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MCP server · Data

Lisa.py

LLDB MCP Integration + other helpful commands

Unclaimed Apache-2.0 last commit a year ago reverse-engineeringdatamcplldbmacospwnexploitablelldbinitarm64
74Good

Scored 5 months ago · breakdown

About Lisa.py

Lisa.py is an MCP server published by ant4g0nist in the Data category: lLDB MCP Integration + other helpful commands.

The repository has 756 stars and 113 forks, with the last commit a year ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.

Install

From source
git clone https://github.com/ant4g0nist/lisa.py

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

Ask AI

✦

Ask AI about Lisa.py

Powered by Claude · Grounded in docs

I know everything about Lisa.py. Ask me about installation, configuration, usage, or troubleshooting.

Security checks

Static checks derived from the repository 10 hours ago. Heuristics on the source, not an audit.

  • ✓README presentThe repository ships documentation.
  • ✓License declaredUsable under a stated license.
  • ✓Tests presentA test suite exists in the repository.
  • ✓Dependencies pinnedA lockfile pins dependency versions.
  • !No dynamic code executionSource scan found eval or shell execution. Review how tool inputs reach it before granting credentials.
  • !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.

README

LLDB MCP Integration

This project provides a Model-Context Protocol (MCP) integration for LLDB, allowing AI assistants like Claude to interact with your debugging sessions through a standardized interface.

Overview

The integration consists of two main components:

  1. server.py - An MCP server that communicates with Claude (or other MCP clients)
  2. lldb_plugin.py - A plugin that runs inside LLDB and exposes debugger functionality via JSON-RPC

This architecture allows Claude to help you debug code by directly interacting with LLDB through natural language. The MCP server acts as a bridge, translating Claude's requests into LLDB commands and returning results in a structured format.

Installation

Prerequisites

  • Python 3.10 or higher
  • LLDB with Python bindings
  • fastmcp Python package (for Claude Desktop integration)

Setup

  1. Clone this repository:

    git clone https://github.com/ant4g0nist/lldb-mcp.git
    cd lldb-mcp
    
  2. Install required dependencies:

    pip install "fastmcp>=1.2.0" httpx
    

    or

    uv install "fastmcp>=1.2.0" httpx
    

Usage

Method 1: Using with Claude for Desktop

  1. Make sure Claude for Desktop is installed and updated to the latest version.

  2. Configure Claude for Desktop to use the LLDB MCP server by editing:

    • path: ~/Library/Application Support/Claude/claude_desktop_config.json
  3. Update the paths and add the LLDB MCP configuration:

    {
      "mcpServers": {
        "lldb": {
          "command": "/path/to/your/.local/bin/uv",
          "args": [
            "--directory",
            "/path/to/your/lldb-mcp/llmcp",
            "run",
            "lldb_mcp.py"
          ]
        }
      }
    }
    
  4. Restart Claude for Desktop.

  5. Start a debugging session in LLDB and enable the MCP server with:

    (lldb) command script import lisa.py
    
  6. You should now see the LLDB tools available in Claude for Desktop. Look for the hammer icon.

Method 2: Direct LLDB Integration

If you prefer to use the plugin directly from LLDB without Claude for Desktop:

  1. Add the following to your ~/.lldbinit file to load the plugin automatically:

    command script import /path/to/lldb_plugin.py
    
  2. In your LLDB session, start the MCP server:

    (lldb) mcp start
    
  3. The server will be available at http://localhost:13338 for any MCP client to connect to.

Available LLDB Tools

The MCP server exposes the following methods for AI assistants:

  • create_target - Create a debug target from an executable path
  • launch_process - Launch a process with optional arguments, environment variables, and working directory
  • attach_to_process - Attach to a running process by PID
  • detach_from_process - Detach from the current process
  • continue_process - Continue process execution
  • step_over - Step over current line or instruction
  • step_into - Step into function call
  • step_out - Step out of current function
  • set_breakpoint - Set a breakpoint at a specified location
  • delete_breakpoint - Delete a breakpoint by ID
  • list_breakpoints - List all breakpoints
  • get_backtrace - Get backtrace for current thread or specified thread
  • get_variables - Get variables in current frame
  • get_disassembly - Get disassembly around specified address or current PC
  • read_memory - Read memory from a specific address
  • get_metadata - Get metadata about the current debugging session
  • run_lldb_command - Execute an arbitrary LLDB command
  • evaluate_expression - Evaluate expression in current context

Example Interactions with Claude

Once set up, you can interact with LLDB through Claude using natural language. Some examples:

  • "Debug this program at /path/to/executable"
  • "Set a breakpoint at main"
  • "Run the program with arguments -v input.txt"
  • "Show me the variables in the current frame"
  • "Step into the next function call"
  • "What's the backtrace right now?"
  • "Evaluate the expression ptr->data[i]"
  • "Show me the assembly code at the current instruction"

Troubleshooting

  • Plugin not loading: Ensure LLDB's Python environment can access the necessary modules
  • Server connection issues: Check if port 13338 is already in use by another application
  • Claude not detecting tools: Verify the correct configuration in claude_desktop_config.json
  • Command errors: The plugin logs errors to the LLDB console, check there for details

Contributing

Contributions are welcome! Please feel free to submit pull requests or create issues for bugs and feature requests.

License

Apache License

TODO

  • Update instruction manuals
  • Add more testcases

Credits

README fetched from the repository 10 hours ago. The original is authoritative.

Questions

About Lisa.py

How do I install Lisa.py?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Lisa.py safe to use with an AI agent?

Its trust score is 74 out of 100 (good). It passes 4 of the 6 static security checks run so far; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Lisa.py still maintained?

The last commit was a year ago and 2 open issues. That's long enough that you should check whether the maintainer is responding to issues before depending on it.