real-estate-sustainability-mcp 0.0.0

MCP server for analyzing building sustainability metrics through Excel, PDF, and standardized frameworks (ESG, LEED, BREEAM, DGNB) with IFC integration

Real Estate Sustainability Analysis MCP

MCP server for analyzing building sustainability metrics through Excel, PDF, and standardized frameworks (ESG, LEED, BREEAM, DGNB) with IFC integration

Built with FastMCP and mcp-refcache for efficient handling of large data in AI agent tools.

Features

• ✅ Reference-Based Caching - Return references instead of large data, reducing context window usage

• ✅ Preview Generation - Automatic previews for large results (sample, truncate, paginate strategies)

• ✅ Pagination - Navigate large datasets without loading everything at once

• ✅ Access Control - Separate user and agent permissions for sensitive data

• ✅ Private Computation - Let agents compute with values they cannot see

• ✅ Docker Ready - Production-ready containers with Python slim base image

• ✅ GitHub Actions - CI/CD with PyPI publishing and GHCR containers

• ✅ Langfuse Tracing - Built-in observability integration

• ✅ Type-Safe - Full type hints with Pydantic models

• ✅ Testing Ready - pytest with 73% coverage requirement

• ✅ Pre-commit Hooks - Ruff formatting and linting

Quick Start

Prerequisites

• Python 3.12+
• uv (recommended) or pip

Installation

# Clone the repository
git clone https://github.com/l4b4r4b4b4/real-estate-sustainability-mcp
cd real-estate-sustainability-mcp

# Install dependencies
uv sync

# Run the server (stdio mode for Claude Desktop)
uv run real-estate-sustainability-mcp

# Run the server (SSE/HTTP mode for deployment)
uv run real-estate-sustainability-mcp --transport sse --port 8000

Install from PyPI

# Run directly with uvx (no install needed)
uvx real-estate-sustainability-mcp stdio

# Or install globally
uv tool install real-estate-sustainability-mcp
real-estate-sustainability-mcp --help

Docker Deployment

# Pull and run from GHCR
docker pull ghcr.io/l4b4r4b4b4/real-estate-sustainability-mcp:latest
docker run -p 8000:8000 ghcr.io/l4b4r4b4b4/real-estate-sustainability-mcp:latest

# Or build locally with Docker Compose
docker compose up

# Build images manually
docker compose --profile build build base
docker compose build

Using with Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "real-estate-sustainability-mcp": {
      "command": "uv",
      "args": ["run", "real-estate-sustainability-mcp"],
      "cwd": "/path/to/real-estate-sustainability-mcp"
    }
  }
}

Using with Zed

The project includes .zed/settings.json pre-configured for MCP context servers.

Project Structure

real-estate-sustainability-mcp/
├── app/                     # Application code
│   ├── __init__.py          # Version export
│   ├── server.py            # Main server with tools
│   ├── tools/               # Tool modules
│   └── __main__.py          # CLI entry point
├── tests/                   # Test suite
│   ├── conftest.py          # Pytest fixtures
│   └── test_server.py       # Server tests
├── docker/
│   ├── Dockerfile.base      # Python slim base image with dependencies
│   ├── Dockerfile           # Production image (extends base)
│   └── Dockerfile.dev       # Development with hot reload
├── .github/
│   └── workflows/
│       ├── ci.yml           # CI pipeline (lint, test, security)
│       ├── publish.yml      # PyPI trusted publisher
│       └── release.yml      # Docker build & publish to GHCR
├── .agent/                  # AI assistant workspace
│   └── goals/
│       └── 00-Template-Goal/  # Goal tracking template
├── pyproject.toml           # Project config
├── docker-compose.yml       # Local development & production
├── flake.nix                # Nix dev shell
└── .rules                   # AI assistant guidelines

Development

Setup

# Install dependencies
uv sync

# Install pre-commit and pre-push hooks
uv run pre-commit install --install-hooks
uv run pre-commit install --hook-type pre-push

Running Tests

uv run pytest
uv run pytest --cov  # With coverage

Linting and Formatting

uv run ruff check . --fix
uv run ruff format .

Type Checking

uv run mypy app/

Docker Development

# Run development container with hot reload
docker compose --profile dev up

# Build base image (for publishing)
docker compose --profile build build base

# Build all images
docker compose build

Using Nix (Optional)

nix develop  # Enter dev shell with all tools

Configuration

Environment Variables

Variable	Description	Default
LANGFUSE_PUBLIC_KEY	Langfuse public key	-
LANGFUSE_SECRET_KEY	Langfuse secret key	-
LANGFUSE_HOST	Langfuse host URL	https://cloud.langfuse.com

CLI Commands

uvx real-estate-sustainability-mcp --help

Commands:
  stdio             Start server in stdio mode (for Claude Desktop and local CLI)
  sse               Start server in SSE mode (Server-Sent Events)
  streamable-http   Start server in streamable HTTP mode (recommended for remote/Docker)

# Examples:
uvx real-estate-sustainability-mcp stdio                          # Local CLI mode
uvx real-estate-sustainability-mcp sse --port 8000                # SSE on port 8000
uvx real-estate-sustainability-mcp streamable-http --host 0.0.0.0 # Docker/remote mode

Publishing

PyPI

Configure trusted publisher at PyPI:

• Project name: real-estate-sustainability-mcp
• Owner: l4b4r4b4b4
• Repository: real-estate-sustainability-mcp
• Workflow: publish.yml
• Environment: pypi

Docker Images

Images are automatically published to GHCR on:

• Push to main branch → latest tag
• Version tags (v*.*.*) → latest, v0.0.1, 0.0.1, 0.0 tags

License

MIT License - see LICENSE for details.

Contributing

See CONTRIBUTING.md for development guidelines.

Related Projects

• mcp-refcache - Reference-based caching for MCP servers
• FastMCP - High-performance MCP server framework
• Model Context Protocol - The underlying protocol specification