Pm4py MCP Server

pm4py-mcp PyPI v0.4.1

Published by azizketata — 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.

Open-source Model Context Protocol server for process mining, wrapping PM4Py behind a small handle-based tool surface.

Trust grade
A
96/100
Last scanned get badge →
Trust
A · 96/100
Adoption risk for you: the threat score, then adjusted down for blast radius, publisher verification and how much the scan could see. Deterministic; every point is auditable.
Capability
Moderate
Blast radius if it went rogue — what the server’s tools could reach. Independent of trust.
Coverage
Source
How much the scan could actually inspect. Shallow coverage is stated, never hidden.
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A Why this grade threat 100 − adoption risk = 96/100

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 − 4 = 96. 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:

PointsAdoption-risk factor
−3 capability blast radius (moderate) — 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 0

✓ No findings. The scan raised nothing on this surface — see Coverage for how deep it could look.

Tools 67

Each tool and what it can reach — statically extracted from the published source.

  • list_workspacereads sensitive data
  • abstract_caseno sensitive capability
  • abstract_declareno sensitive capability
  • abstract_dfgno sensitive capability
  • abstract_log_attributesno sensitive capability
  • abstract_log_featuresno sensitive capability
  • abstract_log_skeletonno sensitive capability
  • abstract_ocdfgno sensitive capability
  • abstract_ocelno sensitive capability
  • abstract_petri_netno sensitive capability
Show 57 more tools ↓
  • abstract_snano sensitive capability
  • abstract_streamno sensitive capability
  • abstract_temporal_profileno sensitive capability
  • abstract_variantsno sensitive capability
  • conformance_alignmentsno sensitive capability
  • conformance_token_replayno sensitive capability
  • convert_modelno sensitive capability
  • describe_logno sensitive capability
  • describe_ocelno sensitive capability
  • discover_activity_based_resource_similarityno sensitive capability
  • discover_bpmnno sensitive capability
  • discover_declareno sensitive capability
  • discover_dfgno sensitive capability
  • discover_handover_networkno sensitive capability
  • discover_log_skeletonno sensitive capability
  • discover_oc_petri_netno sensitive capability
  • discover_ocdfgno sensitive capability
  • discover_organizational_rolesno sensitive capability
  • discover_petri_netno sensitive capability
  • discover_powlno sensitive capability
  • discover_process_treeno sensitive capability
  • discover_subcontracting_networkno sensitive capability
  • discover_temporal_profileno sensitive capability
  • discover_working_together_networkno sensitive capability
  • export_logno sensitive capability
  • export_ocelno sensitive capability
  • filter_attribute_valuesno sensitive capability
  • filter_case_performanceno sensitive capability
  • filter_case_sizeno sensitive capability
  • filter_ocel_attributeno sensitive capability
  • filter_ocel_ccno sensitive capability
  • filter_ocel_object_typesno sensitive capability
  • filter_ocel_time_rangeno sensitive capability
  • filter_time_rangeno sensitive capability
  • filter_variantsno sensitive capability
  • flatten_ocelno sensitive capability
  • get_case_durationsno sensitive capability
  • get_cycle_timeno sensitive capability
  • get_domain_contextno sensitive capability
  • get_start_end_activitiesno sensitive capability
  • get_variantsno sensitive capability
  • load_event_logno sensitive capability
  • load_ocelno sensitive capability
  • pingno sensitive capability
  • render_reportno sensitive capability
  • sample_case_idsno sensitive capability
  • set_domain_contextno sensitive capability
  • simulate_logno sensitive capability
  • visualize_bpmnno sensitive capability
  • visualize_dfgno sensitive capability
  • visualize_dotted_chartno sensitive capability
  • visualize_oc_petri_netno sensitive capability
  • visualize_ocdfgno sensitive capability
  • visualize_performance_spectrumno sensitive capability
  • visualize_petri_netno sensitive capability
  • visualize_powlno sensitive capability
  • visualize_process_treeno sensitive capability

What this scan could not see

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.

VersionScoreFindingsEngineScanned
v0.4.1 latest A 96/100 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.

MCP Trust Score: A · 96/100
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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.

npx mcptrustchecker scan pm4py-mcp --online --registry pypi

Use the free API → How scoring works

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