MCP server

Ifr Coworker

com.spocont/ifrCoworker

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

IFRS engine: 31 standards, 20 tools. Journal entries, XBRL tags, ECL, CGU impairment, deferred tax.

At a glance

Type

MCP server

Publisher

spocont.com (verified by the MCP Registry)

Status

Working at last check

Tools

20

Token cost

About 20,585 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http ifrcoworker https://mcp.ifrcoworker.app

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.ifrcoworker]
url = "https://mcp.ifrcoworker.app"

Gemini CLI

{"mcpServers":{"ifrcoworker":{"httpUrl":"https://mcp.ifrcoworker.app"}}}

Cursor

{"mcpServers":{"ifrcoworker":{"url":"https://mcp.ifrcoworker.app"}}}

VS Code

{"servers":{"ifrcoworker":{"type":"http","url":"https://mcp.ifrcoworker.app"}}}

Antigravity

agy mcp add ifrcoworker https://mcp.ifrcoworker.app

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"ifrcoworker","server_url":"https://mcp.ifrcoworker.app","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"ifrcoworker","server_url":"https://mcp.ifrcoworker.app"}

Tools

• ifr_amortisation_schedule ~515 tokens
  Compute a multi-period amortisation / depreciation / EIR amortisation schedule by rolling reportingDate forward one period at a time. Supported standards: ias16 (PPE depreciation), ias38 (intangible amortisation), ias40 (investment property — cost model), ias23 (borrowing cost capitalisation), ifrs9
• ifr_apply_ias10 ~331 tokens
  Apply IAS 10 (Events After Reporting Period) overlay to a prior calculation output. Classifies events as adjusting/non-adjusting, assesses going concern, generates adjusted journal entries. Most standards auto-trigger IAS 10 when subsequentEventDate + subsequentEventKind are provided — use this tool
• ifr_batch_validate ~2750 tokens
  FREE pre-flight validator for ifr_period_end_batch. Validates every item in one call and returns all missing required fields across the batch. A field an item's standard does not declare is refused here exactly as ifr_period_end_batch refuses it (FIELD_UNRECOGNISED, naming the field and the item — G
• ifr_calculate ~1022 tokens
  If you know the economic object type but not the standard, pass `elementType` instead of `standard`. The discriminator field (`assetClass` for 'asset', `investmentType` for 'equity-method-investment') must be included in the `input` object. Run a full IFRS/IAS calculation. Returns journal entries, d
• ifr_calculation_sheets ~344 tokens
  Retrieve the calculation-sheets workbook for a prior ifr_calculate or ifr_period_end_batch call. Returns a downloadUrl for the XLSX workbook (GET /api/ifrcoworker/calculation-sheets/{correlationId} with Bearer token) and a structured JSON summary of each sheet's data (journalEntries count, trialBala
• ifr_check_quota ~158 tokens
  Check your remaining ifrCoworker credits without consuming any. Returns creditsRemaining, creditsUsedToday, fullAccess flag, and a cost estimate for batch calls. FREE — does not decrement quota. Call before a large batch to verify you have enough credits. batchCostEstimate.perItem = credits per succ
• ifr_disclosure_checklist ~602 tokens
  Generate a disclosure-needs checklist for the period-end. FREE — no credit charged. Input: entityProfile fact flags (same shape as ifr_period_checklist) → returns the core MANDATORY disclosure requirements per applicable standard, each with its IAS/IFRS paragraph reference and category (policy / rec
• ifr_ecl_provision_matrix ~604 tokens
  IFRS 9 Simplified Approach — ECL provision matrix for trade receivables, IFRS 15 contract assets, and IFRS 16 lease receivables. Ages each receivable into buckets (current / 1-30 / 31-60 / 61-90 / 91-180 / 180+ days past due). Applies entity-supplied historical loss rates per bucket. Returns per-inv
• ifr_explain_result ~343 tokens
  Return a human-readable explanation of a previously computed calculation. Pass the correlationId from any ifr_calculate or ifr_period_end_batch response (this tool reads a 10-minute result cache; the workbook of the same id stays downloadable for 24 h), OR pass the full prior response object as `cal
• ifr_flag_result ~745 tokens
  Flag a calculation result you believe is incorrect for expert review. Call immediately when the server output appears to contradict IFRS — wrong amount, missing journal entry, incorrect OCI/P&L routing, wrong paragraph, or missing disclosure. FREE — no credit charged. MINIMUM REQUIRED: standard + se
• ifr_generate_workpaper ~535 tokens
  Generate a structured audit working paper JSON from one or more prior ifr_calculate results. Aggregates across standards: accounting policies (IAS 1.117), key estimation uncertainties (IAS 1.125), calculation workings, journal entries, and a disclosure completeness checklist. Reference prior results
• ifr_ingest_document ~523 tokens
  Extract structured data from a PDF (contract, invoice, lease, bond indenture) using Google Document AI. Requires docuScanAccess on the token — returns 403 otherwise; do NOT retry or offer document scanning again this session if access is denied. PROTOCOL: (1) offer PDF processing to the user, (2) re
• ifr_input_schema ~479 tokens
  Returns the JSON Schema for the input to ifr_calculate for a given standard. Use this to discover required fields, enum values, and defaults without calling ifr_schema. Returns a standard JSON Schema object suitable for programmatic validation. Derived from the controller FIELD_DEFINITIONS — always
• ifr_period_checklist ~624 tokens
  Planning tool for a full period-end close. Pass an entityProfile of fact flags (hasInventory, hasPPE, hasLeases, hasFinancialInstruments, isGroup, isListed, incomeTaxApplicable, etc.) and get back the exact ordered list of IFRS/IAS standards to run for this entity — each with its requiredInputFields
• ifr_period_end_batch ~7262 tokens
  THE period-end execution tool — process multiple IFRS calculations for a reporting period in one call (year-end, quarter-end, or month-end). One tool, three modes: (1) PLAIN BATCH (default): items + accountingPolicy → per-item results, every item's journal entries in one list, trial balance, and all
• ifr_propose_mapping ~308 tokens
  Map OCR data from ifr_ingest_document into an IFRS standard's input schema and validate it. Returns proposedInput, unmappedFields, missingRequiredFields, validation errors/warnings, needsUserInput[], and a confidence score. CRITICAL: proposedInput is a suggestion — every entry in needsUserInput[] mu
• ifr_replay ~818 tokens
  Deterministic audit replay — recompute a prior calculation from its input and verify it reproduces the stored output. FREE — no credit charged. The engine is stateless and pure: identical input + identical engine/schema version always produces identical output. Every ifr_calculate response carries a
• ifr_route_event ~637 tokens
  ROUTER — the entry point for every business event. Describe what happened in plain language ("bought a machine", "signed an office lease", "customer went bankrupt") and get back the exact call to make. FREE — no usage charge. Each match carries an `endpoint` block with the EXACT next call: the ifr_c
• ifr_schema ~1305 tokens
  If you know the economic object type but not the standard, pass `elementType` (e.g. 'lease', 'asset', 'financial-instrument') instead of `standard`. For multi-standard types (asset, equity-method-investment), also pass `assetClass` or `investmentType` to get the specific standard's schema. The recur
• ifr_validate ~680 tokens
  If you know the economic object type but not the standard, pass `elementType` instead of `standard`. The discriminator field (`assetClass` for 'asset', `investmentType` for 'equity-method-investment') must be included in the `input` object. OPTIONAL pre-flight validator — only use when you need to s

Browse

• Website monitoring
• PDF tools
• OCR (text from images)
• Spreadsheets

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