Aihydro Tools MCP Server
aihydro-tools
PyPI
v2.1.0
Published by ai-hydro — 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.
AI-Hydro: hydrological research tools as an MCP server for AI agents
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 − 11 = 89. 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 |
|---|---|
| −10 | capability blast radius (critical) — 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 7
critical Completed toxic-flow trifecta across toolsMTC-FLOW-002
This server (without client built-ins) exposes a complete data-exfiltration chain: check_record_length → list_available_tools → preview_list_modules. Untrusted input is ingested, private data is read, and it can be sent to an external sink via the agent composing the tools (→). Static analysis proves the primitive exists, not that a specific run will occur.
Fix: Remove one leg of the trifecta: isolate untrusted-input tools from secret-reading tools and from egress tools, or require human approval between them.
Location: flow check_record_length → list_available_tools → preview_list_modules
high Shell/command execution in server code (ai_hydro/gee/auth.py)MTC-SRC-002
In the server's implementation (`ai_hydro/gee/auth.py:84`): 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: try: proc = subprocess.run( ["gcloud", "projects", "list", "--format=json(projectId,name,project
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 ai_hydro/gee/auth.py
high Shell/command execution in server code (ai_hydro/mcp/tools_execution.py)MTC-SRC-002
In the server's implementation (`ai_hydro/mcp/tools_execution.py:90`): 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: onic() result = subprocess.run( [sys.executable, "-"], input=full_script, ca
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 ai_hydro/mcp/tools_execution.py
high Shell/command execution in server code (ai_hydro/mcp/tools_session.py)MTC-SRC-002
In the server's implementation (`ai_hydro/mcp/tools_session.py:56`): 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: p. result = subprocess.run( [sys.executable, "-m", "pip", "list", "--format=json"],
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 ai_hydro/mcp/tools_session.py
medium Hardcoded egress to an external endpoint (ai_hydro/gee/auth.py)MTC-SRC-003
In the server's implementation (`ai_hydro/gee/auth.py:131`): A hardcoded outbound call to a fixed external host inside server code is a classic exfiltration/telemetry channel — especially paired with reads of local data. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: t()) response = requests.get( "https://cloudresourcemanager.googleapis.com/v1/projects",
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 ai_hydro/gee/auth.py
low Shell/command execution in packaging/dev tooling (bench/gen_scorecard.py)MTC-SRC-002
In a packaging/dev/install script (shipped, but not the server runtime) (`bench/gen_scorecard.py:99`): 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: lush=True) result = subprocess.run(cmd, capture_output=False) print(f"Exit code: {result.returncode}", flush=Tru
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 bench/gen_scorecard.py
low Shell/command execution in packaging/dev tooling (tests/test_capsule.py)MTC-SRC-002
In a packaging/dev/install script (shipped, but not the server runtime) (`tests/test_capsule.py:448`): 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: eypatch) proc = subprocess.run( [sys.executable, str(cap / "replay.py")], capture_output
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 tests/test_capsule.py
Tools 147
Each tool and what it can reach — statically extracted from the published source.
check_record_lengthingests untrusted inputcheck_usgs_qualification_codesingests untrusted inputcompute_flow_duration_curveingests untrusted inputdata_fetch_backgroundingests untrusted inputdescribe_toolingests untrusted inputdescribe_toolsingests untrusted inputfetch_camels_usingests untrusted inputfetch_forcing_dataingests untrusted inputfetch_streamflow_dataingests untrusted inputget_data_fetch_resultingests untrusted input
Show 137 more tools ↓
list_available_toolsreads sensitive datapreview_list_modulesnetwork egressadd_assumptionno sensitive capabilityadd_claimno sensitive capabilityadd_journal_entryno sensitive capabilityadd_noteno sensitive capabilityadd_session_to_projectno sensitive capabilityaihydro_chat_statusno sensitive capabilityaihydro_describe_capabilityno sensitive capabilityaihydro_rebind_chatno sensitive capabilityarchive_sessionno sensitive capabilityaudit_interpretationno sensitive capabilitybind_map_to_claimno sensitive capabilitycancel_jobno sensitive capabilitycheck_registry_stalenessno sensitive capabilitycheck_regulated_basinno sensitive capabilitycheck_stationarityno sensitive capabilitycheck_temporal_alignmentno sensitive capabilitycheck_unit_consistencyno sensitive capabilitycheck_water_balance_consistencyno sensitive capabilityclear_sessionno sensitive capabilitycompute_design_hydrographno sensitive capabilitycompute_drought_indexno sensitive capabilitycompute_flood_frequencyno sensitive capabilitycompute_soil_loss_rusleno