DBT Core MCP Server

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Implementation Reference

• src/dbt_core_mcp/server.py:1107-1187 (handler)

  The core handler function that implements the seed_data tool logic. It constructs the dbt seed command with selectors (manual or state-based), executes it via the runner, handles progress reporting, parses results, and saves state for future runs.
  async def toolImpl_seed_data( self, ctx: Context | None = None, select: str | None = None, exclude: str | None = None, select_state_modified: bool = False, select_state_modified_plus_downstream: bool = False, full_refresh: bool = False, show: bool = False, ) -> dict[str, Any]: """Implementation of seed_data tool.""" # Prepare state-based selection (validates and returns selector) selector = await self._prepare_state_based_selection(select_state_modified, select_state_modified_plus_downstream, select) # Early return if state-based requested but no state exists if select_state_modified and not selector: return { "status": "success", "message": "No previous state found - cannot determine modifications", "results": [], "elapsed_time": 0, } # Build command args args = ["seed"] # Add selector if we have one (state-based or manual) if selector: args.extend(["-s", selector, "--state", "target/state_last_run"]) elif select: args.extend(["-s", select]) if exclude: args.extend(["--exclude", exclude]) if full_refresh: args.append("--full-refresh") if show: args.append("--show") # Execute with progress reporting logger.info(f"Running DBT seed with args: {args}") # Define progress callback if context available async def progress_callback(current: int, total: int, message: str) -> None: if ctx: await ctx.report_progress(progress=current, total=total, message=message) result = await self.runner.invoke(args, progress_callback=progress_callback if ctx else None) # type: ignore if not result.success: error_msg = str(result.exception) if result.exception else "Seed failed" response = { "status": "error", "message": error_msg, "command": " ".join(args), } # Include dbt output for debugging if result.stdout: response["dbt_output"] = result.stdout if result.stderr: response["stderr"] = result.stderr return response # Save state on success for next modified run if result.success and self.project_dir: state_dir = self.project_dir / "target" / "state_last_run" state_dir.mkdir(parents=True, exist_ok=True) manifest_path = self.runner.get_manifest_path() # type: ignore shutil.copy(manifest_path, state_dir / "manifest.json") # Parse run_results.json for details run_results = self._parse_run_results() return { "status": "success", "command": " ".join(args), "results": run_results.get("results", []), "elapsed_time": run_results.get("elapsed_time"), }
• src/dbt_core_mcp/server.py:1639-1684 (registration)

  The FastMCP tool registration decorator (@self.app.tool()) that defines the 'seed_data' tool, its parameters (serving as input schema), comprehensive docstring, and delegates to the implementation handler.
  async def seed_data( ctx: Context, select: str | None = None, exclude: str | None = None, select_state_modified: bool = False, select_state_modified_plus_downstream: bool = False, full_refresh: bool = False, show: bool = False, ) -> dict[str, Any]: """Load seed data (CSV files) from seeds/ directory into database tables. Seeds are typically used for reference data like country codes, product categories, etc. State-based selection modes (detects changed CSV files): - select_state_modified: Load only seeds modified since last successful run (state:modified) - select_state_modified_plus_downstream: Load modified + downstream dependencies (state:modified+) Note: Requires select_state_modified=True Manual selection (alternative to state-based): - select: dbt selector syntax (e.g., "raw_customers", "tag:lookup") - exclude: Exclude specific seeds Important: Change detection for seeds works via file hash comparison: - Seeds < 1 MiB: Content hash is compared (recommended) - Seeds >= 1 MiB: Only file path changes are detected (content changes ignored) For large seeds, use manual selection or run all seeds. Args: select: Manual selector for seeds exclude: Exclude selector select_state_modified: Use state:modified selector (changed seeds only) select_state_modified_plus_downstream: Extend to state:modified+ (changed + downstream) full_refresh: Truncate and reload seed tables (default behavior) show: Show preview of loaded data Returns: Seed results with status and loaded seed info Examples: seed_data() # Load all seeds seed_data(select_state_modified=True) # Load only changed CSVs seed_data(select="raw_customers") # Load specific seed """ await self._ensure_initialized_with_context(ctx) return await self.toolImpl_seed_data(ctx, select, exclude, select_state_modified, select_state_modified_plus_downstream, full_refresh, show)
• src/dbt_core_mcp/server.py:479-520 (helper)

  Helper method used by seed_data (and similar tools) to validate parameters and construct state-based dbt selectors like 'state:modified' or 'state:modified+'.
  async def _prepare_state_based_selection( self, select_state_modified: bool, select_state_modified_plus_downstream: bool, select: str | None, ) -> str | None: """Validate and prepare state-based selection. Args: select_state_modified: Use state:modified selector select_state_modified_plus_downstream: Extend to state:modified+ select: Manual selector (conflicts with state-based) Returns: The dbt selector string to use ("state:modified" or "state:modified+"), or None if: - Not using state-based selection - No previous state exists (cannot determine modifications) Raises: ValueError: If validation fails """ # Validate: hierarchical requirement if select_state_modified_plus_downstream and not select_state_modified: raise ValueError("select_state_modified_plus_downstream requires select_state_modified=True") # Validate: can't use both state-based and manual selection if select_state_modified and select: raise ValueError("Cannot use both select_state_modified* flags and select parameter") # If not using state-based selection, return None if not select_state_modified: return None # Check if state exists state_dir = self.project_dir / "target" / "state_last_run" # type: ignore if not state_dir.exists(): # No state - cannot determine modifications return None # Return selector (state exists) return "state:modified+" if select_state_modified_plus_downstream else "state:modified"
• src/dbt_core_mcp/server.py:304-341 (helper)

  Helper method to parse dbt's run_results.json file after seed/run/test/build operations, simplifying results for tool responses.
  def _parse_run_results(self) -> dict[str, Any]: """Parse target/run_results.json after dbt run/test/build. Returns: Dictionary with results array and metadata """ if not self.project_dir: return {"results": [], "elapsed_time": 0} run_results_path = self.project_dir / "target" / "run_results.json" if not run_results_path.exists(): return {"results": [], "elapsed_time": 0} try: with open(run_results_path) as f: data = json.load(f) # Simplify results for output simplified_results = [] for result in data.get("results", []): simplified_results.append( { "unique_id": result.get("unique_id"), "status": result.get("status"), "message": result.get("message"), "execution_time": result.get("execution_time"), "failures": result.get("failures"), } ) return { "results": simplified_results, "elapsed_time": data.get("elapsed_time", 0), } except Exception as e: logger.warning(f"Failed to parse run_results.json: {e}") return {"results": [], "elapsed_time": 0}