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ModelRisk

PYPI · MODELRISK-MCP · SCANNED SEP 21

Read, build, fit, and run Monte Carlo risk models in Excel through Vose Software's ModelRisk.

Available components

0 this week 62 Trust /100
Trust breakdown (7 categories)

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →

Supply Chain Security50
  • Malware scan not yet available for this package.Unverified
  • No known CVEs affecting this package version or its production dependencies.Pass
  • Runs hatchling.build at install time, a recognised native-build step with no shell scripting around it. View diagnostics → Pass
  • 1 of 35 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency6
Schema Quality & AI Usability83
  • 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).Pass
  • AI-judged instruction clarity (excellent).Pass
  • Context-footprint check failed: tool/resource definitions use about 9507 tokens (~146/item across 65 items; 59 tools + 6 resources), over budget; trim descriptions and params. See how to fix → Fail
  • Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management100
  • No destabilizing schema changes in the last 30 days.Pass
Tool Coverage88
  • 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
  • 58% of tool parameters carry a description.Partial
  • Structured output schemas are declared (100% of tools); any adoption earns full credit.Pass
Tool Safety100
  • No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
  • We read all 59 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
  • An AI judge read all 61 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
  • Implements a current MCP spec version (2026-07-28).Pass
Install

How do I install the ModelRisk MCP server?

ModelRisk runs locally as a PyPI package, launched with uvx modelrisk-mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

pypi · modelrisk-mcp

# add to Claude Code
claude mcp add vosesoftware-modelrisk-mcp -- uvx modelrisk-mcp
// .cursor/mcp.json
{
  "mcpServers": {
    "vosesoftware-modelrisk-mcp": {
      "command": "uvx",
      "args": [
        "modelrisk-mcp"
      ]
    }
  }
}
// .vscode/mcp.json
{
  "servers": {
    "vosesoftware-modelrisk-mcp": {
      "command": "uvx",
      "args": [
        "modelrisk-mcp"
      ]
    }
  }
}
# add to Codex CLI
codex mcp add vosesoftware-modelrisk-mcp -- uvx modelrisk-mcp
// opencode.json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "vosesoftware-modelrisk-mcp": {
      "type": "local",
      "command": [
        "uvx",
        "modelrisk-mcp"
      ],
      "enabled": true
    }
  }
}
# add to OpenClaw
openclaw mcp add vosesoftware-modelrisk-mcp --command uvx --arg modelrisk-mcp
# ~/.hermes/config.yaml
mcp_servers:
  vosesoftware-modelrisk-mcp:
    command: "uvx"
    args: ["modelrisk-mcp"]
// ~/.netclaw/config/netclaw.json
{
  "McpServers": {
    "vosesoftware-modelrisk-mcp": {
      "Transport": "stdio",
      "Command": "uvx",
      "Arguments": [
        "modelrisk-mcp"
      ]
    }
  }
}
# add to Vellum
assistant mcp add vosesoftware-modelrisk-mcp -t stdio -c uvx -a modelrisk-mcp
// mcp.json
{
  "mcpServers": {
    "vosesoftware-modelrisk-mcp": {
      "command": "uvx",
      "args": [
        "modelrisk-mcp"
      ]
    }
  }
}
Changelog

Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.

  • 21 Sept 26 0
    • Stability: 0.97 → pass security
  • 20 Sept 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 93 to 97. That category is still filling its 30-day observation window: 28 days of observed history at the previous scan, 29 at this one. The score rises as the window fills, whether or not the server changes.

  • 18 Sept 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 87 to 90. That category is still filling its 30-day observation window: 26 days of observed history at the previous scan, 27 at this one. The score rises as the window fills, whether or not the server changes.

  • 16 Sept 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 80 to 83. That category is still filling its 30-day observation window: 24 days of observed history at the previous scan, 25 at this one. The score rises as the window fills, whether or not the server changes.

  • 15 Sept 26 −3
    • Stability: pass → 0.80 functional
  • 14 Sept 26 −15
    • Malware scan: pass → unverified security
    • Stability: 0.97 → pass security
  • 13 Sept 26 +16
    • Malware scan: unverified → pass security
  • 12 Sept 26 −15
    • Malware scan: pass → unverified security
Diagnostics

Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.

Captured 21 Sept 2026 · Analysed pypi/modelrisk-mcp@0.4.0

Provenance No attestation

The registry publishes no build provenance for this version, so there is nothing to verify.

Result No attestation
Ecosystem pypi

Background: How many MCP packages publish verified provenance →

Install scripts 1 script
Hook Tier Command
build_backend allowlisted hatchling.build

Background: Why install scripts are a supply-chain risk →

Dependencies 35 packages
Packages resolved 35
No linked repository 1
Tree resolution Complete

Background: SBOMs and build attestations, explained →

MCP tools · 59 exposed · ~9,139 tokens

The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →

Tool Tokens
read_vmrs ~86

ModelRisk: Read simulation results directly from a `.vmrs` file. Convenience wrapper for `set_active_vmrs` + `get_simulation_results` that doesn't need an open workbook. Pass `output_names` to filter; leave empty to attempt enumeration of all known outputs.

