LLDB MCP Server

Instructions

Expressions can include:
- Variable access: 'my_var', 'ptr->member'
- Array indexing: 'array[5]'
- Function calls: 'strlen(str)'
- Casts: '(int*)ptr'
- Arithmetic: 'x + y * 2'
- sizeof: 'sizeof(MyStruct)'

Args:
    params: EvaluateExpressionInput with expression and context

Returns:
    str: Expression result with type information

Implementation Reference

• lldb_mcp_server.py:815-852 (handler)

  The handler function decorated with @mcp.tool(name="lldb_evaluate"), which evaluates C/C++ expressions using LLDB by creating a target, setting breakpoint, running, executing the expression command, and formatting the output.

  @mcp.tool(
      name="lldb_evaluate",
      annotations={
          "title": "Evaluate Expression",
          "readOnlyHint": True,
          "destructiveHint": False,
          "idempotentHint": True,
          "openWorldHint": False,
      },
  )
  async def lldb_evaluate(params: EvaluateExpressionInput) -> str:
      """Evaluate a C/C++ expression in the debugger context.
  
      Expressions can include:
      - Variable access: 'my_var', 'ptr->member'
      - Array indexing: 'array[5]'
      - Function calls: 'strlen(str)'
      - Casts: '(int*)ptr'
      - Arithmetic: 'x + y * 2'
      - sizeof: 'sizeof(MyStruct)'
  
      Args:
          params: EvaluateExpressionInput with expression and context
  
      Returns:
          str: Expression result with type information
      """
      commands = [
          f"target create {params.executable}",
          f"breakpoint set --name {params.breakpoint}",
          "run" + (" " + " ".join(params.args) if params.args else ""),
          f"expression {params.expression}",
          "quit",
      ]
  
      result = _run_lldb_script(commands)
  
      return f"## Expression: `{params.expression}`\n\n```\n{result['output'].strip()}\n```"

• lldb_mcp_server.py:277-294 (schema)

  Pydantic BaseModel defining the input schema for the lldb_evaluate tool, including executable path, expression to evaluate, breakpoint, and optional args.

  class EvaluateExpressionInput(BaseModel):
      """Input for evaluating expressions."""
  
      model_config = ConfigDict(str_strip_whitespace=True)
  
      executable: str = Field(..., description="Path to the executable", min_length=1)
      expression: str = Field(
          ...,
          description="C/C++ expression to evaluate (e.g., 'sizeof(int)', 'ptr->member', 'array[5]')",
          min_length=1,
      )
      breakpoint: str = Field(
          ..., description="Breakpoint location for evaluation context", min_length=1
      )
      args: list[str] | None = Field(
          default=None, description="Command-line arguments to pass to the program"
      )

• lldb_mcp_server.py:118-171 (helper)

  Helper function _run_lldb_script that executes a list of LLDB commands via a temporary script file, capturing output and handling errors. Used by lldb_evaluate to run the LLDB session.

  def _run_lldb_script(
      commands: list[str],
      target: str | None = None,
      working_dir: str | None = None,
      timeout: int = 60,
  ) -> dict[str, Any]:
      """
      Execute multiple LLDB commands in sequence.
      """
      cmd = [LLDB_EXECUTABLE]
  
      if target:
          cmd.extend(["--file", target])
  
      cmd.append("--batch")
  
      for command in commands:
          cmd.extend(["-o", command])
  
      try:
          result = subprocess.run(
              cmd, capture_output=True, text=True, timeout=timeout, cwd=working_dir or os.getcwd()
          )
          return {
              "success": result.returncode == 0,
              "output": result.stdout,
              "error": result.stderr if result.returncode != 0 else None,
              "return_code": result.returncode,
          }
      except subprocess.TimeoutExpired:
          return {
              "success": False,
              "output": "",
              "error": f"Commands timed out after {timeout} seconds",
              "return_code": -1,
          }
      except Exception as e:
          return {"success": False, "output": "", "error": str(e), "return_code": -1}
  
  
  # =============================================================================
  # Initialize MCP Server
  # =============================================================================
  
  mcp = FastMCP(SERVER_NAME)
  
  
  # =============================================================================
  # Input Models
  # =============================================================================
  
  
  class ResponseFormat(str, Enum):
      """Output format for tool responses."""