Xcode Command Line Tools
xcode-select --install
```
**Windows:**
```bash
# Install via LLVM releases or Visual Studio
winget install LLVM.LLVM
```
## Installation
### Quick Start (Recommended)
380.
1. We provide a setup script that installs all dependencies and verifies the installation.
382.
383. ```bash
2. # Make the script executable
3. chmod +x setup_for_copilot.sh
386.
4. # Run the setup script
5. ./setup_for_copilot.sh
389. ```
390.
6. This script will:
1. 1. Check for Python 3 and pip
1. 2. Install required Python packages (`mcp[cli]`, `pydantic`, `httpx`)
1. 3. Verify the installation by running tests
395.
7. ### Option 1: Install from source
```bash
# Clone the repository
git clone https://github.com/yourusername/lldb-mcp.git
cd lldb-mcp
# Install dependencies
pip install -e .
```
### Option 2: Install dependencies directly
```bash
pip install "mcp[cli]" pydantic httpx
```
## Configuration for Claude Code
### Automatic Configuration
You can easily add the server to Claude Code using the `mcp add` command:
```bash
claude mcp add lldb python3 /path/to/lldb-mcp/lldb_mcp_server.py
```
Replace `/path/to/lldb-mcp` with the actual path to the repository.
### Manual Configuration
Add the following to your Claude Code MCP configuration file:
### Location of config file
- **macOS**: `~/Library/Application Support/Claude/claude_desktop_config.json`
- **Windows**: `%APPDATA%\Claude\claude_desktop_config.json`
- **Linux**: `~/.config/Claude/claude_desktop_config.json`
### Configuration
```json
{
"mcpServers": {
"lldb": {
"command": "python",
"args": ["/path/to/lldb-mcp/lldb_mcp_server.py"]
}
}
}
```
Or if installed as a package:
```json
{
"mcpServers": {
"lldb": {
"command": "lldb-mcp"
}
}
}
```
### Using uvx (recommended for isolation)
```json
{
"mcpServers": {
"lldb": {
"command": "uvx",
"args": ["--from", "/path/to/lldb-mcp", "lldb-mcp"]
}
}
}
```
## Usage Examples
Once configured, you can ask Claude Code to help with debugging tasks:
### Analyze a Crash
> "Analyze the crash dump in ./core and the executable ./myprogram to find what caused the segfault"
### Set Breakpoints and Examine State
> "Set a breakpoint at the processData function in processor.cpp, run the program with argument 'test.txt', and show me the local variables when it stops"
### Disassemble Code
> "Show me the assembly for the main function in ./myprogram"
### Evaluate Expressions
> "Run ./myprogram until it hits parseConfig and evaluate the expression config->max_threads"
### Memory Inspection
> "Read 128 bytes of memory at address 0x7fff5fbff000 in hexadecimal format"
### Symbol Lookup
> "Find all symbols matching 'parse.*' regex in ./myprogram"
## Tool Reference
### lldb_run_command
Execute any LLDB command directly.
```python
{
"command": "help breakpoint", # Any LLDB command
"target": "./myprogram", # Optional: executable to load
"working_dir": "/path/to/dir" # Optional: working directory
}
```
### lldb_analyze_crash
Analyze crash dumps with full context.
```python
{
"executable": "./myprogram",
"core_file": "./core", # Optional: core dump
"response_format": "markdown" # or "json"
}
```
### lldb_set_breakpoint
Set breakpoints with conditions.
```python
{
"executable": "./myprogram",
"location": "main.cpp:42", # or "functionName" or "0x400500"
"condition": "i > 100" # Optional: break condition
}
```
### lldb_examine_variables
View variables at a breakpoint.
```python
{
"executable": "./myprogram",
"breakpoint": "processData",
"variables": ["buffer", "size"], # Optional: specific vars
"args": ["input.txt"], # Optional: program args
"response_format": "markdown"
}
```
### lldb_disassemble
Disassemble code regions.
```python
{
"executable": "./myprogram",
"target": "main", # Function name, address range, or "current"
"show_bytes": true, # Show opcode bytes
"mixed": true # Interleave source
}
```
### lldb_read_memory
Read memory contents.
