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Mofstructure

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An MCP server for deconstructing and analyzing Metal-Organic Framework (MOF) structures, including SBU and ligand identification, guest removal, and COF stackin

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Описание

An MCP server for deconstructing and analyzing Metal-Organic Framework (MOF) structures, including SBU and ligand identification, guest removal, and COF stacking analysis. It enables AI agents to perform automated chemical informatics and structural characterization on crystal structures via CIF files.

README

A lean, MCP-enabled repackaging of the outstanding mofstructure library by Dr. Dinga Wonanke.


Standing on the shoulders of giants

Let's be blunt: the original mofstructure is one of the most impressive pieces of software in computational materials science written by a single researcher.

In a field where "framework analysis" usually means running a black-box binary and hoping the output makes sense, Dr. Wonanke built something genuinely different. The deconstruction engine inside mofdeconstructor.py — over 2 000 lines of carefully reasoned graph theory — can take any arbitrary MOF crystal structure and correctly identify every secondary building unit, every organic ligand, every metal cluster, the SBU topology, the coordination number of every metal centre, and the points of extension — all automatically, all in pure Python, without ever needing a pre-curated database of known topologies to look things up in.

That is a hard problem. Most tools either require you to label things manually, rely on heuristic pattern matching that breaks on anything non-standard, or are proprietary closed-source binaries. mofstructure does it right: it constructs the full molecular graph, identifies metal nodes, finds the organic bridges, locates the breaking points, and assembles the building units — then hands you back proper ASE Atoms objects with SMILES, InChI and InChIKey already computed via OpenBabel.

The guest-removal logic is similarly thoughtful. Rather than a naive "delete small molecules" heuristic it analyses graph connectivity to find genuinely unbound components, which means it works correctly even on unusual solvates and disordered structures that trip up simpler approaches.

And the COF stacking analysis, the PBC wrapping, the IUPAC name lookup database — all of it is the kind of infrastructure that takes years of domain knowledge to build correctly.

If you are doing any serious high-throughput MOF screening or computational reticular chemistry, reading the original codebase is essential. This fork would not exist without its extraordinary foundation.

Original repository: https://github.com/bafgreat/mofstructure
Original author: Dr. Dinga Wonanke — https://www.dingawonanke.com
Original paper: Wonanke et al., Journal of Open Source Software, 2024.


What is this fork?

This edition strips the original down to a focused MCP (Model Context Protocol) server so that AI agents — in particular those built with featherflow — can call MOF structure operations as tools over stdio or HTTP.

What was removed and why

Removed Reason
Porosity calculation (porosity.py) Provided by the separate zeopp-backend MCP service
Open metal site detection (get_oms) Provided by mofchecker-mcp and zeopp-backend
obsolate/ directory Dead code, superseded by current implementation
Sphinx docs Out of date; not needed for MCP deployment

What was added

Added Description
mofstructure/mcp_server.py FastMCP server exposing 5 tools over stdio
mcp dependency MCP Python SDK
mofstructure_mcp CLI entry point python -m mofstructure.mcp_server

The three-service architecture

This fork is designed to work alongside two companion MCP services:

mofchecker-mcp      →  "Is this structure valid?"        (quality checks)
mofstructure-mcp    →  "What is this structure made of?" (deconstruction + cleanup)
zeopp-backend       →  "How porous is this structure?"   (geometric analysis)

Point your agent at all three and it can perform end-to-end MOF analysis from a raw CIF file.


Installation

Important — each MCP server should run in its own virtual environment.

git clone https://github.com/lichman0405/mofstructure.git
cd mofstructure
python -m venv .venv
# Linux / macOS
source .venv/bin/activate
# Windows PowerShell
.\.venv\Scripts\Activate.ps1

pip install -e .

Optional RDKit support:

pip install -e ".[rdkit]"

MCP tools

The server exposes five tools. Every tool accepts either a cif_path (absolute path on the server filesystem) or cif_content (raw CIF text).

Tool Description
remove_guest Remove unbound guest molecules; returns clean host CIF
get_sbu Deconstruct into metal + organic SBUs with SMILES / InChI / InChIKey
get_ligands Deconstruct into metal clusters + organic ligands with cheminformatics
wrap_structure Wrap atoms into unit cell — fixes the "broken bond" PBC visualisation artefact
analyze_cof_stacking Compute interlayer lateral offsets and heights; classify AA / AB / mixed stacking

Running the server

stdio (for featherflow / Claude Desktop)

python -m mofstructure.mcp_server
# or, after pip install:
mofstructure_mcp

featherflow integration

Edit ~/.featherflow/config.json:

{
  "tools": {
    "mcpServers": {
      "mofstructure": {
        "command": "/path/to/mofstructure/.venv/bin/python",
        "args": ["-m", "mofstructure.mcp_server"],
        "toolTimeout": 120
      },
      "mofchecker": {
        "command": "/path/to/mofchecker/.venv/bin/python",
        "args": ["-m", "mofchecker.mcp_server"],
        "toolTimeout": 120
      },
      "zeopp": {
        "url": "http://localhost:9877/mcp",
        "toolTimeout": 120
      }
    }
  }
}

On Windows replace the path with C:/path/to/mofstructure/.venv/Scripts/python.exe.


Using as a Python library

The library API is unchanged from the original:

from mofstructure import structure

mof = structure.MOFstructure(filename="path/to/your.cif")

# Remove guest molecules
clean = mof.remove_guest()

# Deconstruct into SBUs  (cheminfo=True computes SMILES / InChI / InChIKey)
metal_sbus, organic_sbus = mof.get_sbu(cheminfo=True)
for sbu in metal_sbus:
    print(sbu.info['sbu_type'], sbu.info['smi'])

# Deconstruct into ligands and metal clusters
metal_clusters, organic_ligands = mof.get_ligands(cheminfo=True)
for ligand in organic_ligands:
    print(ligand.info['inchikey'])

Command-line tools

Command Description
mofstructure <cif_file> [output_dir] Deconstruct a single CIF into SBUs and ligands
mofstructure_database <cif_folder> [output_dir] Batch-process a folder of CIFs into a database
mofstructure_building_units <cif_folder> Batch deconstruction only
mofstructure_curate <cif_folder> Curate / validate a folder of CIFs
mofstructure_mcp Start the MCP server (stdio)

License

MIT — same as the original project.

from github.com/lichman0405/mofstructure-mcp

Установить Mofstructure в Claude Desktop, Claude Code, Cursor

Рекомендуется · одна команда, все IDE
unyly install mofstructure-mcp

Ставит в Claude Desktop, Claude Code, Cursor и VS Code — сам разбирается с npx, uvx и сборкой из исходников.

Впервые? Поставь CLI: curl -fsSL https://unyly.org/install | sh

Или настроить вручную

Выполни в терминале:

claude mcp add mofstructure-mcp -- uvx mofstructure

Пошаговые гайды: как установить Mofstructure

FAQ

Mofstructure MCP бесплатный?

Да, Mofstructure MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для Mofstructure?

Нет, Mofstructure работает без API-ключей и переменных окружения.

Mofstructure — hosted или self-hosted?

Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.

Как установить Mofstructure в Claude Desktop, Claude Code или Cursor?

Открой Mofstructure на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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