NameTypeReqDescription
output_names
pathstringyesAbsolute path to a .vmrs file.

Structured output declared, but exposes no named fields.

No examples provided.

replace_constant_with_distribution ~115

ModelRisk: Replace a hard-coded number in a cell with a Vose distribution wrapped by VoseInput. Use after find_hard_coded_inputs identifies candidates. This is the only tool that overwrites a non-Vose cell — it does so by design.

NameTypeReqDescription
cellstringyes
dry_runboolean
function_namestringyes
input_namestringyes
parametersarrayyes
sheetstringyes
workbookstringyes
NameTypeReqDescription
cellyes
formulastringyes
previous_formula
writtenbooleanyes

No examples provided.

restore_cell ~110

ModelRisk: Restore a cell to its pre-write state from the audit log. Reads %LOCALAPPDATA%\VoseSoftware\modelrisk-mcp\writes.log and rewrites the oldest captured before-formula for the cell. Pass `since` (ISO timestamp) to restrict the window.

NameTypeReqDescription
cellstringyes
sheetstringyes
sinceOptional ISO-8601 timestamp. Restore the oldest write captured at or after this time.
workbookstringyes
NameTypeReqDescription
cellyes
formulastringyes
previous_formula
writtenbooleanyes

No examples provided.

restore_deterministic_state ~131

ModelRisk: Recover a workbook that's been left in a 'frozen sample' state — VoseOutput cells stuck on per-iteration sample values instead of their deterministic baseline. Triggers a full Excel recalculation (Application.CalculateFull) which re-evaluates every formula and restores the deterministic values. Use this after `run_simulation` raises a post-condition error, or whenever `list_modelrisk_outputs` shows nonsense `current_value`s that look like a single sample draw rather than the model's deterministic answer.

NameTypeReqDescription
workbook_nameWorkbook to recalculate. Omit for the active workbook.

Structured output declared, but exposes no named fields.

No examples provided.

reverse_stress_test ~268

ModelRisk: Reverse stress test — start from a BAD output outcome and work back to the joint input state that produces it. Partitions the simulation's iterations into breach / no-breach (output above/below a threshold, given directly or as a percentile), then for each input reports how far its mean shifts inside the breach set (in its own standard deviations) and how concentrated breaches are in its tail — a breach-driver tornado — plus the mean input vector as a concrete named stress scenario. This is the Solvency II / PRA 'reverse stress test' and is only possible with the engine's recorded per-iteration joint sample matrix (requires a completed simulation).

NameTypeReqDescription
directionstringBreach side: 'above' (default) or 'below' the threshold.
max_nintegerMax samples per variable to pull. Default 100000.
output_namestringyesVoseOutput name to stress.
thresholdBreach threshold on the output. Omit to use threshold_percentile.
threshold_percentileBreach threshold as an output percentile (0-1), e.g. 0.95. Used when `threshold` is omitted.
workbook_nameWorkbook name. Omit for the active workbook.
NameTypeReqDescription
breach_countintegeryes
breach_probabilitynumberyes
directionstringyes'above' or 'below' — the breach side of the threshold.
driversarrayyesInputs ranked by how far they shift in the breach set.
iterationsintegeryes
notestringyes
output_namestringyes
scenarioThe mean input vector over the breach iterations.
thresholdnumberyes

No examples provided.

run_scenarios ~218

ModelRisk: Sweep a single input cell across multiple deterministic values, running a full simulation at each. Returns per-output P5 / P50 / P95 / mean for every scenario value. Useful for what-if analysis: 'what if widget cost is $50 vs $75 vs $100'. The cell's original formula is captured before the sweep and restored afterwards (even on error), so the workbook ends in its pre-call state. Each scenario takes roughly the same time as one `run_simulation` call, so keep the values list short — 3-7 scenarios is a normal range.

NameTypeReqDescription
cellstringyesA1-style cell reference for the input to sweep.
samplesintegerIterations per scenario.
seedintegerFixed seed (same seed across scenarios).
sheetstringyesSheet name holding the input cell.
valuesarrayyesDeterministic values to test (1-20 scenarios).
workbook_nameWorkbook name. Omit for the active workbook.
NameTypeReqDescription
cellstringyes
original_formulastring
samples_per_scenariointeger
scenariosarray
sheetstringyes
workbook_namestringyes

No examples provided.

run_simulation ~310

ModelRisk: Run a Monte Carlo simulation on the active (or named) workbook and save the results to a `.vmrs` file. Defaults to 1000 iterations with a fixed seed for reproducibility, and saves the .vmrs next to the workbook as `<book>.vmrs`. The simulation is run via the same XLL commands ModelRisk's own ribbon uses (VoseStartSimulCustom12 + VoseGetDataSZ12 with the SaveResultsToFile session), so behaviour matches what you'd see clicking 'Simulate' manually. Blocks until the simulation completes. After this returns, call get_simulation_results — the produced .vmrs is automatically pinned as the active results source.

