"Extracting Orders from PDF Files" matching MCP connectors:
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PDF engagement layer for apps and agents: tracking links, read analytics, and a full PDF toolset.
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. Use Cases Resume screening — Parse and structure resumes for AI-powered shortlisting Job description analysis — Extract required skills, experience range, and qualifications from any JD Candidate-to-job matching — One-to-one fit scoring with field-level evidence, no indexing required Talent pool search — Keyword search across your indexed resume database Skill gap analysis — Identify what a candidate is missing for a specific role Bias-free hiring — Redact names, photos, gender, and age before sharing with hiring managers Taxonomy enrichment — Look up and autocomplete 10,000+ standardized skills and job titles Document standardization — Convert and reformat candidate documents into consistent templates Tools — 17 Total userkey and subuserid are injected automatically from your Bearer token — you never need to pass them manually. 🔍 Resume & Job Description Parsing — 3 tools extract_resume_data Converts resumes, CVs, and candidate documents into structured, searchable profiles — contact details, skills, experience, education, certifications, and taxonomy-enriched data ready for ATS, HCM, and AI recruiting workflows. Used on a careers page or application form, the same 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 clear legacy databases or migration backlogs overnight. It 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, with no new document required from the candidate. This is distinct from bulk import (first-time extraction of a new batch) and from talent data refresh (re-enrichment from a newer submitted resume). extract_resume_data_from_url Accepts a direct URL to a PDF, DOCX, or RTF file and returns the same normalized JSON profile as extract_resume_data. Built for pipeline automation where resumes live in cloud storage, S3, or email attachments — with the same auto-fill, multilingual, and batch-processing capabilities applied to URL-based intake. extract_job_data Converts job descriptions into structured hiring data — job title, required and preferred skills, responsibilities, experience, education, and taxonomy-normalized role requirements — ready for recruitment automation and candidate matching. 🧠 Skills & Job Taxonomy — 4 tools lookup_skill Returns the authoritative record for a known skill: description, all aliases, related skills, proficiency levels, and O*NET/ESCO mappings. Use it when you need the complete record rather than a ranked search. lookup_job_profile Returns the authoritative record for a known job profile: canonical title, SOC/O*NET code, job family, typical required and preferred skills, salary bands, and work context. autocomplete_skill Takes a partial skill string (minimum 2 characters) and returns up to 10 ranked suggestions with canonical names and categories — preventing free-text entry errors and keeping skill data clean at the point of entry. autocomplete_job_profile Takes a partial job title and returns ranked suggestions with canonical titles and job families, ensuring titles map to taxonomy profiles from the moment a recruiter starts typing. 🛡️ Redaction, Documents & Utilities — 7 tools redact_resume Redacts personally identifiable information from candidate profiles to support anonymized review, bias-aware screening, compliance workflows, and audit logs. Redaction scope is configurable, and the operation is idempotent. reformat_resume_with_template Takes any structured candidate profile and applies one of six branded templates (TM001–TM006) to produce a consistently formatted document in PDF, DOCX, RTF, or HTML — so every candidate is presented in a standardized, professional layout regardless of how their original resume was structured. Built for staffing firms, agencies, and enterprise HR teams that need to control candidate presentation at scale, it removes manual reformatting effort and enforces brand consistency across every submission. convert_document_format Accepts a document as base64 or URL and converts between PDF, DOCX, RTF, HTML, and plain text while preserving formatting fidelity. Useful as a pre-processing step before extraction on non-standard file types. tag_entities Takes already-extracted HR text and annotates it in place, wrapping each recognized entity in a structured XML-style label — 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> — across 10+ HR-specific entity types including person name, state, country, date, and year. Unlike extraction tools that produce separate field lists, tag_entities preserves the full original text structure with entities labeled inline, making the output immediately consumable by ATS field-mapping pipelines, candidate profile builders, and content annotation workflows — with no offset calculation or post-processing. extract_contacts Identifies and structures names, emails, phone numbers, LinkedIn URLs, and addresses from candidate records, emails, or documents, with field-level confidence scores. Safe for GDPR/CCPA workflows. geolocate Converts partial or informal location text into structured city, state, country, ISO codes, latitude, and longitude — enabling radius-based candidate and job search plus workforce planning analytics. classify_job_zone Reads the job profile from a resume or job description and returns its ONET Job Zone — one of five standardized levels, from Zone 1 (little or no preparation required) through Zone 2 (some preparation), Zone 3 (medium), Zone 4 (considerable), to Zone 5 (extensive preparation required) — based on ONET's education, experience, and training criteria. The returned level powers candidate-to-role fit filtering, compensation benchmarking, over/under-qualification flagging, and job architecture standardization, with no manual O*NET lookup. 🎯 Search & Matching — 3 tools score_resume_against_jd Accepts one resume and one job description — no index required — and returns an overall match score, dimension scores, a skill gap list, and a natural-language explanation. Bias-controlled and audit-ready. find_matches_in_index Accepts a resume or job description and returns the top-N most similar documents from the indexed corpus, ranked by semantic similarity. No index setup is required for the input document itself. search_indexed_documents Accepts a query string and returns ranked document references from the tenant's pre-populated index. Supports both Boolean and semantic search modes; documents must be indexed before use.
