fdmnes-mcp 0.1.0

MCP server wrapping FDMNES (X-ray spectroscopy ab-initio code) for natural-language driven workflows in Claude Code, Claude Desktop, and other MCP clients.

fdmnes-mcp

MCP (Model Context Protocol) server that wraps FDMNES — the ab-initio Fortran code for X-ray spectroscopy by Yves Joly at Institut Néel CNRS, Grenoble. Drive FDMNES through Claude Desktop, Claude Code, Codex CLI, Cline, or any other MCP-aware client with natural-language tool calls.

Build and validate input files, launch parallel mpirun fdmnes_mpi jobs asynchronously, poll status, fetch outputs, plot spectra, and look up any of FDMNES's ~350 input keywords from a source-grounded catalog — without ever leaving the chat.

About FDMNES. FDMNES (Finite Difference Method Near Edge Structure) computes XANES, EXAFS (via the FDMX extension), XMCD, RXS/DAFS, RIXS, NRIXS / X-Raman, optic, and emission spectra. Two solver engines: a 3D real-space finite-difference solver (full-potential) and a multiple-scattering Green's function (muffin-tin). Free download at https://fdmnes.neel.cnrs.fr/. This wrapper does NOT redistribute FDMNES itself — you install FDMNES separately.

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Install

1. Install FDMNES

If you haven't already, grab FDMNES from https://fdmnes.neel.cnrs.fr/download/. You want either:

• the parallel Linux executable (parallel_fdmnes zip — recommended), or
• the Fortran source + the MUMPS / ScaLAPACK / OpenMPI toolchain (build it yourself).

Make sure your FDMNES binary is executable (chmod +x <binary>) and ideally on $PATH. The MCP server autodetects it from $PATH, then from common install directories (~/fdmnes, ~/FDMNES, /opt/fdmnes, /usr/local/fdmnes); override with the FDMNES_BIN env var if needed.

2. Install fdmnes-mcp

From PyPI (recommended once a release is published):

pip install fdmnes-mcp

From GitHub main (bleeding edge):

pip install git+https://github.com/Joint-Photon-Sciences-Institute/fdmnes-mcp.git

From a local checkout (for development):

git clone https://github.com/Joint-Photon-Sciences-Institute/fdmnes-mcp.git
cd fdmnes-mcp
python3 -m venv .venv
.venv/bin/pip install -e .

After install, the fdmnes-mcp console script is on your $PATH and equivalent to python -m fdmnes_mcp.

3. Verify the wiring

fdmnes-mcp --info     # or: python -m fdmnes_mcp --info

Prints the resolved paths and flags anything missing. Example output:

fdmnes-mcp configuration
========================

  FDMNES binary       : /usr/local/bin/fdmnes_mpi
      exists / x-bit  : True / True
  Bundle directory    : /opt/fdmnes/linux_bundle/fdmnes_Linux
      exists          : True
  Examples directory  : /opt/fdmnes/linux_bundle/fdmnes_Linux/Sim/Test_stand/in
      exists          : True
  Docs directory      : /.../site-packages/fdmnes_mcp/data/docs  (packaged)
      exists          : True
  Work directory      : /home/you/fdmnes-jobs
  mpirun default -np  : 4

All paths resolved.

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Register with your MCP client

Claude Code

claude mcp add fdmnes -- fdmnes-mcp

(If fdmnes-mcp isn't on your $PATH, use the absolute path returned by which fdmnes-mcp.)

Claude Desktop

Edit claude_desktop_config.json (location varies by OS: ~/Library/Application Support/Claude/ on macOS, %APPDATA%\Claude\ on Windows, ~/.config/Claude/ on Linux):

{
  "mcpServers": {
    "fdmnes": {
      "command": "fdmnes-mcp"
    }
  }
}

To override defaults via environment variables:

{
  "mcpServers": {
    "fdmnes": {
      "command": "fdmnes-mcp",
      "env": {
        "FDMNES_BIN": "/opt/fdmnes/fdmnes_mpi",
        "FDMNES_MPI_DEFAULT_NP": "8"
      }
    }
  }
}

Codex CLI

In your ~/.codex/config.toml:

[mcp_servers.fdmnes]
command = "fdmnes-mcp"

Cline (VS Code)

Edit cline_mcp_settings.json (Cline → MCP Servers → Configure):

{
  "mcpServers": {
    "fdmnes": {
      "command": "fdmnes-mcp",
      "transport": "stdio"
    }
  }
}

Any generic MCP client

Run the binary as a stdio server:

fdmnes-mcp

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Quick start (Claude)

After registering, try:

List the bundled FDMNES examples, then run the Cu K-edge one on 4 ranks and plot the convolved spectrum when it finishes.

