Which integrations are available for this server?

Provides tools for BIM (Building Information Modeling) extraction and building energy simulation workflows, enabling AI agents to process IFC data, integrate with TEASER, model scenarios, bind weather data, and export results for downstream analysis.

How do I use bim2sim-mcp?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@bim2sim-mcp Extract thermal zones from the IFC model for energy simulation" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

bim2sim-mcp

by l4b4r4b4b4

Overview Schema Related Servers Score Discussions

Python

Hybrid

BIM2Sim MCP

PyPI version Python 3.12+ License: MIT

GHCR

MCP server for BIM-to-building-energy simulation workflows with IFC extraction, TEASER integration, scenario modeling, weather binding, and results export for downstream WAT/ROI analysis

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

Related MCP server: mcp-server-for-revit

Quick Start

Prerequisites

Python 3.12+
uv (recommended) or pip

Installation

# Clone the repository
git clone https://github.com/l4b4r4b4b4/bim2sim-mcp
cd bim2sim-mcp

# Install dependencies
uv sync

# Run the server (stdio mode for Claude Desktop)
uv run bim2sim-mcp

# Run the server (SSE/HTTP mode for deployment)
uv run bim2sim-mcp --transport sse --port 8000

Install from PyPI

# Run directly with uvx (no install needed)
uvx bim2sim-mcp stdio

# Or install globally
uv tool install bim2sim-mcp
bim2sim-mcp --help

Docker Deployment

# Pull and run from GHCR
docker pull ghcr.io/l4b4r4b4b4/bim2sim-mcp:latest
docker run -p 8000:8000 ghcr.io/l4b4r4b4b4/bim2sim-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": {
    "bim2sim-mcp": {
      "command": "uv",
      "args": ["run", "bim2sim-mcp"],
      "cwd": "/path/to/bim2sim-mcp"
    }
  }
}

Using with Zed

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

Project Structure

bim2sim-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 bim2sim-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 bim2sim-mcp stdio                          # Local CLI mode
uvx bim2sim-mcp sse --port 8000                # SSE on port 8000
uvx bim2sim-mcp streamable-http --host 0.0.0.0 # Docker/remote mode

CI/CD Workflow

This project uses a CI-gated workflow to ensure code quality and safe releases:

┌─────────────────────────────────────────────────────────────┐
│  Feature Branch → Open PR                                   │
│         ↓                                                    │
│  CI Runs (lint, test, security)                            │
│         ↓                                                    │
│  ✅ CI Must Pass (enforced by branch protection)           │
│         ↓                                                    │
│  Merge to main                                              │
└─────────────────────────────────────────────────────────────┘
                         ↓
┌─────────────────────────────────────────────────────────────┐
│  CI Re-runs on main                                         │
│         ↓                                                    │
│  Release Workflow waits for CI Success                      │
│         ↓                                                    │
│  Docker Images Built & Pushed to GHCR                       │
└─────────────────────────────────────────────────────────────┘
                         ↓
┌─────────────────────────────────────────────────────────────┐
│  Manually Create GitHub Release                             │
│         ↓                                                    │
│  Publish Workflow verifies Release succeeded                │
│         ↓                                                    │
│  Package Published to PyPI                                  │
└─────────────────────────────────────────────────────────────┘
                         ↓
┌─────────────────────────────────────────────────────────────┐
│  CD Workflow deploys (staging/production)                   │
└─────────────────────────────────────────────────────────────┘

Key Safeguards:

✅ Branch protection ensures CI passes before merge
✅ Tag pushes verify CI passed before building images
✅ Publish workflow verifies Release succeeded before PyPI upload
✅ CD workflow only deploys after Release completes

Manual Gates:

🔒 Creating GitHub Release (allows review before PyPI publish)
🔒 Production deployments (requires manual approval)

Publishing

PyPI

Configure trusted publisher at PyPI:

Project name: bim2sim-mcp
Owner: l4b4r4b4b4
Repository: bim2sim-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.

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

This server cannot be installed

license - permissive license

quality - not tested

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

–Release cycle

–Releases (12mo)

Commit activity

Resources

GitHub Repository

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