PDFMonkey

@PDFMonkey list all document templates in my account and show me which ones were used in the last 30 days

Based on your PDFMonkey account, you have 7 document templates. Three have been actively used in the past 30 days: 'Monthly Invoice' (template ID: tmpl_abc123, 47 documents generated), 'Client Proposal' (tmpl_def456, 12 documents), and 'Service Agreement' (tmpl_ghi789, 8 documents). The remaining four templates—'Quarterly Report', 'Welcome Packet', 'NDA Standard', and 'Receipt Template'—have not been used recently. This example illustrates a typical response structure; actual template names and usage counts will reflect your account's activity.

This example demonstrates read-only template discovery and usage analysis. Requires a valid API key with read permissions. PDFMonkey's API does not natively track 'last used' timestamps on templates, so the AI would infer usage by querying recent documents and correlating their template IDs—expect slower responses if you have hundreds of documents.

@PDFMonkey create a new invoice PDF using template tmpl_inv_2024 with client name 'Acme Corp', amount $4,250, and due date March 15th

I've queued a new document (ID: doc_xyz789) using your 'Monthly Invoice' template. The PDF is generating now with the following payload: client_name='Acme Corp', invoice_amount='$4,250.00', due_date='2024-03-15'. Status is 'pending'—generation typically completes in 5–15 seconds. Once ready, the document status will update to 'success' and a download URL will be available for 1 hour. This example shows the immediate response; the actual PDF file is not yet available until generation finishes.

This write operation creates a document asynchronously by default. The MCP's 'Create Document' tool returns immediately with status='pending'; use 'Create Document Sync' if you need the AI to wait for the PDF to finish generating before responding. Be aware that high-volume generation may hit rate limits (check your plan's quota). The download URL expires after 1 hour—refetch if needed.

@PDFMonkey generate a contract PDF from template tmpl_contract_std for client 'Beta LLC', then summarize the key terms visible in the generated document

I've generated document doc_abc456 using your standard contract template with client_name='Beta LLC'. The PDF is ready for download. Based on the template's payload structure, the contract includes: a 12-month service term starting from the signature date, a monthly fee of $2,500 with net-30 payment terms, automatic renewal unless either party provides 60 days' notice, and a standard liability cap at one year of fees paid. Note: this summary reflects the template's data fields and typical contract language—I cannot parse the actual rendered PDF content, only the structured payload you provided to the template.

This synthesis example shows the AI reasoning over the document's input payload, not OCR or text extraction from the final PDF. PDFMonkey generates PDFs from templates and structured data; the MCP does not include tools to read or parse the rendered PDF's text. If you need to extract or verify content from the generated file, you'd download it and use a separate PDF-parsing tool. Useful for confirming what data went into the document before distribution.

When PDFMonkey wins for repeatable contract workflows

A 6-person sales team closes 40-60 deals a month, each needing a custom MSA, SOW, and invoice. They store templates in PDFMonkey and trigger generation from Slack or their CRM via Switchy. The Create Document Sync tool waits for the PDF to finish rendering before posting the download link back to the channel—no manual polling, no broken links. This works because the team has 3-5 stable templates and the payload (customer name, pricing, terms) changes predictably. If your contracts need complex conditional logic or multi-party e-signature orchestration, you'll hit the template editor's limits and need a heavier doc-gen stack. For straightforward mail-merge-style PDFs at small-team scale, PDFMonkey keeps the workflow in one place and the API key is the only auth you manage.

When PDFMonkey fits recurring client deliverables

A 3-person consulting shop sends 20 clients a monthly performance report—same layout, different data each time. They schedule a Switchy automation that pulls metrics from their analytics tool, calls Create Document with the template ID and JSON payload, then emails the finished PDF. The Download Document File tool fetches a presigned URL that expires in an hour, so the automation grabs it immediately and attaches it to the outbound email. This scenario works because the report structure is fixed and the data is already structured (no OCR, no parsing). If your reports need live charts or pivot tables that update in the PDF, PDFMonkey's static templating won't cut it—you'd need a BI tool with native PDF export. For teams that own the template design and just need to inject data at send-time, PDFMonkey keeps the stack simple and the per-document cost predictable.

When PDFMonkey handles HR document bundling

A 10-person startup onboards 2-3 people a month and needs to generate offer letters, benefits summaries, and equipment checklists from a shared template library. HR triggers the workflow from Notion or their HRIS, and Switchy calls Create Template once to set up a new packet type, then Create Document for each hire with personalized fields (name, start date, salary band). The Get Document tool confirms generation succeeded before the packet is emailed. This works when your templates are mostly text with light formatting and you control the source data. If you need to merge scanned signatures, redact PII dynamically, or handle multi-language variants with complex layout shifts, the template editor becomes a bottleneck. For small teams with straightforward onboarding docs and a stable hire cadence, PDFMonkey keeps the process in-house without a Docusign-sized contract.