Claude will call (roughly):

1. fdmnes_list_examples → see Cu
2. fdmnes_run_example(example_name="Cu", np=4) → get a job_id
3. fdmnes_status(job_id) until status == "completed"
4. fdmnes_fetch_result(job_id) → returns output paths
5. fdmnes_plot_spectrum(path=".../Cu_conv.txt") → renders the spectrum

Or for a new material:

Scaffold an SCF XANES job for Fe₂O₃ at the Fe K-edge with Hubbard U = 5 eV under ~/jobs/fe2o3/, then run it on 8 ranks.

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Configuration

All paths are auto-detected with sensible fallbacks. Override any of them via environment variables:

Variable	Default	Purpose
FDMNES_BIN	autodetect from $PATH and common installs	FDMNES binary (parallel or serial)
FDMNES_BUNDLE_DIR	autodetect	Directory with fdmfile.txt + Sim/Test_stand/
FDMNES_EXAMPLES_DIR	$FDMNES_BUNDLE_DIR/Sim/Test_stand/in	Bundled _inp.txt examples
FDMNES_DOCS_DIR	packaged docs	Override path to docs (keyword DB source)
FDMNES_WORK_DIR	~/fdmnes-jobs	Default cwd for new jobs
FDMNES_MPI_DEFAULT_NP	4	Default -np for mpirun

Call fdmnes_get_config inside a Claude session at any time to see what's currently active.

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Tool reference

27 tools across 6 categories (+ 8 resources). See src/fdmnes_mcp/tools/ for implementations.

I/O & inspection

Tool	Purpose
fdmnes_get_config	Show MCP paths + binary status
fdmnes_list_examples	List bundled _inp.txt examples
fdmnes_read_input	Parse an _inp.txt into structured blocks
fdmnes_read_spectrum	Read X.txt / X_conv.txt into arrays (auto-downsampled)
fdmnes_summarise_spectrum	Compact metadata-only view (no arrays)
fdmnes_read_bav	Extract release / point group / Symsite / SCF trace / Fermi level / parallel banner from a _bav.txt
fdmnes_list_outputs	List FDMNES output files under a prefix or directory

Authoring

Tool	Purpose
fdmnes_keyword_lookup	Look up a keyword (name or alias) → args, default, effect, source ref
fdmnes_keyword_search	Substring search across name / alias / effect text
fdmnes_list_keyword_categories	List the ~16 categories in the keyword DB
fdmnes_validate_input	Lint an _inp.txt against the keyword catalog
fdmnes_build_input	Build an _inp.txt from structured params

Execution (async)

Tool	Purpose
fdmnes_run	Launch mpirun fdmnes in the background → returns a job_id
fdmnes_run_example	One-shot: select a bundled example by name and launch
fdmnes_status	Poll job status + stdout/stderr tails
fdmnes_list_jobs	List all jobs launched in this session
fdmnes_cancel_job	Terminate a running job
fdmnes_fetch_result	Once a job completes, list its output files
fdmnes_reconvolve	Generate + run a convolution-only job that re-broadens an existing output

Plotting

Tool	Purpose
fdmnes_plot_spectrum	Render an FDMNES output to PNG (base64 + optional save path)
fdmnes_compare_spectra	Overlay multiple spectra with optional normalisation

Workflow templates

Tool	Purpose
fdmnes_template_xanes	Scaffold a basic XANES job (FDM or MS)
fdmnes_template_scf_xanes	XANES with SCF (and optional Hubbard U)
fdmnes_template_fdmx_exafs	EXAFS via FDMX (K-edge)
fdmnes_template_rxs	Resonant diffraction with one or more reflections
fdmnes_template_xmcd	Magnetic / XMCD with circular polarisation

