"Email" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
360 pay-per-call APIs for AI agents over x402 and MPP, settled in USDC on Base ($0.001-$0.25 a call, no account or API key). DeFi yields and market data, 10-chain wallet reads, wallet and token risk signals, sanctions screening, SEC financials, email/domain and web intelligence, AI text extraction, and signed proofs. Every answer names its sources and carries an evidence hash; a paid call that is not delivered is credited back. Built and run by UnyKorn LLC.
AI visibility for your brand: which buyer questions name you in ChatGPT, Perplexity, Claude and Google AI Overviews, which competitors AI recommends instead, which sources it cites, and what to fix first. OAuth sign-in with email and a one-time code.
Formify turns document paperwork into something you can just ask for. Describe the agreement you need and it is built as a real, fillable PDF — text fields, checkboxes, dropdowns and signature space placed where a signing client actually expects them. Send it for electronic signature to one person or several, in a set order or all at once, by email or SMS, and preview exactly where every field landed before anyone is contacted. Prove who signed. Swedish BankID, an ID document scan, a live face check, or a company registration lookup for KYC and AML — including the option to capture an ID document's data without storing the image at all. Attach an AI assistant to the document itself. The recipient can ask it what a clause means and it highlights the passage it is answering about, reads it aloud if they prefer, and answers in English, Swedish or Spanish. They never have to paste your contract into another chatbot to understand it. Then track it. See who signed, who only opened it, and who never looked. Remind only the people who have not signed. Fix a mistyped email, hand someone a link in person, revoke a send, or download the completed document. Built for small businesses — agencies, property managers, trades, clinics and tour operators — where the person winning the client is also the person chasing the signature.
55 tools, 7 Resources, Sigma rules, email SPF/DMARC, MITRE, CVE/KEV, risk_score. No key.
Pay-per-call APIs for AI agents: web scraping, DNS/email checks, classification, trading risk.
AI Agent Builder, Orchestrator & Grader. Build, test, optimize and deploy AI agents from any MCP client. 32 tools: agent CRUD, template deployment, grading & AutoResearch optimization, multi-agent teams, pipelines, memory management, 5-channel deployment (widget, Slack, Telegram, WhatsApp, webhooks), OAuth connectors (email, calendar), usage analytics, EU AI Act compliance reports, and portable agent export/import
email-ish token count, text discarded
Verify the email instantly: Identify the spam email while authenticating your users.
# **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.
232 pay-per-call agent tools: LLMs, search, browser, OCR, media, vision, email. x402 USDC.
Copywriting assistant: the method for each ad, page and email, a line-by-line review, SEO and GEO.
Authenticated email gateway for AI agents — per-agent inboxes, HITL approval, SPF/DKIM verified.
Backend for AI-built apps: database, auth, files, email, AI, payments, deploy, realtime. 170+ tools.
People-enrich: work email + phone, company & domain enrichment. Pay-per-call USDC, no key.
Automated resume screening for small businesses: post jobs, rank applicants, email candidates.
NextBento is a production-ready Next.js 16 SaaS boilerplate with Supabase auth (OAuth, magic link, email/password), Stripe subscriptions, owner/admin/member teams, Resend email, programmatic SEO templates, and 8 AI skills.
Sequenzy MCP server for AI-powered email marketing automation.
Agent-Native Superhuman - email client with keyboard shortcuts and AI triage
- mcpOAuth unavailableio.styleforge
Brand-aware creative studio for Claude: 200+ tools for on-brand ads, video, email and campaigns.
GrowthHackers copywriting prompts (Meta/Google Ads, email, VSL) as MCP tools — search & generate.
