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Xraylib MCP Server

by tschoonjversion 0.1.6i★ –iRuns on your computer
Registry nameio.github.tschoonj/xraylib-mcp-server

Install

Overview

Description from the maker (original English)

MCP server providing X-ray interaction data via xraylib

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "xraylib": {
      "command": "uvx",
      "args": [
        "xraylib-mcp-server"
      ]
    }
  }
}

Run this in your terminal

claude mcp add xraylib -- uvx xraylib-mcp-server

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "xraylib": {
      "command": "uvx",
      "args": [
        "xraylib-mcp-server"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "xraylib": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "xraylib-mcp-server"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account tschoonj, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 18354 servers in this category
  • Published to the registry more recently than 5% of the other 18354 servers in this category
  • Basic checks equal to or better than 100% of the other 18354 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Xraylib MCP Server safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.6) reached the registry 7 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv), Docker on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Qemu MCP

Alternatives

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Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

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Boot and drive QEMU VMs from an AI agent: keys, screenshots, serial. No guest agent.

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

xraylib MCP Server

A Model Context Protocol (MCP) server that provides access to xraylib X-ray interaction data through a standardized interface. Query cross-sections, fluorescence lines, edge energies, and more from any MCP-compatible client.

Table of Contents

  • Features
  • Installation
  • Usage
  • As a standalone server
  • With Claude Desktop
  • With VS Code
  • With Claude Code
  • As a development server
  • Using Docker
  • Development
  • License
  • Contributing

Features

This server exposes 104 tools organized into the following categories:

Utility tools
  • AtomicNumberToSymbol / SymbolToAtomicNumber -- convert between atomic numbers and element symbols
  • AtomicWeight -- atomic weight (g/mol)
  • ElementDensity -- element density (g/cm3)
  • ElectronConfig -- electron configuration for a given shell
  • CompoundParser -- parse chemical formulas (e.g. SiO2, Ca5(PO4)3F)
  • Atomic_Factors -- atomic scattering factors f0, f', f''
Line, edge, and shell properties
  • LineEnergy / EdgeEnergy -- fluorescence line and absorption edge energies (keV)
  • FluorYield / JumpFactor / RadRate -- fluorescence yields, jump factors, radiative rates
  • AtomicLevelWidth -- natural widths of atomic levels (keV)
Cross-sections (element)
  • CS_Total, CS_Photo, CS_Rayl, CS_Compt, CS_Energy, CS_KN -- mass cross-sections (cm2/g)
  • CSb_Total, CSb_Photo, CSb_Rayl, CSb_Compt -- atomic cross-sections (barn/atom)
Fluorescence cross-sections
  • CS_FluorLine / CSb_FluorLine -- line fluorescence cross-sections
  • CS_FluorShell / CSb_FluorShell -- shell fluorescence cross-sections
  • Kissel photoionization variants with full, radiative, nonradiative, and no cascade options
Differential cross-sections
  • DCS_Rayl / DCS_Compt and barn/atom variants -- unpolarized differential cross-sections
  • DCSP_Rayl / DCSP_Compt and barn/atom variants -- polarized differential cross-sections
Scattering factors
  • FF_Rayl / SF_Compt -- Rayleigh form factor and Compton scattering function
  • MomentTransf / ComptonEnergy -- momentum transfer and Compton-scattered photon energy
  • Fi / Fii -- anomalous scattering factors
  • ComptonProfile / ComptonProfile_Partial -- Compton profiles (total and per-shell)
Auger and Coster-Kronig transitions
  • AugerRate / AugerYield -- Auger transition rates and yields
  • CosKronTransProb -- Coster-Kronig transition probabilities
Compound cross-sections
  • All CS/CSb, DCS/DCSb, and DCSP/DCSPb variants for compounds (by chemical formula)
  • Kissel photoionization variants for compounds
Refractive index
  • Refractive_Index_Re / Refractive_Index_Im -- real and imaginary parts of the refractive index
NIST compounds
  • GetCompoundDataNISTByName / GetCompoundDataNISTByIndex / GetCompoundDataNISTList -- access the built-in NIST compound database
Radionuclide data
  • GetRadioNuclideDataByName / GetRadioNuclideDataByIndex / GetRadioNuclideDataList -- access the built-in radionuclide database (X-ray lines, intensities, gamma energies)
Constant listings
  • ListLineConstants / ListShellConstants / ListTransitionConstants / ListAugerConstants / ListNISTCompoundConstants -- enumerate valid constant names

Installation

Using uv (recommended)
uv tool install xraylib-mcp-server
Using pip
pip install xraylib-mcp-server

Usage

As a standalone server
# Run with stdio transport (for Claude Desktop, etc.)

xraylib-mcp-server

Run with HTTP transport

xraylib-mcp-server --transport http --port 8000

Run with SSE transport

xraylib-mcp-server --transport sse --port 8000

With Claude Desktop

Add to your Claude Desktop configuration:

{

"mcpServers": { "xraylib": { "command": "uvx", "args": ["xraylib-mcp-server"] } } }

Or using the pre-built Docker image:

{

"mcpServers": { "xraylib": { "command": "docker", "args": ["run", "-i", "--rm", "ghcr.io/tschoonj/xraylib-mcp-server:latest"] } } }

With VS Code

Add to your VS Code settings (.vscode/settings.json or user settings):

{

"mcp.servers": { "xraylib": { "command": "uvx", "args": ["xraylib-mcp-server"] } } }

Or using the pre-built Docker image:

{

"mcp.servers": { "xraylib": { "command": "docker", "args": ["run", "-i", "--rm", "ghcr.io/tschoonj/xraylib-mcp-server:latest"] } } }

With Claude Code

Add the server using the CLI:

claude mcp add xraylib -- uvx xraylib-mcp-server

Or using the pre-built Docker image:

claude mcp add xraylib -- docker run -i --rm ghcr.io/tschoonj/xraylib-mcp-server:latest
As a development server
# Run in development mode with MCP inspector

uv run mcp dev src/xraylib_mcp_server/server.py

Using Docker
Pre-built images from GitHub Container Registry
# Pull the latest image

docker pull ghcr.io/tschoonj/xraylib-mcp-server:latest

Run with stdio transport

docker run -i --rm ghcr.io/tschoonj/xraylib-mcp-server:latest

Run with HTTP transport on port 8000

docker run --rm -p 8000:8000 ghcr.io/tschoonj/xraylib-mcp-server:latest xraylib-mcp-server --transport http --port 8000

Use a specific version

docker pull ghcr.io/tschoonj/xraylib-mcp-server:0.1.0 docker run -i --rm ghcr.io/tschoonj/xraylib-mcp-server:0.1.0

Local development with Docker
# Build the Docker image locally

docker build -t xraylib-mcp-server .

Run with stdio transport

docker run -i --rm xraylib-mcp-server

Run with HTTP transport on port 8000

docker run --rm -p 8000:8000 xraylib-mcp-server xraylib-mcp-server --transport http --port 8000

Development

Setup
# Clone the repository

git clone https://github.com/tschoonj/xraylib-mcp-server.git cd xraylib-mcp-server

Install development dependencies

uv sync --dev

Running tests
# Run all tests

uv run pytest

Run with coverage

uv run pytest --cov=src/xraylib_mcp_server --cov-report=html

Code quality
# Lint

uv run ruff check .

Format

uv run ruff format .

Type check

uv run mypy src/ --ignore-missing-imports

License

BSD 3-Clause License -- see LICENSE for details.

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Add tests for new functionality
  5. Run the test suite
  6. Submit a pull request
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