Skip to main content
Glama
KonstantinGerbig

spectra-mcp-server

by KonstantinGerbig
OverviewSchemaSourceRelated ServersScoreDiscussionsAdmin
Hybrid

spectra-mcp-server

Part 1 of the client-server agent tutorial. An MCP server that exposes science tools — CLASS matter power spectra compared against eBOSS DR14 Lyman-α forest data — to any LLM agent.

Part 2, the multi-agent client that drives this server, lives in multiagent-client-demo. Setup instructions for both repos are in that repo's prep.md.

The one idea this repo teaches

The science code stays in usual Python. The MCP wrapper only publishes it.

  • tools/ is an ordinary science package. It never imports MCP. The power-spectrum example lives in tools/spectra_tools.py.

  • mcp_server/ is a ~70-line generic wrapper. It reads one line of config from pyproject.toml, imports the science package, and registers every function listed in its __all__ as an MCP tool.

[tool.mcp-server]
tool_modules = ["tools"]

Your type hints, Pydantic Field constraints, and docstrings become the tool schema agents see. To build your own server: drop your modules into tools/ (or point that one config line at your own package), list the public functions in __all__, done.

Related MCP server: LocalData MCP Server

Layout

data/DR14_pm3d_19kbins.txt        eBOSS DR14 Ly-α P(k): 19 bins of (k, P, σ)
tools/
  cosmology.py                    CLASS parameter sets (Planck 2018) + run_class()
  spectra_tools.py                the 4 tool functions + ArtifactResult contract
  __init__.py                     __all__ — ONLY these names become tools
mcp_server/                       generic drop-in wrapper (FastMCP)
notebooks/01_manual_pipeline.ipynb  a walkthrough: science → tools → server
tests/test_tools.py               tools tested as plain Python, no MCP needed

About the data file

DR14_pm3d_19kbins.txt is taken from marius311/mpk_compilation (Chabanier, Millea & Palanque-Delabrouille 2019, arXiv:1905.08103): the z = 0 linear matter power spectrum inferred from the eBOSS DR14 Ly-α forest. Mind the file's mixed units — k is in 1/Mpc while P(k), σ are in (Mpc/h)³ (the source notebook plots errorbar(k/h, Pk)). tools/spectra_tools.py does the k/h conversion once, on load; read the file any other way and the data appears offset from theory by a factor ~2.

Tools

tool

what it does

get_eboss_data()

return the 19 observed (k, P(k), σ) bins

list_cosmology_models()

valid model names (lcdm, nu_mass, wcdm) + tunables

compute_power_spectrum(model, output_dir, ...)

run CLASS, write pk_<model>.csv

plot_power_spectra(spectrum_files, output_dir, ...)

two-panel figure: P(k) + data, ratio panel

Two conventions worth copying into any science MCP server:

  1. Every tool returns {status, files, message, metadata} (ArtifactResult).

  2. Arrays move between tools as file paths, never through the agent's context window.

Install

conda create -n spectra-tutorial python=3.12 -y
conda activate spectra-tutorial
pip install -e ".[dev]"       # classy compiles from source; see prep.md if it fails
pytest                        # 7 tests, no server or API key needed

Run the server

Streamable HTTP — the server is a visible process with a URL:

python -m mcp_server --transport streamable-http --port 8000

Clients connect to http://127.0.0.1:8000/mcp. Stop the server with Ctrl+C (Ctrl+Z only suspends it, leaving the port taken — if that happens, just start the server again: it detects a leftover mcp_server holding the port and clears it automatically).

To use this server from Claude Code, the Claude desktop app, Codex, Cursor, or any other MCP client — or to run it alongside gaia-mcp-server (ports 8000/8001) — see docs/mcp-clients.md; a checked-in .mcp.json already wires it into Claude Code.

Try the hosted instance — no install needed

A live copy of this server (and its Gaia twin) is running for tutorial sessions:

server

MCP endpoint

spectra

https://spectra.77-42-88-84.sslip.io/mcp

gaia

https://gaia.77-42-88-84.sslip.io/mcp

Connect from any MCP client, for example:

claude mcp add --transport http spectra https://spectra.77-42-88-84.sslip.io/mcp

(Claude desktop app: Settings → Connectors → Add custom connector → paste the endpoint. Cursor: a "url" entry in mcp.json.)

Ask the agent to save files under /srv/artifacts/<your-name> — that is the server's disk — then browse your figures at https://files.77-42-88-84.sslip.io/. This is a small demo box: be gentle, and expect it to be rebuilt or offline outside tutorial sessions.

Start with the notebook

notebooks/01_manual_pipeline.ipynb builds everything up in order: the data, the science by hand, the same science as tools, then the server. Committed outputs let you read it without running anything.

This server cannot be installed

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Maintenance

ActivityMaintained
ResponsivenessNo issues

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Connectors

Related MCP Servers

  • Astro MCP

    SandyYuan
    F
    license
    Not graded
    quality
    D
    maintenance
    Provides unified natural language access to 40+ astronomical databases and surveys including DESI, SIMBAD, SDSS, and Gaia, enabling researchers to search, retrieve, and analyze astronomical data without learning complex APIs.
    6
    -

  • LocalData MCP Server

    ChrisGVE
    A
    license
    Not graded
    quality
    A
    maintenance
    Gives LLM agents access to local and remote data via databases, files, graphs, and structured documents, along with a full data science toolkit for analysis and modeling.
    3
    Apache 2.0

  • bbn-mcp-server

    nesar
    F
    license
    Not graded
    quality
    D
    maintenance
    Exposes Big Bang Nucleosynthesis computation and analysis tools to LLM agents, enabling them to scan parameters like baryon density, extra relativistic species, and neutron lifetime, and to fit abundances against observations.
    -