sensitive capabilitycompute_spectral_indexno sensitive capabilitycompute_twino sensitive capabilitycourse_get_curriculumno sensitive capabilitycourse_get_stateno sensitive capabilitycourse_navigateno sensitive capabilitycourse_scaffoldno sensitive capabilitycourse_set_progressno sensitive capabilitycreate_cn_gridno sensitive capabilitydefine_experimentno sensitive capabilitydelineate_watershedno sensitive capabilitydelineate_watershed_from_pointno sensitive capabilitydelineation_doctorno sensitive capabilitydescribe_model_spaceno sensitive capabilitydraft_claim_from_runno sensitive capabilityexport_inundation_surrogate_datasetno sensitive capabilityexport_sessionno sensitive capabilityextract_geomorphic_parametersno sensitive capabilityextract_hydrological_signaturesno sensitive capabilitygee.extract_timeseriesno sensitive capabilitygee.preview_layerno sensitive capabilitygee.statusno sensitive capabilityget_citation_by_doino sensitive capabilityget_dataset_infono sensitive capabilityget_equation_definitionno sensitive capabilityget_experiment_tableno sensitive capabilityget_inundation_physics_resultno sensitive capabilityget_inundation_surrogate_resultno sensitive capabilityget_leaderboardno sensitive capabilityget_library_referenceno sensitive capabilityget_metric_definitionno sensitive capabilityget_model_resultsno sensitive capabilityget_project_summaryno sensitive capabilityget_researcher_profileno sensitive capabilityget_session_healthno sensitive capabilityget_session_raw_stateno sensitive capabilityget_session_summaryno sensitive capabilityget_training_statusno sensitive capabilityget_variable_definitionno sensitive capabilityget_workflow_manifestno sensitive capabilityindex_literatureno sensitive capabilityindex_passagesno sensitive capabilitylist_assumptionsno sensitive capabilitylist_available_workflowsno sensitive capabilitylist_cached_citationsno sensitive capabilitylist_claimsno sensitive capabilitylist_featuresno sensitive capabilitylist_jobsno sensitive capabilitylist_known_datasetsno sensitive capabilitylist_known_metricsno sensitive capabilitylist_known_variablesno sensitive capabilitylist_registry_claimsno sensitive capabilitylist_relevant_clisno sensitive capabilitylist_skillsno sensitive capabilitylist_spectral_indicesno sensitive capabilityload_skillno sensitive capabilitylog_researcher_observationno sensitive capabilitylookup_citationno sensitive capabilitymap_add_layer_from_runno sensitive capabilitymap_apply_symbologyno sensitive capabilitymap_fit_extentno sensitive capabilitymap_fit_layerno sensitive capabilitymap_flood_inundationno sensitive capabilitymap_flood_inundation_hydrographno sensitive capabilitymap_fly_tono sensitive capabilitymap_get_stateno sensitive capabilitymap_list_layersno sensitive capabilitymap_remove_layerno sensitive capabilitymap_save_roino sensitive capabilitymap_set_basemapno sensitive capabilitymap_set_roino sensitive capabilitymap_set_time_rangeno sensitive capabilitymap_set_working_geometryno sensitive capabilitymap_showno sensitive capabilitymap_update_layerno sensitive capabilitymerge_session_shardsno sensitive capabilitymerit_add_map_layersno sensitive capabilitymerit_ensure_basinno sensitive capabilitymerit_ensure_basins_regionno sensitive capabilitymerit_ensure_regionno sensitive capabilitymerit_ensure_routing_regionno sensitive capabilitypreview_address_commentno sensitive capabilitypreview_focus_cellno sensitive capabilitypreview_get_pending_changesno sensitive capabilitypreview_get_stateno sensitive capabilitypreview_recent_eventsno sensitive capabilitypreview_revise_sectionno sensitive capabilitypromote_claim_to_registryno sensitive capabilitypropose_and_trainno sensitive capabilityregister_featureno sensitive capabilityregister_research_planno sensitive capabilityresolve_passageno sensitive capabilityrun_autoresearchno sensitive capabilityrun_experimentno sensitive capabilityrun_inundation_physics_validationno sensitive capabilityrun_pythonno sensitive capabilityrun_skepticno sensitive capabilitysave_skillno sensitive capabilitysearch_experimentsno sensitive capabilitysearch_literatureno sensitive capabilitysearch_passages_toolno sensitive capabilityseparate_baseflowno sensitive capabilityset_active_featureno sensitive capabilityshow_html_previewno sensitive capabilityshow_on_mapno sensitive capabilitystart_projectno sensitive capabilitystart_sessionno sensitive capabilitytrain_hydro_modelno sensitive capabilitytrain_inundation_surrogateno sensitive capabilityupdate_claim_statusno sensitive capabilityupdate_researcher_profileno sensitive capabilitywait_for_jobno sensitive capabilitywrite_research_interpretationno sensitive capability
Toxic flows 1
Cross-tool combinations that form a data-exfiltration primitive (untrusted input → sensitive source → external sink).
What this scan could not see
- Tools were statically extracted from the published source (147 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 |
|---|---|---|---|---|
v2.1.0 latest |
B 89/100 | 7 | 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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