XTB MCP Server

Overview

The XTB MCP Server is a dedicated Model Context Protocol (MCP) service that empowers AI assistants to automate the creation of Extended Tight‑Binding (XTB) quantum chemistry input files. By exposing a rich set of tools and templates, the server removes the manual overhead that traditionally accompanies setting up XTB calculations. Developers can now ask an AI assistant to generate a complete, validated input package for any common XTB workflow—single‑point energies, geometry optimizations, frequency analyses, reaction scans, or molecular dynamics—and receive a ready‑to‑run file set in seconds.

What problem does it solve?

Quantum chemists and computational researchers often spend significant time formatting molecular structures, selecting appropriate methods, and configuring calculation parameters. Errors in input files can lead to wasted compute cycles or misleading results. The XTB MCP Server eliminates these pain points by providing a single, consistent interface that validates structures, enforces parameter conventions, and produces syntactically correct XTB inputs. This automation is especially valuable in high‑throughput screening, workflow orchestration, or educational settings where reproducibility and speed are critical.

Core capabilities

• Comprehensive input generation for all major XTB calculation types (single‑point, optimization, frequency, scan, MD) and advanced sampling techniques such as metadynamics or path‑finder.
• Method flexibility with built‑in support for GFN0, GFN1, GFN2, and the GFN‑FF force field.
• Format conversion between XYZ, COORD, and Gaussian formats, enabling seamless integration with other software or data sources.
• Advanced analysis tools that produce orbital, population, and spectroscopic output files for downstream inspection.
• ONIOM QM/MM support to construct multi‑layer hybrid calculations directly from a single prompt.
• Rigorous validation that checks both structural integrity and parameter consistency, returning detailed error messages when inputs are malformed.

Real‑world use cases

• Automated high‑throughput screening: A research group can have an AI assistant generate thousands of XTB input packages for ligand–protein binding studies, saving hours of manual scripting.
• Workflow orchestration: In a pipeline that chains geometry optimization, frequency analysis, and MD, the server ensures each step receives correctly formatted inputs without human intervention.
• Educational tools: Students learning quantum chemistry can experiment with different methods and parameters by simply describing their desired calculation, while the server guarantees correct syntax.
• Hybrid QM/MM modeling: A materials scientist can request a multi‑layer ONIOM calculation for a defect in a crystal, and the server will output the full input set ready for XTB execution.

Integration with AI assistants

The server is designed to be plug‑and‑play for any MCP‑compliant client. Developers can add a single configuration entry to Claude Desktop, Cursor, or Windsurf, specifying the command that launches . Once registered, AI assistants can invoke tools such as , receiving a structured JSON response that includes the complete input files and any auxiliary data. Because the server exposes validation and error handling through MCP’s standard response format, developers can build robust user interfaces that surface clear feedback to end users.

Unique advantages

• One‑stop shop: All XTB-related functionality—generation, validation, sampling, analysis—is consolidated in a single MCP service.
• Extensibility: The repository’s modular structure allows contributors to add new templates, methods, or analysis routines without modifying the core API.
• Documentation‑driven: Rich parameter and format specifications are bundled with the server, ensuring that generated inputs always adhere to the latest XTB conventions.
• Cross‑platform: By exposing a simple Python entry point, the server runs on any system that supports MCP clients, from local desktops to cloud‑based notebooks.

In summary, the XTB MCP Server transforms quantum chemistry workflows from a manual, error‑prone process into an AI‑driven, reproducible pipeline. By handling structure conversion, method selection, and rigorous validation behind the scenes, it enables developers to focus on scientific insight rather than file syntax.