Modelforge

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Works with Claude Code, Codex, VS Code, Cursor, Windsurf, Claude Desktop. Read the repository before you give any tool access to your data.

npx agentmarket install connector/whatsonyourmind-modelforge

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What this server can do and what it asks for, from its tool list, install config and code. Checked Oct 25, 2026.

Tools

16 read · 3 write · 0 delete · 6 not yet classified

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1 (API keys, tokens or passwords)

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Python package

Tools (25)

Read from the source code; the running server may differ. Descriptions are the server’s own words; hidden characters are shown as [U+…].

• audit_conservation

  Recompute the QC sheet and require ALL_PASS==1 — the other certify-blind defect. certify proves zero formula errors, but a conservation check that legitimately recomputes to 0 (a balance sheet that doesn't balance, a debt roll-forward that telescopes, NI != EBT + tax) is a VALID formula returning 0 — not an Excel error — so it certifies CERTIFIED today. This recomputes every formula with the `formulas` engine, reads the recomputed ALL CHECKS PASS aggregator plus every per-check on the QC sheet, and requires the aggregator to be 1 with no per-check at 0. Deterministic, zero-LLM. Takes xlsx_pat…

• audit_schedule

  Flag hardcoded numbers wedged inside a formula series — the certify-blind defect. certify proves a workbook has zero formula errors, but it cannot see a cell that SHOULD be a formula and was overwritten with a bare number (e.g. a value typed over year 4 of a 10-year debt schedule). This auditor catches exactly that: a non-innocuous hardcode sitting BETWEEN formula cells in a contiguous period series. Edge-period inputs and input/reference/audit sheets are excluded, so it is high-precision (zero findings on all certified examples). Takes xlsx_path; returns {xlsx, verdict, findings[], finding_c…

• build_model

  Generate a live-formula Excel workbook (.xlsx) plus its SQLite linkage graph (.graph.db) from a typed YAML spec. Use when the user has (or has just produced) a ModelForge YAML spec and wants the actual workbook — formulas in every cell, scenario toggles, and source-tagged inputs. Takes spec_path and optional output_dir; returns {xlsx, graph_db, evidence, spec, ok} or {error}. The evidence-binding gate runs first (optionally against the source documents in ``dataroom``). A BROKEN or CONTESTED binding — or, with ``evidence_strict``, an UNVERIFIED one — returns {verdict: EVIDENCE_BLOCKED, block…

• certify

  Build from a YAML spec (or take an existing workbook) and run the zero-formula-error certification audit. Pass EITHER ``spec_yaml`` (YAML text or a path to a .yaml file — it is validated, built exactly as the CLI `build` command ships it, including the Trust/Moat sheets and the deterministic finishing chain) OR ``workbook_path`` (an already-built .xlsx to audit as-is). The auditor recomputes every formula with the third-party `formulas` engine and flags any Excel error cell (#REF!/#DIV0!/#VALUE!/#NAME?/#NUM!/#N/A) plus numeric cells lacking font colour or number_format. Returns {verdict: CER…

• compute_tax

  Compute corporate income tax (effective rate + total tax) for one of seven jurisdictions from pretax book income. Use when a model or analysis needs a quick jurisdiction-aware tax figure. US, UK, DE, FR, ES, JP are fully wired; IT returns a pointer to the dedicated italian_tax module for full IRES/IRAP inputs. Takes jurisdiction code, pretax_book_income, and optional jurisdiction-specific kwargs; returns {jurisdiction, etr, total_tax} or an error for an unknown code. Conversational loop: helper at STEP 3 — ground a spec's tax-rate assumption in the right jurisdiction while drafting.

• data_providers_status

  List every registered market-data provider with its tier and an availability flag. Use this FIRST before quote/history/fundamentals/search_filings to see which providers are actually usable in the current environment (free providers work out of the box; paid/institutional ones activate only when their API keys are set). Returns {providers, available_count, total_count}. Conversational loop: outside the core loop — check it before using the market-data tools to ground spec assumptions at STEP 3.

• entity_lookup

  Resolve a legal entity by LEI, FIGI, or ticker and return its canonical legal name plus any cross-reference IDs. Use to disambiguate a counterparty or issuer before building a model spec or wiring market data. Takes any one of lei / figi / ticker; returns the resolved Entity record or {error}. Conversational loop: drafting helper at STEP 3 — pin down the exact legal entity a spec's target block refers to.

