Mofstructure
БесплатноНе проверенAn MCP server for deconstructing and analyzing Metal-Organic Framework (MOF) structures, including SBU and ligand identification, guest removal, and COF stackin
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.
Установить Mofstructure в Claude Desktop, Claude Code, Cursor
unyly install mofstructure-mcpСтавит 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 mofstructureПошаговые 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.
Похожие MCP
Fetch
Web content fetching and conversion for efficient LLM usage.
AWS KB Retrieval
Retrieval from AWS Knowledge Base using Bedrock Agent Runtime.
автор: modelcontextprotocolSpring AI MCP Server
Provides auto-configuration for setting up an MCP server in Spring Boot applications.
llm-analysis-assistant
A very streamlined mcp client that supports calling and monitoring stdio/sse/streamableHttp, and can also view request responses through the /logs page. It also
автор: xuzexin-hzMCP-Agent
A simple, composable framework to build agents using Model Context Protocol by [LastMile AI](https://www.lastmileai.dev)
автор: lastmile-aiSpring AI MCP Client
Provides auto-configuration for MCP client functionality in Spring Boot applications.
mcp.natoma.ai
A Hosted MCP Platform to discover, install, manage and deploy MCP servers by [Natoma Labs](https://www.natoma.ai)
MCPHub
Website to list high quality MCP servers and reviews by real users. Also provide online chatbot for popular LLM models with MCP server support.
MCP Servers Rating and User Reviews
Website to rate MCP servers, write authentic user reviews, and [search engine for agent & mcp](http://www.deepnlp.org/search/agent)
mkinf
An Open Source registry of hosted MCP Servers to accelerate AI agent workflows.
Compare Mofstructure with
Не уверен что выбрать?
Найди свой стек за 60 секунд
Автор?
Embed-бейдж для README
Похожее
Все в категории ai