Generate on-brand images from your AI agent: design, edit, and render templates over MCP.
Publish websites from Claude, the terminal, or CI — drop a folder, get a link that doesn't expire.
Turn long videos into short, captioned viral clips from your AI assistant. 28 tools, OAuth.
Drive OctoPerf load testing from any AI agent — import, edit, validate, run scenarios, read metrics. Hosted remote server, OAuth 2.1 (DCR + PKCE), no API key.
Your unified inbox — everything that reaches you, understood and actionable from your AI assistant.
CompanyLens is a remote MCP server giving AI agents instant access to official company registry data across 19 jurisdictions in Europe, the Americas, and Asia-Pacific. Eighteen read-only tools let you search companies and people, look up officers and beneficial owners, map corporate networks through shared directors, screen names against the UK disqualified directors register, find every company at a registered address, and pull filing history — all from a single connector. Visit our website: https://companylens.io
Connect your AI assistant to your Peec AI account to monitor and analyze your brand's visibility across AI search engines like ChatGPT, Perplexity, and Gemini. Ask questions about brand visibility, competitor comparisons, source citations, and trends: all in plain language, directly from your AI tools.
ShaBaas Pay MCP lets AI agents securely create PayTo agreements, initiate payments, and check statuses via structured tools. Authenticate with your ShaBaas Pay API key and control tool access from the dashboard.
Get social media data from Instagram and TikTok: profiles, posts, videos, comments, and more.
CareerProof MCP gives AI agents direct access to a professional-grade career and workforce intelligence platform. Two namespaces: atlas_* for HR/TA teams (candidate evaluation, batch shortlisting, competency scoring, interview generation, JD analysis, custom eval frameworks, research reports) and ceevee_* for professionals (CV optimization, career positioning, salary intelligence, market reports). Backed by RAG knowledge from 50+ premium research sources (McKinsey, BCG, HBR, Gartner, WEF)
Manage your dedicated AI assistant instances on [OpenClaw Direct](https://openclaw.com) through natural language. Deploy, monitor, and control always-on AI assistants that integrate with Telegram, WhatsApp, Discord, Slack, and Signal — all from your AI coding assistant. Learn more about the [MCP integration](https://openclaw.com/openclaw-mcp-integration).
Agent Interviews is an AI-powered research platform designed to conduct qualitative interviews an...
- apify-mcp-serverOAuth
Extract data from any website with thousands of scrapers, crawlers, and automations on Apify Store ⚡
Search company disclosures and financial statements from the Korean market. Retrieve stock profile…
FFmpeg Micro MCP Server. Transcode videos from n8n or Make using FFmpeg in the cloud. Code+Docs: https://github.com/javidjamae/ffmpeg-micro-mcp/
Access live company and contact data from Explorium's AgentSource B2B platform.
Monetize and manage your Tip4Serv store directly from your LLM.