B-

pypi:scicomp-neural-mcp

https://pypi.org/project/scicomp-neural-mcp/
81/100 · MCP Trust Grade · checked 2h ago · MCP 0.1.6

What it offers — 30 tools · Finance & Crypto

info
create_lattice_potential
create_custom_potential
create_gaussian_wavepacket
create_plane_wave
solve_schrodinger
solve_schrodinger_2d
get_task_status
get_simulation_result
analyze_wavefunction
render_video
visualize_potential
define_model
load_dataset
train_model
evaluate_model
get_experiment_status
get_model_summary

+12 more tools

Spec / packaging20%100
Security (OWASP MCP)30%65
Maintenance / popularity20%83
Tool hygiene15%80
Transparency / provenance15%85

Findings

INFO Static analysis of PyPI package scicomp-neural-mcp@0.1.6 (source: github.com/andylbrummer/math-mcp) — stdio server, no remote endpoint. Runtime behavior not measured.
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MCP Trust report card — pypi:scicomp-neural-mcp grade B-
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MCP Trust Grade B- · wmcp.sh
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How this grade is computed. An open, independent rubric — Spec conformance (20%), Security mapped to the OWASP MCP Top 10 (30%), Reliability (20%), Tool hygiene (15%), Transparency (15%) — run by connecting to the server and inspecting its real MCP surface. The grade is free and identical whether or not the operator pays. v1 uses static + spec signals from a single connection; continuous uptime, real latency, and annotation-truthing (declared readOnly vs observed behavior) layer on via the wmcp.sh proxy.