Invofox

@Invofox list all invoices processed in the last 30 days where the total amount exceeds $5,000, sorted by date descending.

Found 47 documents matching your criteria. The most recent is invoice #INV-2847 from Acme Corp dated 2024-01-15 for $12,450.00 (confidence: 98%). Next is invoice #INV-2839 from Global Supplies dated 2024-01-14 for $8,200.00 (confidence: 96%). The list continues with invoices from TechVendor Inc., Office Solutions Ltd., and others. Each record includes extracted vendor name, date, total, line items, and tax amounts with per-field confidence scores. You can retrieve full document details or OCR text for any invoice using its document ID.

This example shows Invofox's core strength: structured search across extracted invoice fields. The MCP returns metadata and extracted data, not the original PDFs. Confidence scores help you identify documents that may need manual review. API key must have read access to the company collection being queried.

@Invofox process these three supplier invoices from our email attachments: https://storage.example.com/invoice-jan-001.pdf, https://storage.example.com/invoice-jan-002.pdf, https://storage.example.com/invoice-jan-003.pdf

Queued 3 documents for extraction. Import ID: imp_9x4kL2mP. File IDs: file_a1b2c3, file_d4e5f6, file_g7h8i9. Processing typically completes in 15-45 seconds per document depending on page count and image quality. You can check status by asking me to get the import details, or I'll notify you when extraction finishes. Once complete, you'll have access to vendor names, dates, line items, totals, tax amounts, and payment terms with confidence scores for each field.

This demonstrates asynchronous document ingestion from public URLs. Invofox does not fetch documents from private storage or email directly—you must provide HTTPS URLs. The import ID lets you poll for completion. Processing is not instantaneous; plan workflows accordingly. Side-effect: documents are permanently stored in your Invofox account and count toward your plan limits.

@Invofox get the full OCR text and extracted fields for document doc_5m8nQ1rT, then summarize any discrepancies between the line-item subtotal and the invoice total.

Retrieved document doc_5m8nQ1rT (invoice #2024-0156 from Midwest Distributors, 3 pages). Extracted total: $4,287.50 (confidence: 99%). Line items: $1,200 for Widget Assembly, $950 for Fastener Kit, $2,100 for Hydraulic Pump, subtotal $4,250. Tax: $37.50. The extracted line-item subtotal of $4,250 plus $37.50 tax equals $4,287.50, matching the invoice total perfectly. OCR text shows no handwritten adjustments or strikethroughs. No discrepancies detected—this invoice reconciles cleanly.

This example pairs Invofox's extraction API with AI reasoning to validate invoice math. The MCP returns structured fields and raw OCR text; the AI performs the analysis. Useful for auditing workflows where you need both machine-readable data and human-readable context. Requires the document to already be processed—you cannot analyze documents mid-extraction.

When Invofox replaces manual invoice data entry

A 6-person finance team at a B2B SaaS company receives 200-300 vendor invoices per month as email attachments. They spend 4 hours weekly copying line items into NetSuite. Invofox is the right call here: the Process Documents by URL tool accepts HTTPS links to invoice PDFs, extracts fields like vendor name, tax ID, line items, and totals, then returns structured JSON the team pipes into their ERP via Zapier. The Get Document tool surfaces confidence scores so the AP lead knows which invoices need human review. The threshold: if your invoices are handwritten or use non-Latin scripts, OCR accuracy drops below 85 percent and you'll still need manual QA on most records. For typed invoices in English, French, German, or Spanish, Invofox cuts data-entry time by 70 percent and pays for itself in week two.

Why Invofox struggles with multi-party KYC workflows

A 12-person fintech startup onboards 40 new business customers monthly, each submitting incorporation docs, tax certificates, and bank statements. The ops team wants to auto-extract entity names and registration numbers into their CRM. Invofox can handle the extraction—Create Company organizes documents by customer, List Documents filters by field values—but the MCP has no built-in approval or routing logic. If your workflow requires a compliance officer to review flagged documents before marking a customer "verified," you'll need a separate orchestration layer (Airtable, Retool, or custom code) to manage state transitions. The tool works for the OCR step but doesn't replace your onboarding workflow engine. Use Invofox if you already have that orchestration and just need reliable field extraction; skip it if you're looking for an end-to-end KYC platform.

When Invofox wins for distributed team reimbursements

A 20-person remote consulting firm reimburses travel expenses monthly. Consultants upload 150-200 receipts to a shared Dropbox folder; the finance lead manually keys merchant names, dates, and amounts into a Google Sheet for approval. Invofox fits this use case cleanly: the Process Documents by URL tool accepts receipt image URLs, the Get Document Text tool returns OCR'd merchant and total fields, and the List Documents tool lets the finance lead filter by date range or amount threshold to spot anomalies. Because receipts are single-page and follow predictable layouts, extraction confidence averages 92 percent. The buying call: if your team already stores receipts in cloud storage with public or signed URLs, Invofox eliminates 90 percent of manual keying and gives you structured data for downstream approval or accounting integrations.