Chuk Mcp Lazarus MCP Server
chuk-mcp-lazarus
PyPI
v0.14.6
Published by an unidentified publisher — no publish provenance and no public repository, so the publisher could not be verified and the source cannot be independently located.
Mechanistic interpretability MCP server wrapping chuk-lazarus
The grade answers one question — how safe is this server for you to adopt — so it is computed in two auditable stages. Nothing below is an opinion or an LLM's guess; every line is a real term the deterministic engine applied, and the same input always yields the same number.
1. Threat score — 100 − 0 = 100. What the published surface and source actually contain:
The deterministic scan raised no scored threat in the surface it inspected — the threat score stayed at 100. Capability observations and advisory notes are recorded but never lower it.
2. Client adoption risk — 100 − 2 = 98. Three small, subtract-only factors that reflect your risk in adopting it — a clean scan proves less on a powerful, unverified or barely-inspectable package, so the grade says so plainly:
| Points | Adoption-risk factor |
|---|---|
| −2 | publisher verification (unlinked) — no provenance/repo link, but the shipped source was fully read |
Capability observations and info notes are shown under Findings but never scored.
Open any row's finding below for the file, line and evidence behind a deduction.
Findings 0
Tools 64
Each tool and what it can reach — statically extracted from the published source.
ablate_layersno sensitive capabilityadd_experiment_resultno sensitive capabilityanalyze_neuronno sensitive capabilityattention_headsno sensitive capabilityattention_patternno sensitive capabilityattribution_sweepno sensitive capabilitybranch_and_collapseno sensitive capabilitybuild_dark_tableno sensitive capabilitycompare_activationsno sensitive capabilitycompare_attentionno sensitive capability
Show 54 more tools ↓
compare_generationsno sensitive capabilitycompare_representationsno sensitive capabilitycompare_weightsno sensitive capabilitycomponent_interventionno sensitive capabilitycomputation_mapno sensitive capabilitycompute_steering_vectorno sensitive capabilitycompute_subspaceno sensitive capabilitycreate_experimentno sensitive capabilitydecode_residualno sensitive capabilitydirection_anglesno sensitive capabilitydiscover_neuronsno sensitive capabilityembedding_neighborsno sensitive capabilityevaluate_probeno sensitive capabilityextract_activationsno sensitive capabilityextract_directionno sensitive capabilityfeature_dimensionalityno sensitive capabilityfull_causal_traceno sensitive capabilitygenerate_textno sensitive capabilityget_experimentno sensitive capabilityget_model_infono sensitive capabilityhead_attributionno sensitive capabilityinject_residualno sensitive capabilitylayer_clusteringno sensitive capabilitylist_dark_tablesno sensitive capabilitylist_experimentsno sensitive capabilitylist_probesno sensitive capabilitylist_steering_vectorsno sensitive capabilitylist_subspacesno sensitive capabilityload_comparison_modelno sensitive capabilityload_modelno sensitive capabilitylogit_attributionno sensitive capabilitylogit_lensno sensitive capabilityneuron_traceno sensitive capabilitypatch_activationsno sensitive capabilitypredict_next_tokenno sensitive capabilityprobe_at_inferenceno sensitive capabilityresidual_atlasno sensitive capabilityresidual_decompositionno sensitive capabilityresidual_mapno sensitive capabilityresidual_matchno sensitive capabilityresidual_trajectoryno sensitive capabilityscan_probe_across_layersno sensitive capabilitysteer_and_generateno sensitive capabilitysubspace_decompositionno sensitive capabilitysubspace_surgeryno sensitive capabilitytoken_spaceno sensitive capabilitytokenizeno sensitive capabilitytop_neuronsno sensitive capabilitytrace_tokenno sensitive capabilitytrack_raceno sensitive capabilitytrack_tokenno sensitive capabilitytrain_probeno sensitive capabilityunload_comparison_modelno sensitive capabilityweight_geometryno sensitive capability
What this scan could not see
- Tools were statically extracted from the published source (64 recovered), not enumerated from a running server. Tool-poisoning, Unicode-smuggling, capability and toxic-flow analysis ran on this inferred surface, but a mis-parsed registration could be missed or mis-attributed, so tool-derived findings are capped below “confirmed”. To grade the real runtime surface, scan the running server: --command "npx -y <package>".
Versions 1
Scan history per published version. The engine is deterministic — the same version always yields the same score, so a changed score means the package itself changed.
| Version | Score | Findings | Engine | Scanned |
|---|---|---|---|---|
v0.14.6 latest |
A 98/100 | 0 | 1.13.0 | 2026-08-25 |
Embed this score
Show this server's live Trust Score in your README, docs or website. The badge is served straight from the registry and updates automatically after every rescan — no API key needed. It links back to this page, so anyone who sees the grade can also read the findings behind it instead of taking a number on faith.
Verify this score yourself
The score above is reproducible: the same package version always yields the same result. Run it locally or over the free API — no account, no LLM, fully deterministic.
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