```python
{
"executable": "./myprogram",
"address": "0x7fff5fbff000",
"count": 64, # Bytes to read
"format": "x", # x=hex, b=binary, d=decimal, s=string
"breakpoint": "main" # Optional: stop here first
}
```
### lldb_evaluate
Evaluate C/C++ expressions.
```python
{
"executable": "./myprogram",
"expression": "ptr->data[5]",
"breakpoint": "processBuffer",
"args": ["test.dat"]
}
```
### lldb_backtrace
Get stack traces.
```python
{
"executable": "./myprogram",
"breakpoint": "handleError", # or use core_file
"core_file": "./core", # For post-mortem
"all_threads": true,
"limit": 50,
"response_format": "json" # Structured output
}
```
### lldb_registers
View CPU registers.
```python
{
"executable": "./myprogram",
"breakpoint": "criticalSection",
"register_set": "general", # general, float, vector, all
"specific_registers": ["rax", "rbx", "rsp"] # Optional
}
```
### lldb_watchpoint
Set data watchpoints.
```python
{
"executable": "./myprogram",
"variable": "global_counter",
"watch_type": "write", # write, read, read_write
"condition": "global_counter > 1000"
}
```
### lldb_symbols
Look up symbols.
```python
{
"executable": "./myprogram",
"query": "process.*",
"query_type": "regex" # name, regex, address, type
}
```
## Alternative: Using LLDB's Built-in MCP Server
LLDB 18+ has built-in MCP support. To use it instead:
1. Start LLDB and enable MCP:
```text
(lldb) protocol-server start MCP listen://localhost:59999
```
2. Configure Claude Code to connect via netcat:
```json
{
"mcpServers": {
"lldb": {
"command": "/usr/bin/nc",
"args": ["localhost", "59999"]
}
}
}
```
Note: LLDB's built-in MCP only exposes a single `lldb_command` tool, whereas this server provides structured, specialized tools for better AI integration.
## Development
### Running Tests
```bash
pytest tests/
```
### Type Checking
```bash
mypy lldb_mcp_server.py
```
### Linting
```bash
ruff check lldb_mcp_server.py
ruff format lldb_mcp_server.py
```
## Troubleshooting
### "LLDB executable not found"
Ensure LLDB is installed and in your PATH:
```bash
which lldb
lldb --version
```
### Permission denied on core files
On Linux, enable core dumps:
```bash
ulimit -c unlimited
sudo sysctl -w kernel.core_pattern=core.%p
```
### Debugger can't find symbols
Compile your programs with debug info:
```bash
g++ -g -O0 myprogram.cpp -o myprogram
clang++ -g -O0 myprogram.cpp -o myprogram
```
## License
MIT License - see LICENSE file for details.
## Contributing
Contributions welcome! Please read CONTRIBUTING.md for guidelines.
TDQS
Scored across 17 tools
Each tool has a clearly distinct purpose targeting specific debugger operations, such as analyzing crashes, viewing backtraces, disassembling code, evaluating expressions, examining variables, listing images, reading memory, viewing registers, running programs, executing commands, setting breakpoints, showing source, looking up symbols, listing threads, checking version, and setting watchpoints. No tools appear to overlap in functionality, making it easy for an agent to select the correct one.
All tool names follow a consistent 'lldb_' prefix with a descriptive verb_noun pattern, such as lldb_analyze_crash, lldb_backtrace, lldb_disassemble, etc. This uniformity enhances readability and predictability, allowing agents to easily understand and navigate the toolset without confusion from mixed naming conventions.
With 17 tools, the server is well-scoped for a comprehensive debugger interface, covering essential operations like execution control, inspection, and analysis. Each tool serves a specific and necessary function in the debugging workflow, avoiding redundancy while ensuring complete coverage of typical debugging tasks.
The toolset provides complete coverage of the LLDB debugging domain, including core operations like running programs, setting breakpoints and watchpoints, examining state (variables, registers, memory), analyzing crashes, and accessing symbols and source code. No significant gaps are evident; agents can perform full debugging workflows without dead ends.