NameTypeReqDescription
iterationsAlias for `samples`. ModelRisk's UI calls this 'samples'; many users call it 'iterations'. Both work.
samplesIteration count. Default: 1000. Either `samples` or `iterations` is accepted (they mean the same thing). If both are passed, `samples` wins.
save_toAbsolute path to write the .vmrs. Default: next to the workbook as `<book_stem>.vmrs`. For OneDrive-hosted workbooks (where path resolution can fail) the default falls back to the user's Desktop fold…
seedintegerRandom seed for reproducibility (fixed seed).
workbook_nameWorkbook file name (e.g. 'model.xlsx'). Omit for the active workbook.
NameTypeReqDescription
next_stepstringyesSuggested follow-up call for the MCP client — typically `get_simulation_results` to pull the per-output statistics.
samplesintegeryes
seedintegeryes
vmrs_pathstringyes
workbook_namestringyes

No examples provided.

save_workbook_as ~114

ModelRisk: Save the workbook to a specific path on disk. Distinct from the user's Ctrl+S — the MCP server never calls Workbook.Save() implicitly. Use only when the caller explicitly named a target file. Refuses to overwrite an existing file unless overwrite=True. Returns the resolved absolute path that was written.

NameTypeReqDescription
overwriteboolean
pathstringyesAbsolute path. Must end in .xlsx, .xlsm, .xlsb, or .xls.
workbookstringyes

Structured output declared, but exposes no named fields.

No examples provided.

set_active_vmrs ~100

ModelRisk: Pin a specific `.vmrs` file as the source of simulation results. Pass the absolute path of the file; subsequent calls to get_simulation_results / get_correlation_matrix / get_sensitivity_ranking will read from it instead of trying to locate a sibling file next to the workbook. Pass an empty string to clear the override.

NameTypeReqDescription
pathstringyesAbsolute path to a .vmrs file, or '' to clear.

Structured output declared, but exposes no named fields.

No examples provided.

set_named_range ~90

ModelRisk: Create or overwrite a workbook-level named range. Useful for giving cells clear identities the LLM can reference by name later. The reference must be A1-style (e.g. 'Sheet1!$A$1:$A$10').

NameTypeReqDescription
dry_runboolean
namestringyes
range_refstringyes
workbookstringyes

Structured output declared, but exposes no named fields.

No examples provided.

wrap_with_input ~72

ModelRisk: Wrap an existing distribution cell with VoseInput("name")+ so it appears in the input list and the Results Viewer.

NameTypeReqDescription
cellstringyes
dry_runboolean
namestringyes
sheetstringyes
workbookstringyes
NameTypeReqDescription
cellyes
formulastringyes
previous_formula
writtenbooleanyes

No examples provided.

wrap_with_output ~71

ModelRisk: Wrap an existing output cell with VoseOutput("name")+ so it appears in the output list and Results Viewer.

NameTypeReqDescription
cellstringyes
dry_runboolean
namestringyes
sheetstringyes
workbookstringyes
NameTypeReqDescription
cellyes
formulastringyes
previous_formula
writtenbooleanyes

No examples provided.

write_formula ~238

ModelRisk: Write an arbitrary formula or value into a single cell. Use this for wiring cells (e.g. =A1*B1, =SUM(...), =IF(...), or links to other sheets) that aren't covered by the Vose-specific tools. Safety: refuses to overwrite a cell containing an existing formula unless allow_overwrite=True — that protects user-written formulas AND prior Vose distributions. Empty cells write freely. Defaults to dry_run=True; pass dry_run=False to commit. Every commit appends to the audit log so `restore_cell` can roll back.

NameTypeReqDescription
allow_overwritebooleanPermit overwriting a non-empty cell. Required if the cell already has any content. Without this flag the tool refuses and returns the existing formula so Claude can decide what to do.
cellstringyesA1 cell reference like 'C1'.
dry_runboolean
formulastringyesFormula or value to write. Excel-style; leading '=' is optional (we'll add it if missing for non-numeric content).
sheetstringyes
workbookstringyes
NameTypeReqDescription
cellyes
formulastringyes
previous_formula
writtenbooleanyes

No examples provided.

Common questions

What is the ModelRisk MCP server?

ModelRisk is an MCP server listed in the public MCP registry as io.github.vosesoftware/modelrisk-mcp. Read, build, fit, and run Monte Carlo risk models in Excel through Vose Software's ModelRisk. This page covers its PyPI package (modelrisk-mcp).

Is the ModelRisk MCP server safe to use?

ModelRisk scores 62 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 21 September 2026. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

What tools does the ModelRisk MCP server expose?

ModelRisk exposes 59 tools: list_open_workbooks, get_active_workbook, open_workbook, close_workbook, get_workbook_summary, and 54 more. Their descriptions and schemas cost roughly 9,139 tokens of context every time the server is loaded.

Is the ModelRisk MCP server still maintained?

ModelRisk is still listed as active in the MCP registry. We last reached this channel on 21 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.