Autonomath MCP Server
autonomath-mcp
PyPI
v0.5.0
Published by shigetosidumeda-cyber — no publish provenance, so origin is unverified, but the source is public: the repository link below is self-declared yet readable, so you can inspect the code before adopting it.
REST + MCP context-compression layer for Japanese institutional public data. jpcite turns long PDFs, official pages, and search results into compact Evidence Packets with source URLs, fetched timestamps, known gaps, and compatibility/exclusion rules before downstream AI agents draft answers. 3 yen/billable unit metered (3.30 tax-incl), anonymous 3/day per IP free.
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 − 7 = 93. 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 |
|---|---|
| −6 | capability blast radius (high) — client exposure if the model is manipulated |
| −1 | publisher verification (public source) — no provenance, but the source is public and inspectable |
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 3
high Tool "rule_tree_batch_eval_chain" exposes command/code executionMTC-CAP-001
Tool "rule_tree_batch_eval_chain" appears to run shell commands or evaluate code (keyword "eval" in tool name). Arbitrary execution driven by model input is one of the most dangerous MCP capabilities; combined with any untrusted input it becomes RCE.
Fix: Sandbox execution, allowlist commands/arguments, and never pass model output to a shell unescaped.
Location: tool rule_tree_batch_eval_chain
high Shell/command execution in server code (src/jpintel_mcp/mcp/jpcite_prompts.py)MTC-SRC-002
In the server's implementation (`src/jpintel_mcp/mcp/jpcite_prompts.py:334`): Spawning a shell/process is command-execution capability; with unsanitized tool input it is command injection / RCE. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: nderer": _renderer} exec(body_src, ns) # noqa: S102 — controlled scope, no external input cb = ns["_cb"] cb
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server src/jpintel_mcp/mcp/jpcite_prompts.py
low Mutating tool "rule_tree_batch_eval_chain" declares no destructiveHintMTC-CAP-005
Tool "rule_tree_batch_eval_chain" can mutate/egress but declares no destructiveHint. Clients that don't default to spec-safe behavior may not prompt before running it.
Fix: Declare accurate annotations, and gate destructive tools on user confirmation regardless.
Location: tool rule_tree_batch_eval_chain
Tools 45
Each tool and what it can reach — statically extracted from the published source.
rule_tree_batch_eval_chainruns code / shellanonymized_cohort_query_with_redact_chainno sensitive capabilityapply_eligibility_chain_amno sensitive capabilitybenchmark_cohort_average_amno sensitive capabilitycase_cohort_match_amno sensitive capabilitycase_law_searchno sensitive capabilitycase_law_summaryno sensitive capabilitycase_law_to_law_refsno sensitive capabilitycases_by_industry_size_prefno sensitive capabilitycheck_answer_freshnessno sensitive capability
Show 35 more tools ↓
check_foreign_capital_eligibilityno sensitive capabilitycompose_audit_workpaperno sensitive capabilitycross_source_score_amno sensitive capabilitydiscover_relatedno sensitive capabilitydynamic_eligibility_check_amno sensitive capabilityfact_signature_verify_amno sensitive capabilityfind_complementary_programs_amno sensitive capabilityfind_fdi_friendly_subsidiesno sensitive capabilityfind_municipality_subsidiesno sensitive capabilityget_evidence_packetno sensitive capabilityget_evidence_packet_batchno sensitive capabilityget_houjin_360_amno sensitive capabilityget_law_article_enno sensitive capabilityget_program_eligibility_predicateno sensitive capabilityget_tax_treatyno sensitive capabilitylaw_related_programs_crossno sensitive capabilitylist_edinet_disclosuresno sensitive capabilitymatch_cohort_5d_amno sensitive capabilityportfolio_optimize_amno sensitive capabilitypredictive_subscriber_fanout_chainno sensitive capabilityprogram_active_periods_amno sensitive capabilityprogram_compatibility_pair_amno sensitive capabilityprogram_eligibility_by_form_amno sensitive capabilityprogram_eligibility_for_houjin_amno sensitive capabilityprogram_full_contextno sensitive capabilityprogram_risk_score_amno sensitive capabilityprograms_by_corporate_form_amno sensitive capabilitysearch_invoice_by_houjin_partialno sensitive capabilitysearch_laws_enno sensitive capabilitysession_multi_step_eligibility_chainno sensitive capabilitysimulate_application_amno sensitive capabilitysupplier_chain_amno sensitive capabilitytime_machine_snapshot_walk_chainno sensitive capabilitytrack_amendment_lineage_amno sensitive capabilityverify_citationsno sensitive capability
What this scan could not see
- Tools were statically extracted from the published source (45 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 |
|---|---|---|---|---|
v0.5.0 latest |
A 93/100 | 3 | 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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