"PDF" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Automate production-ready PDF, Word, Excel and PowerPoint documents from templates and JSON data
Send contracts for e-signature, track signing, get signed PDFs and audit trails, verify any PDF.
AI takeoff for construction: turn PDF blueprints into structured, traceable quantities.
Twistly turns your ideas, notes, and documents into ready-to-edit PowerPoint presentations. Describe a topic, paste in text, or share a file (PDF, DOCX, PPTX, or TXT), and Twistly builds a structured deck of up to 50 slides with clear layouts and matching visuals in seconds. Pick from 50+ templates to keep a consistent, on-brand look. Everything comes out as a native, fully editable .pptx file, not a web export, so it opens cleanly in PowerPoint with no broken layouts. Edit it by hand like any normal presentation, or use the Twistly add-in for PowerPoint to keep refining and redesigning your slides. Nothing stays locked in a separate editor. Generation runs asynchronously: a tool call returns a job id, the assistant follows the job, and the finished deck arrives as a download link in the chat. Used by students, educators, business professionals, and teams around the world.
Publishing our production Model Context Protocol (MCP) server for PDFWix (https://www.pdfwix.com) so Claude and AI agent users can securely inspect, merge, compress, split, watermark, and extract text from PDFs.
# **RChilli MCP Hub** RChilli MCP Hub is a production-grade MCP server that exposes RChilli's full HR data intelligence platform as 17 AI-callable tools across 4 categories. Built on 15+ years of HR data intelligence, it is trusted by ATS vendors, HR technology platforms, staffing agencies, and enterprise recruiting teams worldwide. Every tool is read-only and returns a consistent, structured JSON response — no raw exceptions, no inconsistent formats. <br> --- <br> # **Tools — 17 Total** userkey and subuserid are injected automatically from your Bearer token — you never need to pass them manually. <br> --- <br> # **🔍 Resume & Job Description Parsing — 3 tools** <br> > ### **`extract_resume_data`** > > Extracts and converts resumes, CVs, and candidate documents into structured, searchable profiles with contact details, skills, experience, education, certifications, and taxonomy-enriched data for ATS, HCM, and AI recruiting workflows. When used on a careers page or application form, the same extraction call auto-fills every application field in under 10 seconds — documented to increase candidate conversion by up to 194%. Supports 40+ languages with English-normalized output for global intake, and runs in batch mode to process legacy databases or migration backlogs overnight at scale. Also supports resume reprocessing — re-running previously extracted resumes through the latest extraction logic and taxonomy version to bring older records up to current data quality, without requiring a new document from the candidate. Distinct from bulk import (first-time extraction of a new batch) and from talent data refresh (re-enrichment from a newer submitted resume). <br> > ### **`extract_resume_data_from_url`** > > Accepts a direct URL to a PDF, DOCX, or RTF file and returns the same normalized JSON profile as the Resume Data Extraction tool. Ideal for pipeline automation where resumes are stored in cloud storage, S3, or email attachments. Also supports the same auto-fill, multilingual, and batch-processing capabilities as the core extraction tool for URL-based intake sources. <br> > ### **`extract_job_data`** > > Extracts and converts job descriptions into structured hiring data including job title, required skills, preferred skills, responsibilities, experience, education, and taxonomy-normalized role requirements for recruitment automation and candidate matching. <br> --- <br> # **🧠 Skills & Job Taxonomy — 4 tools** <br> > ### **`lookup_skill`** > > Returns authoritative detail for a known skill including description, all aliases, related skills, proficiency levels, and O*NET/ESCO mappings. Use when you need the complete record rather than a ranked search. <br> > ### **`lookup_job_profile`** > > Returns authoritative detail for a known job profile including canonical title, SOC/O*NET code, job family, typical required and preferred skills, salary bands, and work context. <br> > ### **`autocomplete_skill`** > > Accepts a partial skill string (min 2 chars) and returns up to 10 ranked autocomplete suggestions with canonical names and categories. Prevents free-text entry errors and keeps skill data clean at point of entry. <br> > ### **`autocomplete_job_profile`** > > Accepts a partial job title string and returns ranked autocomplete suggestions with canonical titles and job families. Ensures job titles map to taxonomy profiles from the moment a recruiter starts typing. <br> --- <br> # **🛡️ Redaction, Documents & Utilities — 7 tools** <br> > ### **`redact_resume`** > > Redacts personally identifiable information from candidate profiles to support anonymized review, bias-aware screening, compliance workflows, and audit logs. Configurable redaction scope. Idempotent. <br> > ### **`reformat_resume_with_template`** > > RChilli's Resume Reformatting tool accepts any structured candidate profile and applies one of six branded templates (TM001–TM006) to produce a consistently formatted output document in PDF, DOCX, RTF, or HTML — ensuring every candidate is presented in a standardized, professional layout regardless of how their original resume was structured. Designed for staffing firms, recruitment agencies, and enterprise HR teams who need to control candidate presentation at scale, it eliminates manual reformatting effort and enforces brand consistency across all submissions. <br> > ### **`convert_document_format`** > > Accepts a document as base64 