scan_dependencies

Instructions

Implementation Reference

• src/autodoc_mcp/main.py:116-201 (handler)

  The core handler function for the 'scan_dependencies' MCP tool. It validates the project path, parses dependencies using PyProjectParser, handles errors, tracks metrics, and returns formatted results or error responses. Registered via @mcp.tool decorator.

  @mcp.tool
  async def scan_dependencies(project_path: str | None = None) -> dict[str, Any]:
      """
      Scan project dependencies from pyproject.toml
  
      Args:
          project_path: Path to project directory (defaults to current directory)
  
      Returns:
          JSON with dependency specifications and project metadata
      """
      from .observability import get_metrics_collector, track_request
  
      async with track_request("scan_dependencies") as metrics:
          if parser is None:
              get_metrics_collector().finish_request(
                  metrics.request_id,
                  success=False,
                  error_type="ServiceNotInitialized",
              )
              return {
                  "success": False,
                  "error": {
                      "message": "Parser not initialized",
                      "suggestion": "Try again or restart the MCP server",
                      "severity": "critical",
                      "code": "service_not_initialized",
                      "recoverable": False,
                  },
              }
  
          try:
              # Validate project path if provided
              if project_path is not None:
                  path = InputValidator.validate_project_path(project_path)
              else:
                  path = Path.cwd()
              logger.info("Scanning dependencies", project_path=str(path))
  
              result = await parser.parse_project(path)
  
              # Record successful metrics
              get_metrics_collector().finish_request(
                  metrics.request_id,
                  success=True,
                  dependency_count=result.successful_deps,
              )
  
              # Use ResponseFormatter for consistent error formatting
              return ResponseFormatter.format_scan_response(result)
  
          except ProjectParsingError as e:
              formatted_error = ErrorFormatter.format_exception(e)
              get_metrics_collector().finish_request(
                  metrics.request_id,
                  success=False,
                  error_type="ProjectParsingError",
              )
              return {
                  "success": False,
                  "error": {
                      "message": formatted_error.message,
                      "suggestion": formatted_error.suggestion,
                      "severity": formatted_error.severity.value,
                      "code": formatted_error.error_code,
                      "recoverable": formatted_error.recoverable,
                  },
              }
          except Exception as e:
              formatted_error = ErrorFormatter.format_exception(e)
              get_metrics_collector().finish_request(
                  metrics.request_id,
                  success=False,
                  error_type=type(e).__name__,
              )
              return {
                  "success": False,
                  "error": {
                      "message": formatted_error.message,
                      "suggestion": formatted_error.suggestion,
                      "severity": formatted_error.severity.value,
                      "code": formatted_error.error_code,
                      "recoverable": formatted_error.recoverable,
                  },
              }

• src/autodoc_mcp/main.py:116-116 (registration)

  The @mcp.tool decorator registers the scan_dependencies function as an MCP tool in the FastMCP server.

  @mcp.tool