"Understanding Requirement Analysis" matching MCP connectors:

Real-time options analytics MCP server. Access gamma exposure (GEX), delta exposure (DEX), vanna exposure (VEX), dealer positioning, volatility surfaces, Black-Scholes greeks, implied volatility solver, and key options levels for any US equity — all through natural language. 14 read-only tools covering exposure metrics, volatility analysis, pricing, and market data.

Read-only fantasy analysis for ESPN, Yahoo, and Sleeper leagues via MCP

Mobile-game ad creative intelligence across SDK ad networks: search, rankings, AI hook analysis.

Turkish gold-market digest, derived indicators and analysis search. Keyless, read-only, gated.

Structured restaurant intelligence for AI platforms. 760K+ restaurants catalogued across 26 countries, 62K+ with deep 37-dimension analysis including letter grades, occasion-aware recommendations, menu insights, and neighborhood exploration. Six tools: find restaurants by name, search by location, explore area dining scenes, look up detailed profiles (3 detail tiers), ask natural language questions, and get personalized recommendations.

Search FDIC institutions, branches, failures, and peer analysis over MCP.

MCP server for the CrawlGraph backlink-intelligence API. Gives any MCP client - Claude Desktop, Claude Code, Cursor, Cline, Zed, Windsurf - backlink lookups and competitor gap analysis built on the public Common Crawl webgraph (4.4B edges, 120M domains).

Wash-filtered intelligence layer for x402 — read-only access to category stats, service details, wash analysis aggregate, service search, and 24h trends.

Competitor intelligence for AI agents — SEO, traffic, social, Product Hunt, pricing, AI insights.

Live market data, signals, positions, and macro analysis for crypto, KR stocks, and US stocks.

Crypto market signals, technical indicators, and sentiment analysis for AI agents.

Search and compare Polish bank offers in real time. Find the best savings accounts, deposits, personal accounts, and business accounts. Browse active bank promotions with expert analysis of hidden fees and traps. Get referral codes for bonuses and calculate deposit interest with tax. 11 tools covering all Polish banking products.

Real-time Amazon data API built for AI agents. 200M+ products, 1B+ reviews, live BSR, pricing, and competitor data as clean JSON. 10 agent skills for market research, competitor monitoring, pricing analysis, and listing audits.

Keycloak identity management expert with semantic search, protocol guides, and config analysis

Get stock quotes, financial statements, market data, and company analysis from Yahoo Finance via MCP.

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: 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). 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. 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. 🧠 Skills & Job Taxonomy — 4 tools 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. 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. 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. 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. 🛡️ 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. Configurable redaction scope. Idempotent. 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. 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. 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. 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. 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. classify_job_zone: RChilli's Job Zone Classification tool reads the job profile from a resume or job description and returns its ONET 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 ONET. 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. 🎯 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, skill gap list, and natural-language explanation. Bias-controlled and audit-ready. 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. 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.

SEO research SaaS exposed as 30+ MCP tools. Forge niche analysis, plans, and writer-ready briefs.

Provide real-time cryptocurrency price data and market analysis.

Academic paper search, scientific literature, citation analysis, arXiv & semantic related-work.

Virlo — Short-form video analytics and trend intelligence API. 20 MCP tools and 3 workflow prompts covering keyword search (Orbit), creator analysis (Satellite), niche monitoring (Comet), hashtag analytics, trending videos, and long-term tracking across TikTok, YouTube Shorts, and Instagram Reels. Async operations auto-poll for results. Bearer token auth (virlo_tkn_*). Docs: https://dev.virlo.ai/docs/mcp