Escape hatch

Tool	Purpose
fdmnes_run_shell	Run any shell command in the FDMNES workspace (sparingly)

Resources

Read-only docs available at:

URI	Content
fdmnes://config	Server config snapshot
fdmnes://docs/methods	FDM vs MST, DFT/TDDFT, defaults
fdmnes://docs/io	Input / output file structure
fdmnes://docs/keywords	Full keyword reference (large)
fdmnes://docs/pipelines	16 workflow recipes
fdmnes://docs/examples	Annotated catalog of bundled inputs
fdmnes://docs/keyword/{name}	Reference card for a single keyword

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Architecture

src/fdmnes_mcp/
├── __main__.py                # entry point with --info / --help / --version
├── server.py                  # FastMCP setup + tool/resource registration
├── config.py                  # autodetection + env-var-driven paths
├── session.py                 # JobManager (asyncio subprocess registry)
├── parsers/
│   ├── input_parser.py        # _inp.txt → structured blocks
│   ├── spectrum_parser.py     # X.txt / X_conv.txt → numpy arrays
│   ├── bav_parser.py          # _bav.txt → highlights
│   └── keyword_db.py          # ~770-entry keyword DB (mined from packaged docs)
├── tools/
│   ├── io_tools.py
│   ├── authoring_tools.py
│   ├── execution_tools.py     # async run / status / fetch
│   ├── plot_tools.py
│   ├── template_tools.py      # workflow one-shots
│   └── shell_tools.py
├── resources/docs.py          # fdmnes:// resource URIs
└── data/docs/                 # packaged reference docs (markdown)

The keyword DB is mined from the shipped data/docs/keyword-reference.md at server startup. Override with FDMNES_DOCS_DIR to point at a different docs tree (e.g. a forked / extended catalog).

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Citing FDMNES

If you publish results obtained with FDMNES (with or without this wrapper), the FDMNES author asks that you cite the following, as listed in the FDMNES User's Guide:

• Main FDMNES paper: O. Bunau and Y. Joly, J. Phys.: Condens. Matter 21, 345501 (2009).
• MUMPS-accelerated FDM: S. A. Guda et al., J. Chem. Theory Comput. 11, 4512-4521 (2015).
• FDMX EXAFS extension: J. D. Bourke, C. T. Chantler, Y. Joly, J. Synchrotron Rad. 23, 551-559 (2016).
• Surface RXD: Y. Joly et al., J. Chem. Theory Comput. 14, 973-980 (2018).
• X-Raman / NRIXS: Y. Joly, C. Cavallari, S. A. Guda, C. J. Sahle, J. Chem. Theory Comput. 13, 2172-2177 (2017).
• International Tables for Crystallography, Volume I (2021, 2022).

This wrapper does not need a separate citation, but a link or acknowledgement is appreciated:

FDMNES jobs were driven through the fdmnes-mcp wrapper (Joint Photon Sciences Institute, https://github.com/Joint-Photon-Sciences-Institute/fdmnes-mcp).

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Contributing & releases

Issues and pull requests welcome at https://github.com/Joint-Photon-Sciences-Institute/fdmnes-mcp.

Release process (for maintainers):

1. Bump version in pyproject.toml.
2. Commit, tag (git tag v0.x.y), push the tag (git push --tags).
3. The Publish to PyPI GitHub Actions workflow builds and publishes via PyPI Trusted Publishing. No API tokens needed in the repo — the project's PyPI page must be configured to trust this repo + workflow on first release (one-time setup).

License

This wrapper is released under the BSD 3-Clause License. FDMNES itself is independent software with its own distribution terms; see https://fdmnes.neel.cnrs.fr/ for FDMNES licensing questions.

Acknowledgements

Built in the style of xraylarch-mcp. Thanks to Yves Joly and the FDMNES developers for making the code freely available, and to the MCP / FastMCP authors for the protocol that makes wrappers like this trivial.