MDEngine

MCP serverAI & models

MD workbench for agents: 13 analysis tools, renders, hosted GPU runs; LAMMPS + OpenMM.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the account tool from MDEngine

From the project's README

As published by forcefieldsilicon/mdengine in README.md.

by ForceField Silicon

A native macOS molecular-dynamics workbench: a Metal trajectory viewer, a command-line tool, and an MCP server that lets AI agents inspect trajectories and run LAMMPS simulations as detached background jobs.

Status: pre-release. Not yet distributed; the app is ad-hoc signed (builds run on the building machine only until notarization lands).

Parts

ProductWhat it is
MDEngine.appMetal viewer — orbit / pan / zoom camera, trajectory timeline with 20%/5% tick marks, CPK element colours, XYZ / extended-XYZ, live settings
mdengine-cliinfo / export / decimate / run on trajectories and decks
mdengine-mcpMCP stdio server — trajectory tools plus a detached LAMMPS job runner (submit_lammps / job_status / job_log / list_jobs / cancel_job)

Build

Requires macOS 14+ and Xcode command-line tools. LAMMPS (brew install lammps) is needed only for run / submit_lammps.

swift build -c release            # all three products
./scripts/make_app.sh             # assemble + install /Applications/MDEngine.app

Bundled examples

ExampleWhat it shows
lj_melt.xyz / lj_melt.inLennard-Jones argon melt — the minimal smoke test
fe_oxidation.xyz / fe_oxidation.inReaxFF iron oxidation: a bcc Fe slab meeting O₂ gas, using ffield.reax.Fe_O_C_H from the LAMMPS distribution

Trajectory readers are safe on in-flight dumps — a file a running simulation is still writing parses to its complete frames, so you can inspect a run mid-flight. Rows with non-finite (NaN/inf) coordinates are dropped.

Both decks are ready inputs for mdengine run and submit_lammps. Bare force-field names resolve automatically: if $LAMMPS_POTENTIALS is unset, MDEngine derives it from the LAMMPS install.

MCP server

mdengine-mcp is a dependency-free MCP stdio server, listed in the MCP Registry as com.forcefieldsilicon/mdengine (server.json in this repo). Each release ships a signed macOS MCP Bundle (mdengine-mcp-<version>-macos-arm64.mcpb): double-click it to install in Claude Desktop, or unpack it (mcpb unpack) for any other client. Built from source, register with Claude Code:

claude mcp add mdengine /path/to/.build/release/mdengine-mcp

or in Claude Desktop's claude_desktop_config.json:

{ "mcpServers": { "mdengine": { "command": "/path/to/.build/release/mdengine-mcp" } } }
ToolDoes
trajectory_infoFrames, atom counts, per-atom fields, elements, bbox, charge range
z_profileDeposition/oxidation depth analysis: substrate surface plane, probe penetration depths (min/mean/max), at-surface & in-flight counts, bound-probe charge, z histogram
render_videoTrajectory → MP4 (H.264) or animated GIF via the Metal renderer: camera angles, stride, cinematic orbit, baked scale-bar/frame annotations, per-element colors/sizes, style: "contrast" auto-visibility
render_imageOne frame → PNG with the same camera/style options — lets an agent see a simulation state
export_frameOne frame → XYZ; charges: true → extended-XYZ with the q column
decimateKeep every Nth frame (final frame always kept)
submit_lammpsDetached LAMMPS job: survives the server exiting and machine display-sleep (caffeinate), exit code recorded unattended
job_status / job_logState + live thermo tail / raw log tail
job_filesLocate a finished job's outputs (run dir + bookkeeping dir)
list_jobs / cancel_jobRegistry under ~/.mdengine/jobs/ / SIGTERM a run (state becomes cancelled)
list_hostsExecution hosts from ~/.mdengine/hosts.json and which is the default
fetch_jobPull a remote job's run directory (dumps, data) + logs into the local job dir under results/
run_lammpsSynchronous run for short tests only

Hosted GPU tier over MCP (no install)

The same jobs are reachable from any MCP client that speaks HTTP — Claude Code, Claude.ai custom connectors, Cursor, Goose — via the hosted endpoint's Streamable HTTP server:

claude mcp add --transport http mdengine-cloud https://api.forcefieldsilicon.com/mcp

Sign in when the client asks (OAuth 2.1: a consent page where you paste your API key once; the client keeps a token, the key stays with you). Scripted clients may instead send the key directly as --header "Authorization: Bearer mde_YOUR_KEY". The key comes with a prepaid credit pack (forcefieldsilicon.com/mdengine). initialize and tools/list work without signing in; tool calls without a credential return 401 with the OAuth Windows and Linux. The hosted tier is the supported path on both, and it is the full paid product: every tool below works from Claude Code on Windows exactly as on a Mac. In PowerShell, register at user scope so the server follows you into every folder, then sign in once:

claude mcp add --scope user --transport http mdengine-cloud https://api.forcefieldsilicon.com/mcp

Start claude, type /mcp, pick mdengine-cloud, choose Authenticate, and paste the key on the browser consent page (never into the chat). Decks written on Windows (CRLF line endings) are accepted as-is. The local viewer, renderer and CPU job runner are macOS-only today; a Windows/Linux local build is planned and demand decides its order, so say so if you need it.

discovery pointer, which is what makes clients offer the sign-in. Tools: account, capabilities, preflight_deck, submit_job (deck inline, ≤ 8 MB), create_job + start_job (big decks via presigned PUT), job_status, job_log, job_results, list_jobs, delete_results, cancel_job. Discovery card: https://api.forcefieldsilicon.com/.well-known/mcp/server-card.json. The hosted service (endpoint, billing, GPU launcher) is operated by ForceField Silicon and its source is not part of this repository; the client side of it (HostedClient, CLI run --gpu, MCP host=cloud) is here under the MIT license like everything else.

