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CMB Data MCP Server

CMB Data MCP Server

by nesar-ai-assistant
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Python
Hybrid

CMB Data MCP Server

MCP server for public CMB power spectra, lensing bandpowers and LCDM parameter chains from Planck PR3 (2018), ACT DR6 and SPT-3G (D1 + 2018). It covers data access, quick and honest chi2 checks against LCDM, publication-style plots, and cross-experiment comparisons. It is part of the cosmo-*-mcp-server family (see docs/CONVENTIONS.md).

This is Phase 1 of ~/cmb_mcp_data_survey.md: spectra and chains only. It has no maps and no compiled likelihoods (see the TODO list below).

TT

Tools (13 science/meta + 4 dispatch)

tool

what it does

list_cmb_datasets / describe_cmb_dataset

dataset registry: products, units, verified URLs, citations

list_cmb_skills / load_cmb_skill

server-side recipes (also exposed as MCP prompts)

fetch_cmb_spectrum(dataset, spectrum, binned)

TT/TE/EE/BB/PP bandpowers written to a tidy CSV (+ covariance .npy when released)

plot_cmb_spectra

D_ell with errors, multi-experiment overlay, best-fit LCDM, residual panel

compute_cmb_residuals

chi2 / PTE against a theory spectrum. Uses the full covariance and windows for ACT and lensing; diagonal (indicative) for Planck/SPT plotting products

compute_lcdm_theory_spectrum (heavy)

camb LCDM spectra (optional dependency, lazy import, dispatchable). Falls back to the bundled Planck 2018 best-fit file

plot_lensing_spectrum

Planck/ACT/SPT [L(L+1)]^2 C_L^phiphi/2pi with LCDM, plus a fitted A_lens per experiment

fetch_cmb_chain

downloads and extracts ONE public chain (Planck 2018 plikHM TTTEEE+lowl+lowE+lensing, 65 MB; ACT DR6 ACT-lite / P-ACT, 5–7 MB)

analyze_chain (heavy)

getdist marginal stats (mean, std, 68/95% limits). Dispatch kernel downloads the chain on the node

plot_triangle

getdist triangle plot overlaying up to 3 chains

compare_parameter_constraints

whisker plot of H0/S8/Om/ns/sigma8 from chains and cited published tables, with n-sigma tensions

set_dispatch / get_dispatch / auth_status / export_dispatch_pack

hep-genesis IRI dispatch (family convention)

Related MCP server: spectra-mcp-server

Datasets

key

access

content

planck_pr3

bundled binned spectra + best-fit theory; unbinned spectra downloaded

PLA R3.01/R3.02 TT/TE/EE, low-ell BB, base_plikHM_TTTEEE_lowl_lowE_lensing minimum theory

act_dr6

download (287 kB)

ACT DR6 CMB-only (ACT-lite) sacc: 135 bandpowers, covariance, windows

spt3g_d1

bundled

SPT-3G D1 MV foreground-cleaned TT/TE/EE

spt3g_2018

bundled

SPT-3G 2018 TT/TE/EE MV bandpowers

planck_pr3_lensing

bundled

2018 conservative lensing bandpowers + CMB-marginalised covariance

act_dr6_lensing

bundled (extracted from the 361 MB tarball)

DR6 lensing baseline bins + covariance

spt3g_d1_lensing

bundled

D1 GMV lensing bandpowers, covariance, windows

planck_pr3_chains

download (65 MB)

single-family PLA zip, not the 11 GB grid

act_dr6_chains

download

ACT-lite and P-ACT-lite LCDM Cobaya chains

Provenance for every bundled file is in data/README.md.

Sanity checks (verified by tests)

  • Planck 2018 chain: H0 = 67.36 ± 0.54, Ωm = 0.3153 ± 0.0073, σ8 = 0.8111 ± 0.0060 (getdist output equals the PLA margestats).

  • Planck TT binned vs best fit: χ² ≈ 82.7 for 83 points. Lensing A_lens: Planck 1.01 ± 0.03, ACT 1.02 ± 0.03.

  • SH0ES vs Planck H0: 4.9σ. KiDS S8: −3.1σ. DES Y3 S8: −2.6σ.

Skills

cmb-tour, reproduce-planck-tt-spectrum, cmb-experiment-comparison, h0-s8-tension-whisker, hpc-dispatch-handoff.

Install / run

uv venv --python 3.12 .venv && uv pip install --python .venv/bin/python -e ".[dev]"
uv pip install --python .venv/bin/python --only-binary :all: camb   # optional (".[theory]")
.venv/bin/python -m mcp_server --transport stdio            # or ./run_server.sh
.venv/bin/python -m mcp_server --transport streamable-http --port 8012
MPLBACKEND=Agg .venv/bin/python -m pytest -q                # -m "not network" offline

Known limitations

  • The Planck and SPT-3G D1 spectra are the release plotting products, which ship no covariance. Their χ² values are diagonal-only and indicative.

  • ACT DR6 χ² fixes A_act = P_act = 1.

  • The SPT-3G D1 lensing A_lens comes out ≈ 0.92. candl's lensing-systematics emulator and M_L response corrections are not applied, so this is a known bias, not a physical result.

  • The bundled theory stops at ℓ = 2508. ACT/SPT bins beyond that need camb (lmax=6600).

  • ACT chain Ωm is derived assuming Σmν = 0.06 eV. ACT burn-in is 0.3, since LAMBDA lists none for the lite chains.

TODO — Phase 2: pip likelihoods (not implemented)

  • Planck: HiLLiPoP (PR4 high-ℓ TT/TE/EE) and LoLLiPoP (PR4 low-ℓ EE/BB), via planck-npipe / cobaya.

  • ACT: act_dr6_lenslike (full lensing likelihood with linear corrections), plus the ACT DR6 multi-frequency MFLike.

  • SPT: candl + spt_candl_data (SPT-lite TT/TE/EE and D1 lensing with its systematics emulator).

  • Tools: evaluate_cmb_likelihood(theory_file, likelihood), plus a profile likelihood in one parameter (heavy, dispatchable).

TODO — Phase 3: maps (not implemented)

  • Planck PR3/PR4 SMICA/Commander maps and the lensing κ map (healpy), ACT DR6 maps / κ map (pixell), SPT-3G D1 maps.

  • Tools: map cutouts, power spectra from maps (namaster), cross-correlation with galaxy surveys.

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