• export_deck

  Render a certified, hash-stamped board deck (.pptx) from a ModelForge workbook or spec — fail-closed. Pass EITHER ``workbook_path`` (a built .xlsx with its ``<stem>.manifest.json`` sidecar next to it) OR ``spec_path`` (a YAML spec, built exactly as the CLI ``build`` ships it — Trust/Moat sheets, deterministic finishing, manifest — before the deck chain runs). Fail-closed chain: manifest verify → certification audit must be CERTIFIED → supported-template fact extraction (every numeric fact carries its sheet!cell ref) → compose (``ic_memo`` or ``teaser``) + mandatory "Certification & Red Flags…

• export_docx

  Generate a structured Word memo (.docx) from a built ModelForge workbook. Sections: Executive Summary, Transaction Overview, cited Key Assumptions, Risk Analysis, Recommendation. Use when the user wants a written investment/credit memo derived from a model. Requires the [export] extra (python-docx). Takes xlsx_path and optional output_path; returns {xlsx, docx, ok} or {error}. Conversational loop: STEP 8 (deliverable) — only after certify returns CERTIFIED (or the user accepts a WARN).

• export_pptx

  Generate an executive PowerPoint deck (.pptx) summarizing a built ModelForge workbook. Use when the user wants a presentation-ready summary of a model for a committee or stakeholder review. Requires the [export] extra (python-pptx). Takes xlsx_path and optional output_path; returns {xlsx, pptx, ok} or {error}. Conversational loop: STEP 8 (deliverable) — only after certify returns CERTIFIED (or the user accepts a WARN).

• fundamentals

  Fetch reported financial statements (income, balance, or cashflow) for a ticker, newest first. Use when the user needs historical fundamentals to seed or sanity-check a model. Takes symbol, statement (income/balance/cashflow), period (annual/quarter), limit, optional prefer provider; returns {symbol, statement, period, data: [...]} or {error}. Conversational loop: market-data helper at STEP 3 (drafting) — seed historical_revenue/EBITDA blocks of a spec from reported figures.

• get_spec_schema

  Return the full JSON Schema (draft 2020-12) for a model_type's YAML spec. Use when spec_guide's block list is not enough and you need exact field-level types, enums, ranges, and nested structures while drafting or repairing a spec. Same schema the CLI's `modelforge schema` command emits. Returns {model_type, schema} or {error} for an unknown model_type. Conversational loop: STEP 2 (detail level) — alongside spec_guide, before validate_spec.

• history

  Fetch historical OHLCV price bars for a ticker over a date range and interval. Use when the user needs a price series (e.g. daily bars for the last year, or intraday bars). Takes symbol, interval (1m/5m/1h/1d/1wk/1mo), optional start/end ISO dates, limit, and optional prefer provider; returns {symbol, interval, bars: [...]} or {error}. Conversational loop: market-data helper at STEP 3 (drafting) — e.g. for volatility or historical-growth inputs to a spec.

• ingest_dataroom

  Read a folder of PDFs/XLSXs/CSVs and produce a Pydantic-validated ModelForge YAML spec plus an ingestion report. Use when the user has a directory of raw deal documents and wants to turn them into a buildable spec without hand-coding it. Each extracted field is traced to its source. Requires the [ingest] extra and an Anthropic API key. Takes dataroom_path, template (default project_finance), optional output_spec; returns paths to the YAML + ingestion report + extracted_fields count. Conversational loop: alternative to hand-drafting at STEP 3 when raw deal documents exist — still run validate…

• lineage_walk

  Trace a single output cell back through its drivers to the underlying source document and page. Use when the user asks 'where does this number come from?' or 'show the audit trail for cell X' on a built model. Takes graph_db and a cell reference (e.g. "Returns!E45"); returns an ordered list of upstream hops cell -> driver -> source -> doc page. Conversational loop: STEP 7 (final) — the provenance walk that closes the loop: any number in the certified workbook traces back to a source doc page.

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Stars

3

Forks

1

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0

Weekly downloads

49

Last commit (this folder)

Oct 12, 2026 (18 days ago)

Last release

Jun 22, 2026 (4 months ago)

Last package publish

Jun 22, 2026 (4 months ago)

From GitHub (fetched Oct 24, 2026) and the package registry.

Details

Registry name

io.github.Whatsonyourmind/modelforge

Version

0.9.7

Auth

API key

Packages

pypi modelforge-finance

License

Proprietary

Repository

github.com/Whatsonyourmind/modelforge

First seen

Oct 24, 2026

Last checked

Oct 24, 2026

Source

Official MCP Registrygithub-graphql