"Servers that Enhance Productivity" matching MCP connectors:

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.

Publish websites from Claude, the terminal, or CI — drop a folder, get a link that doesn't expire.

Sports-analytics research assistant that grades its own model and reports the losses. $9.99/mo.

Mezmo MCP is a remote Model Context Protocol (MCP) server that lets AI assistants and IDE chat agents interact with the Mezmo observability platform via the Model Context Protocol. Use it for streamlined observability, log analysis, and root-cause analysis in your favorite tools. Add Mezmo MCP and you can: 🕵️ Run advanced Root-cause analysis over recent logs 📦 List and describe Pipelines 📤 Export and filter Logs with powerful query syntax

Manage CI/CD pipelines, debug failed builds, and optimize test suites directly from your AI tools and agents - no terminal required. The CircleCI MCP Server is a remote server hosted by CircleCI that connects AI tools and agents directly to your CI/CD pipelines, giving you a conversational interface to the same pipeline, workflow, job, and artifact data you'd normally reach through the CircleCI CLI or dashboard.

An accounting engine your AI connects to over MCP. Hand it bank and card statements, invoices, bills and receipts; get reconciled double-entry books with every number traceable to the page it came from. Requires a host that can reach files on your machine — Claude Code, Codex, Cursor, Grok Build, or Claude Desktop + Cowork. Browser chat can install it but cannot send files. Open beta; first 1,000,000 tokens free.

Run Meta, Google, Amazon, and Shopify ads from Claude, ChatGPT, and Cursor. ~150 tools: read performance, inspect campaigns and audiences, research competitor ads, see ad spend vs Shopify revenue, and take confirm-gated writes (pause, budgets, campaign/ad launches) that always stage paused. OAuth 2.0 with dynamic client registration.

aX is an agent-native collaboration network. A single Streamable HTTP MCP endpoint gives agents persistent identity, real-time messaging with @mentions and threads, tasks and handoffs, shared workspace context, semantic search, agent discovery, and rendered MCP App / widget artifacts that humans and agents can open and play back.

mrmarket.ai is a remote MCP server that resolves financial research questions against clean, structured market data. Multi-factor screens, rankings, cohort-relative comparisons, point-in-time event studies, and forward-return analysis across 11,000+ US-listed tickers, returned as structured rows.

SoupNet gives your AI agents one shared memory of how you think — across Claude, Cursor, and ChatGPT. Each checks your past decisions as searchable “recipes” and acts on your real judgment. Share it, and your team’s agents inherit that judgment too.

Your unified inbox — everything that reaches you, understood and actionable from your AI assistant.

A personal RAG database you build from chat, so AI creates work that sounds like you.

Remote MCP server for Manzuko — a Polish store with jewelry-making supplies (beads, findings, stones, Miyuki/Toho). AI agents can search the catalog, fetch product details, check component compatibility, build/edit a cart, apply discount codes, list shipping methods and pickup points, and place an order that returns a Przelewy24 payment link. Also available as in-browser WebMCP (navigator.modelContext). Auth: OAuth 2.1 (customer account) or a static API key. Discovery: https://manzuko.com/.well-

Hosted MCP server that gives AI agents (Claude, Cursor, Codex, etc.) access to the full Runware API — image generation, video generation, audio generation, 3D, upscaling, background removal, captioning, and more.

fomox402 is a last-bidder-wins on-chain game on Solana, designed to be played autonomously by AI agents. Every bid mints a key that earns passive $fomox402 dividends; the last bidder when the timer hits zero wins the pot. Drop our MCP server into Claude Desktop, Cursor, Goose, or any HTTP-speaking client to play.

AI-Ready Data Platform that fills the missing layer between data management and AI execution.

An AI concierge that turns static forms into adaptive AI conversations. From any MCP client.

Open-source MCP server that gives AI agents access to real email and calendar in one npm install. Solves the problem of AI agents hitting a wall when they need your inbox.

Lexicon Oracle is a deep-knowledge engine that analyzes population data and professional behaviors unavailable in standard LLM training. Beyond raw demographics, it specializes in predictive modeling for newer generations (Gen Z/Alpha), identifying emerging cultural trends, and forecasting the success probability of new business ventures based on behavioral market fit. Key Capabilities: Predictive Success: Forecasts business viability and market adoption. Generational Intelligence: Deep-dive ana

Zero-value tracer token system that tracks AI agent activity across the internet. Agents earn tokens by submitting threat intelligence traces, with free trust verification (verify_trust) and paid threat intelligence feeds. 8 tools: submit_trace, check_token_balance, mutate_token, get_trace_schema, verify_trust (free) + threat_intelligence_feed, bulk_verify_trust, query_trace_analytics (paid).