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MCP server for Nutrient DWS Processor API
Server has 7 tools with mostly complete schemas and descriptions. Naming is clear and verb-based (document_processor, document_signer, ai_redactor, parse_document, extract_fields, check_credits, directory_tree). Descriptions are detailed (100-400 chars) and explain WHAT, WHEN, and output formats well. However, parameter descriptions are sparse or missing for complex nested objects (e.g., 'instructions' object in document_processor has no field-level documentation; 'signatureOptions' in document_signer is undescribed). Input schemas lack type details for object properties, 'instructions' and 'signatureOptions' are typed as 'object' with no nested schema. Error handling guidance is absent; no recovery hints for common failures. Output schemas are not documented. Destructive operations (document_processor, document_signer, ai_redactor) lack confirmation/dry-run patterns.
Detect and permanently redact sensitive content using the Nutrient AI Redaction API. Reads input files from the local file system or sandbox (if enabled) and writes redacted output back locally. Automatically detects and permanently removes sensitive information from documents using AI analysis. Detected content types include: • Personally identifiable information (names, addresses, phone numbers) • Financial data (credit card numbers, bank accounts, SSNs) • Email addresses and URLs • Protected health information (PHI) • Any custom criteria you specify By default (when neither stage nor apply is set), redactions are detected and immediately applied. Set stage to true to detect and stage redactions without applying them. Set apply to true to apply previously staged redactions.
Check your Nutrient DWS API credit balance and usage for the current billing period. This is a read-only account lookup. It does not upload any document content. Returns: subscription type, total credits, used credits, and remaining credits.
List the contents of a directory in the sandbox as a tree structure. Useful for exploring available files before processing.
Process, convert, and transform documents using the Nutrient API. Reads input files from the local file system or sandbox (if enabled) and writes results back locally. Features: • Import XFDF annotations • Flatten annotations • OCR processing • Page rotation • Watermarking (text/image) • Redaction creation and application Output formats: PDF, PDF/A, images (PNG, JPEG, WebP), Office (DOCX, XLSX, PPTX) For structured data extraction (typed JSON or Markdown with bounding boxes and confidence scores), use the dedicated parse_document tool instead.
Complex object parameters lack nested schema definitions. 'instructions' in document_processor and 'signatureOptions' in document_signer are typed as bare 'object' with no properties, required fields, or field descriptions. LLMs cannot infer valid structure.
No output schemas documented for any tool. LLMs cannot plan downstream calls or extract required fields (e.g., what does parse_document return? structured JSON? markdown string? both?). Breaks tool chaining.
Destructive operations (document_processor, document_signer, ai_redactor) lack confirmation or dry-run patterns. Agents can irreversibly modify or delete documents without a safety gate.
Inferred effective spec: 2025-06-18+.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | D | 58 | 2025-06-18+ | v2 |
Digitally sign PDF files using the Nutrient Sign API. Reads input files from the local file system or sandbox (if enabled) and writes signed output back locally. Signature types: • CMS/PKCS#7 (standard digital signatures) • CAdES (advanced electronic signatures) Appearance options: • Visible or invisible signatures • Multiple display modes (signature only, description only, or both) • Customizable elements (signer name, reason, location, date) • Support for watermarks and custom graphics Positioning: • Place on specific page coordinates • Use existing signature form fields
Pull specific named fields out of a document into a JSON shape you define, using the Nutrient DWS Data Extraction API. Reads the input file from the local file system or sandbox (if enabled), or fetches it directly from a URL — provide exactly one of filePath or url.
Extract structured data from a document using the Nutrient DWS Data Extraction API. Reads the input file from the local file system or sandbox (if enabled), or fetches it directly from a URL — provide exactly one of filePath or url. Output formats: • spatial — typed elements (paragraphs, tables, key-value pairs, formulas, pictures, handwriting) with bounding boxes, confidence scores, and reading order. Written to outputPath (the list can be large). • markdown — whole-document Markdown. Returned inline, or written to outputPath when provided (recommended for large documents). Good for RAG and search indexing. • Both at once via formats: ["spatial", "markdown"] — a second format costs no extra credits, so ask for both up front instead of extracting twice. Processing modes (cost per page): text = fast Markdown, no OCR (1 credit); structure = OCR spatial (1.5 credits); understand = AI-augmented, default (9 credits); agentic = VLM-augmented (18 credits). Note: markdown output and any extracted content are returned into this conversation and may be logged by the host. For sensitive documents, prefer spatial output to a file plus targeted extract_fields calls.
No error handling guidance. Tools do not document what errors can occur, whether they are retryable, or what the LLM should do next. E.g., parse_document may fail on unsupported formats, but no recovery hint is provided.
Parameter 'criteria' in ai_redactor is a free-form string with no enum or format constraint. Description says 'custom instructions' but does not specify valid syntax, examples, or limits. LLMs will guess at format.