Labsco
MCP SERVER

A shelf of MCP servers for scientific work — Materials Project data, sandboxed Python, DFT through GPAW, a live Jupyter kernel, Mathematica, web and academic search — each started with one `uvx mcp-science <server-name>` command.

Physical Sciences & Scientific Computing
Summary
A shelf of research servers, one command each.

The value is the shelf rather than any single server: retrieval, computation and remote execution all speak the same protocol and start the same way, so a research assistant can hold several at once without a different install story for each. Read the server's own README before you wire it in — SSH Exec and Python Code Execution both run code, and the limits on each are written in its directory, not in the shared one.

What it is

A monorepo of open-source MCP servers built for scientific research, published as one PyPI package (`mcp.science`, version 0.1.7). Each server lives in its own directory under `servers/` with its own README, and any of them starts with `uvx mcp-science <server-name>` — that single command handles installation and execution, so a client entry is just `uvx` plus two arguments. MIT licensed.

What you get
  • **Materials Project** — search, visualise and manipulate materials-science data from the Materials Project database; needs a Materials Project API key
  • **Python Code Execution** — runs Python snippets in a sandboxed environment with restricted standard-library access, so analysis the assistant writes runs somewhere it cannot reach your system
  • **GPAW Computation** — density-functional-theory calculations through the GPAW package
  • **Jupyter-Act** — executes notebook cells against a running Jupyter kernel
  • **Mathematica-Check** — evaluates small Wolfram Language snippets through a headless Mathematica instance
  • **Web Fetch** — fetches and processes HTML, PDF and plain-text content from the web so the assistant can quote or summarise it
  • **TXYZ Search** — web, academic and "best effort" searches through the TXYZ API; needs a TXYZ API key
  • **SSH Exec** — runs pre-validated commands on remote machines over SSH, with configurable authentication and command whitelists
  • **NEMAD** — tools for inspecting NEMAD data sets
  • **TinyDB** — CRUD access to a lightweight JSON database, for small structured things the assistant needs to keep
  • **Timer** — a countdown timer that streams progress updates, demonstrating MCP notifications
  • **Example Server** — the minimal pieces a server implementation needs, as a starting point for your own
Requirements

`uv` and an MCP-enabled client — Claude Desktop, VSCode, Goose and 5ire are the ones named. `uvx mcp-science <server-name>` downloads the package from PyPI and runs the requested entry point, so there is nothing to install per server. Two of them need keys you bring yourself: Materials Project and TXYZ Search. The rest of what a server needs depends on which one you start — SSH Exec wants credentials and a command whitelist for the machines it will touch, Mathematica-Check wants a headless Mathematica, GPAW Computation wants GPAW. Each server's own README under `servers/` is where those specifics live, and `mcpm` will wire servers into supported clients for you if you switch clients often.

Setup effort

One command — uvx mcp-science web-fetch