init commit

.python-version

@@ -0,0 +1 @@
+3.12

Dockerfile

@@ -0,0 +1,49 @@
+# Use a Python image with uv pre-installed
+FROM ghcr.io/astral-sh/uv:python3.12-bookworm-slim AS uv
+
+# Install the project into `/app`
+WORKDIR /app
+
+# Enable bytecode compilation
+ENV UV_COMPILE_BYTECODE=1
+
+# Copy from the cache instead of linking since it's a mounted volume
+ENV UV_LINK_MODE=copy
+
+# Install the project's dependencies using the lockfile and settings
+RUN --mount=type=cache,target=/root/.cache/uv \
+    --mount=type=bind,source=uv.lock,target=uv.lock \
+    --mount=type=bind,source=pyproject.toml,target=pyproject.toml \
+    uv sync --frozen --no-install-project --no-dev --no-editable
+
+# Then, add the rest of the project source code and install it
+# Installing separately from its dependencies allows optimal layer caching
+ADD . /app
+RUN --mount=type=cache,target=/root/.cache/uv \
+    uv sync --frozen --no-dev --no-editable
+
+FROM python:3.12-slim-bookworm
+
+WORKDIR /app
+ 
+# Copy the Python packages from the uv stage
+COPY --from=uv /app/.venv /app/.venv
+
+# Create an app user for better security
+RUN groupadd -r app && useradd -r -g app app
+RUN chown -R app:app /app
+
+# Place executables in the environment at the front of the path
+ENV PATH="/app/.venv/bin:$PATH"
+
+# Set the user to run the application
+USER app
+
+# Set default port to 7860 if not provided
+ENV PORT=7860
+
+# Expose the port defined by the PORT environment variable
+EXPOSE $PORT
+
+# when running the container, add --db-path and a bind mount to the host's db file
+ENTRYPOINT ["mcp-server-ifcopenshell"]

mcp_ifcopenshell/__init__.py

@@ -0,0 +1,4 @@
+from .server import main
+
+if __name__ == "__main__":
+    main()

mcp_ifcopenshell/__main__.py

@@ -0,0 +1,4 @@
+from .server import main
+
+if __name__ == "__main__":
+    main()