or URL and converts between PDF, DOCX, RTF, HTML, and plain text. Preserves formatting fidelity. Useful as a pre-processing step before data extraction on non-standard file types. <br> > ### **`tag_entities`** > > RChilli's Named Entity Recognition tool takes already-extracted HR text and annotates it by wrapping each recognized entity in a structured XML-style label inline — returning output such as `<job_title>Senior Data Engineer</job_title>`, `<skill>Python</skill>`, `<city>Austin</city>`, `<degree>Bachelor of Science</degree>`, and `<organization>Google</organization>` — covering 10+ HR-specific entity types including person name, state, country, date, and year. Unlike data extraction tools that produce separate field lists, tag_entities preserves the full original text structure with entities labeled in place, making the output immediately consumable by ATS field-mapping pipelines, candidate profile builders, and content annotation workflows without any offset calculation or post-processing. <br> > ### **`extract_contacts`** > > Identifies and structures names, emails, phone numbers, LinkedIn URLs, and addresses with field-level confidence scores from candidate records, emails, or documents. Safe for GDPR/CCPA workflows. <br> > ### **`geolocate`** > > Converts partial or informal location text into structured city, state, country, ISO codes, latitude, and longitude. Enables radius-based candidate and job search and supports workforce planning analytics. <br> > ### **`classify_job_zone`** > > RChilli's Job Zone Classification tool reads the job profile from a resume or job description and returns its O/*NET Job Zone — one of five standardized levels ranging from Zone 1 (little or no preparation required) through Zone 2 (some preparation), Zone 3 (medium preparation), Zone 4 (considerable preparation), to Zone 5 (extensive preparation required) — based on the education, experience, and training criteria defined by O/*NET. The returned Job Zone level enables downstream workflows such as candidate-to-role fit filtering, compensation benchmarking, over/under-qualification flagging, and job architecture standardization without any manual O/*NET lookup. <br> --- <br> # **🎯 Search & Matching — 3 tools** <br> > ### **`score_resume_against_jd`** > > Accepts one resume and one Job Description (no index required) and returns an overall match score, dimension scores, skill gap list, and natural-language explanation. Bias-controlled and audit-ready. <br> > ### **`find_matches_in_index`** > > Accepts a resume or Job Description as input and returns the top-N most similar documents from the indexed corpus ranked by semantic similarity. No index setup required for the input document. <br> > ### **`search_indexed_documents`** > > Accepts a query string and returns ranked document references from the tenant's pre-populated index. Supports Boolean and semantic search modes. Requires documents to be indexed before use.
Remote PDF processing over Streamable HTTP: merge, extract, split, rotate, lossless compression, metadata editing and Office-to-PDF. Requires a PaperLumo Bearer API key; OAuth-only clients are unsupported. Free beta: 500 credits/month, 100/day, 5 MB/file. Documentation: https://paperlumo.com/mcp
DocForge turns documents into structured data. Upload a PDF, image, or Office file and get fielded JSON back with per-field confidence scores. 95 templates (invoices, receipts, bank statements, ID docs), custom JSON Schema mode, auto-detect, natural-language instructions. Keyless demo tool included. Free 7-day trial.
A hosted LaTeX editor your assistant can actually use. Search 1,019 free templates, create and edit projects, and compile them to PDF on a real TeX Live farm, getting back the PDF or the compile log when a build fails. Thirteen tools behind OAuth 2.1, with nothing to install and nothing to run locally.
E-signature API for AI agents: send contracts, sign PDF documents, track and download signed files.
144 deterministic file tools: PDF, image, media, convert, analyze. Connect in one click (OAuth).
Generate HTML to PDF documents in bulk or single — raw replacements or based on conditions, loops
Skavio Processing MCP provides secure, company-authenticated PDF processing, OCR, invoice data extraction, document automation, image and media processing, audio transcription, and meeting workflows for AI agents. Supports OAuth authentication, metered processing jobs, and prepaid company credits. Hosted Streamable HTTP MCP server.
- PDFLeanOAuthcom.pdflean
PDF tools for AI agents: validate, extract, merge, split, compress, OCR, sign and redact.
Wanjige - a Chinese AI tool marketplace MCP server with 15,552 callable tools: real-time A-share/HK/US stocks, FX, weather, hot rankings, docs/PDF/Word parsing, TTS, image & video generation, tax and loan calculators, e-commerce profit analytics.
- wcagc — accessibility scanningOAuth unavailableio.github.WCAG-Compliance
Deterministic axe-core accessibility scans (WCAG 2.1 AA, EN 301 549, PDF/UA) via your account.
Translate text PDFs, keep the layout, get bilingual PDFs. MCP: EN/ZH. Website: 92 languages.
RelayPDF is a hosted MCP connector for working with documents. It generates PDFs from HTML, URLs, Markdown, and templates, converts Office files, images, and email, and edits PDFs (merge, split, fill, protect, optimize). It extracts text and JSON with OCR and makes scans searchable. Authenticate with Clerk OAuth or a Bearer token.
Tailor resumes, generate cover letters, render CVs as PDF, and browse 22+ templates.
Create and edit AI mind maps, org charts, and logic charts directly from chat. Build entire maps in one call from an outline, add or move branches, draw cross-links and summaries, apply themes, and export as PNG, SVG, PDF, Markdown, or CSV. No API key required, connects via OAuth 2.1 in one click.