Preflight before spend (GJOB-118). GET /v1/capabilities publishes the hosted image's LAMMPS version, packages and every style with a gpu flag: true = KOKKOS-accelerated, false = the style exists but runs on the pod's CPU cores at the GPU rate. Every client checks a deck against it first — mdengine capabilities deck.in, the app's Run Accelerated, submit_lammps host=cloud, the hosted submit_job — refusing a deck whose styles the image lacks (LAMMPS would exit at startup) and warning when the pair style has no /kk variant (the run would not use the GPU). --force / force=true overrides; the server only advises (preflight in the start response), it never blocks.

Troubleshooting the hosted connector:

SymptomCause / fix
Client says authentication required / 401Use the client's sign-in (OAuth) and paste your mde_… key on the consent page, or add the header Authorization: Bearer mde_…. Keys are issued at purchase and shown once.
Consent page says the key was not recognisedKeys are mde_ + 32 hex characters; a revoked key no longer works. mdengine account prints the balance for a saved key.
"insufficient balance"Top up at forcefieldsilicon.com/mdengine; submissions need credit for at least 15 min at the GPU rate.
"gpu_runners_open_soon" (503)Runners are temporarily closed; credits are safe.
HTTP 429Too many keyless requests from one IP; add the key or slow down.
job_results says results unavailableFiles were deleted by delete_results, the run produced none, or the 30-day purge ran.
Job failed with runner_error / lammps_errorThe deck itself failed; job_results (if present) or job_log holds the LAMMPS error text.
Job failed with pod_lost / no_capacity / launch_timeout / gpu_unavailableInfrastructure (pod died, no GPU stock, a pod that never came up, or the host handed the pod no CUDA device); never billed, relaunched once automatically. Resubmit if it still fails.

Jobs run in the deck's own directory (relative read_data paths work) and launch with -sf omp -pk omp N so the OPENMP package is actually engaged; $LAMMPS_POTENTIALS is derived from the LAMMPS install when unset.

Remote hosts (run on your own Linux / GPU box)

The job runner can execute on another machine with the same tool contract: declare hosts in ~/.mdengine/hosts.json and pass host to submit_lammps (or set a default). The deck's directory is rsynced up (trajectories, checkpoints and logs excluded), LAMMPS starts under nohup with its exit code recorded remotely, and job_status / job_log / job_files / cancel_job work unchanged; fetch_job brings results back for trajectory_info, z_profile and the renderers.

{
  "default": "gpu1",
  "hosts": {
    "gpu1": {
      "ssh": "me@gpu1.example.net",
      "workdir": "~/mdengine-jobs",
      "lmp": "/usr/local/bin/lmp",
      "threads": 8,
      "launch": "{lmp} -in {input} -k on g 1 -sf kk -pk kokkos newton on neigh half -log {log}"
    }
  }
}

ssh is anything ssh accepts (key-based, non-interactive); lmp must be an absolute path (login PATH is not available over ssh); launch is optional — the default is the OpenMP form, and a GPU host is simply one whose template carries the KOKKOS flags. A remote deck must be self-contained within its own directory. The same trust model as local runs applies, on the remote machine.

Platform & limits

macOS 14+ (Apple Silicon or Intel). Trajectories are loaded whole into memory — files over 2 GB are refused with guidance to decimate or split first.

Security note

Running a LAMMPS input executes whatever the deck says. LAMMPS decks are programs, not data — they can invoke arbitrary shell commands (LAMMPS has a literal shell command). Treat a deck from someone else exactly like a shell script: read it before running it.

This applies doubly to the MCP server: an AI agent connected to mdengine-mcp can submit decks, and a submitted deck runs with your user's full privileges on this machine. That is the same trust model as any local dev tool (an agent that can run make can run anything), but be deliberate about which decks — and which agents — you hand to the job runner. Sandboxed execution (containers, no network, resource caps) is how a future hosted tier makes running untrusted decks safe; the local server does not sandbox.

Privacy

The local tools collect nothing; see PRIVACY.md, which also covers the hosted GPU tier.

License

MIT © Gitinama Inc. (d/b/a ForceField Silicon)

Tools it offers (12)

What this server listed when ahel dialed its public endpoint in Sep 2026, with no key and no account of yours. The names are the server’s own.

  • account
  • submit_job
  • create_job
  • start_job
  • job_status
  • job_log
  • job_results
  • list_jobs
  • delete_results
  • capabilities
  • preflight_deck
  • cancel_job

Signals

Last commit
Sep 2026
Advanced
Delivery
mdengine MCP server → your ahel gateway (mcp.ahel.ai) → every connected AI client.
Catalog kind
mcp-server
Gateway key
com-forcefieldsilicon-mdengine
Source
github.com/forcefieldsilicon/mdengine
Hosted endpoint
https://api.forcefieldsilicon.com/mcp