mcp_ifcopenshell/server.py

@@ -0,0 +1,372 @@
+import io
+import os
+import uuid
+from typing import Any, Dict, List
+
+import boto3
+import ifcopenshell
+from mcp.server.fastmcp import FastMCP
+from starlette.requests import Request
+from starlette.responses import PlainTextResponse
+
+
+def main():
+    # Create an MCP server
+    mcp = FastMCP("IfcOpenShell MCP Server", stateless_http=True)
+
+    # Store for IFC models
+    models = {}
+
+    @mcp.tool()
+    def load_model(username: str, filename: str) -> str:
+        """
+        Load an IFC model from S3 using environment variable for bucket name.
+
+        Args:
+            username: The username/email directory in S3 (e.g., 'giulia.daleo2G24H').
+            filename: The IFC filename to load (e.g., 'hotel.ifc').
+
+        Returns:
+            A model_id that can be used in subsequent calls.
+        """
+        try:
+            # Get bucket name from environment variable
+            bucket_name = os.environ.get("S3_BUCKET_NAME")
+            if not bucket_name:
+                raise Exception("S3_BUCKET_NAME environment variable is not set")
+
+            # Set user email from parameter
+            user_email = username
+            file_name = filename
+
+            # Construct the object key
+            object_key = f"{user_email}/{file_name}"
+
+            # Create S3 client
+            s3_client = boto3.client("s3")
+
+            # Create a BytesIO object to store the file data in memory
+            file_data = io.BytesIO()
+
+            # Download the file directly to memory
+            s3_client.download_fileobj(bucket_name, object_key, file_data)
+
+            # save file locally
+            file_path = f"/tmp/{file_name}"
+            with open(file_path, "wb") as f:
+                f.write(file_data.getvalue())
+
+            # Load the model directly from the in-memory file
+            model = ifcopenshell.open(file_path)
+
+            # Clean up the local file if needed
+            os.remove(file_path)
+
+            # Generate a unique ID for this model
+            model_id = str(uuid.uuid4())
+
+            # Store the model for later use
+            models[model_id] = {
+                "model": model,
+                "source": {
+                    "bucket": bucket_name,
+                    "key": object_key,
+                    "user_email": user_email,
+                    "file_name": file_name,
+                },
+            }
+
+            return model_id
+        except Exception as e:
+            raise Exception(f"Failed to load model: {str(e)}")
+
+    @mcp.tool()
+    def filter_by_category(model_id: str, category: str) -> List[Dict[str, Any]]:
+        """
+        Filter elements in the IFC model by category.
+
+        Args:
+            model_id: The ID of the model returned by load_model_from_s3.
+            category: The IFC category to filter by (e.g., "IfcDoor", "IfcWindow").
+
+        Returns:
+            A list of elements matching the category.
+        """
+        if model_id not in models:
+            raise Exception(f"Model with ID {model_id} not found")
+
+        model = models[model_id]["model"]
+
+        try:
+            # Get elements by category
+            elements = model.by_type(category)
+
+            # Convert elements to a serializable format
+            result = []
+            for element in elements:
+                element_data = {
+                    "id": element.id(),
+                    "type": element.is_a(),
+                    "guid": element.GlobalId if hasattr(element, "GlobalId") else None,
+                    "name": element.Name if hasattr(element, "Name") else None,
+                }
+
+                # Add properties if available
+                if hasattr(element, "IsDefinedBy"):
+                    properties = {}
+                    for definition in element.IsDefinedBy:
+                        if definition.is_a("IfcRelDefinesByProperties"):
+                            property_set = definition.RelatingPropertyDefinition
+                            if property_set.is_a("IfcPropertySet"):
+                                for prop in property_set.HasProperties:
+                                    if prop.is_a("IfcPropertySingleValue"):
+                                        properties[prop.Name] = (
+                                            str(prop.NominalValue.wrappedValue)
+                                            if prop.NominalValue
+                                            else None
+                                        )
+
+                    element_data["properties"] = properties
+
+                result.append(element_data)
+
+            return result
+        except Exception as e:
+            raise Exception(f"Error filtering by category: {str(e)}")
+
+    @mcp.tool()
+    def get_element_by_id(model_id: str, element_id: int) -> Dict[str, Any]:
+        """
+        Get a specific element by its ID.
+
+        Args:
+            model_id: The ID of the model returned by load_model_from_s3.
+            element_id: The ID of the element to retrieve.
+
+        Returns:
+            The element details.
+        """
+        if model_id not in models:
+            raise Exception(f"Model with ID {model_id} not found")
+
+        model = models[model_id]["model"]
+
+        try:
+            element = model.by_id(element_id)
+
+            element_data = {
+                "id": element.id(),
+                "type": element.is_a(),
+                "guid": element.GlobalId if hasattr(element, "GlobalId") else None,
+                "name": element.Name if hasattr(element, "Name") else None,
+            }
+
+            # Add properties if available
+            if hasattr(element, "IsDefinedBy"):
+                properties = {}
+                for definition in element.IsDefinedBy:
+                    if definition.is_a("IfcRelDefinesByProperties"):
+                        property_set = definition.RelatingPropertyDefinition
+                        if property_set.is_a("IfcPropertySet"):
+                            for prop in property_set.HasProperties:
+                                if prop.is_a("IfcPropertySingleValue"):
+                                    properties[prop.Name] = (
+                                        str(prop.NominalValue.wrappedValue)
+                                        if prop.NominalValue
+                                        else None
+                                    )
+
+                element_data["properties"] = properties
+
+            return element_data
+        except Exception as e:
+            raise Exception(f"Error getting element by ID: {str(e)}")
+
+    # @server.tool()
+    # def get_model_info(model_id: str) -> Dict[str, Any]:
+    #     """
+    #     Get information about the loaded IFC model.
+
+    #     Args:
+    #         model_id: The ID of the model returned by load_model_from_s3.
+
+    #     Returns:
+    #         Information about the model.
+    #     """
+    #     if model_id not in models:
+    #         raise Exception(f"Model with ID {model_id} not found")
+
+    #     model = models[model_id]["model"]
+
+    #     try:
+    #         # Get the project
+    #         project = model.by_type("IfcProject")[0]
+
+    #         # Basic model info
+    #         info = {
+    #             "model_id": model_id,
+    #             "schema": model.schema,
+    #             "source": models[model_id]["source"],
+    #             "project_name": project.Name if hasattr(project, "Name") else None,
+    #             "category_counts": {},
+    #         }
+
+    #         # Count the number of elements by category
+    #         for element in model.by_type("Ifc*"):
+    #             category = element.is_a()
+    #             if category in info["category_counts"]:
+    #                 info["category_counts"][category] += 1
+    #             else:
+    #                 info["category_counts"][category] = 1
+
+    #         return info
+    #     except Exception as e:
+    #         raise Exception(f"Error getting model info: {str(e)}")
+
+    @mcp.custom_route("/health", methods=["GET"])
+    async def health(request: Request) -> PlainTextResponse:
+        """
+        A basic health check endpoint. Returns HTTP 200 with body "OK".
+        """
+        return PlainTextResponse("OK")
+
+    @mcp.custom_route("/clear", methods=["GET"])
+    async def clear(request: Request) -> PlainTextResponse:
+        """
+        Remove a model from memory using its model_id.
+
+        Query Parameters:
+            model_id: The ID of the model to remove from memory.
+
+        Returns:
+            Confirmation message as plain text.
+        """
+        try:
+            # Extract model_id from query parameters
+            model_id = request.query_params.get("model_id")
+
+            # Validate parameters
+            if not model_id:
+                return PlainTextResponse(
+                    "Error: 'model_id' query parameter is required", status_code=400
+                )
+
+            # Check if model exists
+            if model_id not in models:
+                return PlainTextResponse(
+                    f"Error: Model with ID {model_id} not found", status_code=404
+                )
+
+            # Store model info for the response
+            source_info = models[model_id]["source"]
+            filename = source_info.get("file_name", "unknown")
+
+            # Remove the model from the dictionary
+            del models[model_id]
+
+            # Return success message
+            return PlainTextResponse(
+                f"Model {model_id} ({filename}) successfully removed from memory"
+            )
+
+        except Exception as e:
+            return PlainTextResponse(f"Error: {str(e)}", status_code=500)
+
+    @mcp.custom_route("/load", methods=["GET"])
+    async def load(request: Request) -> PlainTextResponse:
+        """
+        Load an IFC model via HTTP request.
+
+        Query Parameters:
+            username: The username/email directory in S3 (e.g., 'giulia.daleo2G24H').
+            filename: The IFC filename to load (e.g., 'hotel.ifc').
+
+        Returns:
+            The model_id as plain text that can be used in subsequent calls.
+        """
+        try:
+            # Extract query parameters
+            username = request.query_params.get("username")
+            filename = request.query_params.get("filename")
+
+            # Validate parameters
+            if not username or not filename:
+                return PlainTextResponse(
+                    "Error: Both 'username' and 'filename' query parameters are required",
+                    status_code=400,
+                )
+
+            # Get bucket name from environment variable
+            bucket_name = os.environ.get("S3_BUCKET_NAME")
+            if not bucket_name:
+                return PlainTextResponse(
+                    "Error: S3_BUCKET_NAME environment variable is not set",
+                    status_code=500,
+                )
+
+            # Set user email from parameter
+            user_email = username
+            file_name = filename
+
+            # Construct the object key
+            object_key = f"{user_email}/{file_name}"
+
+            # Create S3 client
+            s3_client = boto3.client("s3")
+
+            # Create a BytesIO object to store the file data in memory
+            file_data = io.BytesIO()
+
+            # Download the file directly to memory
+            try:
+                s3_client.download_fileobj(bucket_name, object_key, file_data)
+            except Exception as s3_error:
+                return PlainTextResponse(
+                    f"Error downloading file from S3: {str(s3_error)}", status_code=404
+                )
+
+            # save file locally
+            file_path = f"/tmp/{file_name}"
+            with open(file_path, "wb") as f:
+                f.write(file_data.getvalue())
+
+            # Load the model directly from the in-memory file
+            try:
+                model = ifcopenshell.open(file_path)
+            except Exception as model_error:
+                # Clean up temp file if it exists
+                if os.path.exists(file_path):
+                    os.remove(file_path)
+                return PlainTextResponse(
+                    f"Error loading IFC model: {str(model_error)}", status_code=500
+                )
+
+            # Clean up the local file if needed
+            os.remove(file_path)
+
+            # Generate a unique ID for this model
+            model_id = str(uuid.uuid4())
+
+            # Store the model for later use
+            models[model_id] = {
+                "model": model,
+                "source": {
+                    "bucket": bucket_name,
+                    "key": object_key,
+                    "user_email": user_email,
+                    "file_name": file_name,
+                },
+            }
+
+            # Return the model_id as plain text
+            return PlainTextResponse(model_id)
+
+        except Exception as e:
+            return PlainTextResponse(f"Error: {str(e)}", status_code=500)
+
+    import uvicorn
+
+    port = int(os.environ.get("PORT", 7860))
+    uvicorn.run(mcp.streamable_http_app(), host="0.0.0.0", port=port)
+
+    return 0

pyproject.toml

@@ -0,0 +1,21 @@
+[project]
+name = "mcp_ifcopenshell"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.12"
+dependencies = [
+    "boto3>=1.38.25",
+    "ifcopenshell>=0.8.2",
+    "mcp[cli]>=1.9.1",
+]
+
+[project.scripts]
+mcp_ifcopenshell = "mcp_ifcopenshell:main"
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[tool.hatch.build.targets.wheel]
+packages = ["mcp_ifcopenshell"]

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