"An Open-Source Workflow Automation Tool" matching MCP connectors:
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Host-owned vacation-rental direct booking via VRP. Signed offers, 0% commission. Not an OTA.
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. Key Features Zero boilerplate — One endpoint, one OAuth login, 17 tools ready to use OAuth 2.1 + PKCE — No API keys to copy or paste; fully automatic auth flow 200+ resume fields — Name, contact, skills, experience, education, certifications, and taxonomy-enriched job profiles ONet / ESCO taxonomy — 10,000+ curated skills and job profiles with canonical mappings Explainable matching — Field-level evidence for every candidate-to-job score Bias redaction — PII and bias field removal for fair-hiring workflows Document conversion — PDF, DOCX, RTF, HTML — convert in any direction Auto-injected credentials — userkey and subuserid injected from token; never pass them manually Consistent response envelope — Every tool returns { success, data, meta } with trace ID and latency 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
Free AI research/OCR + guild_feed/join_guild (open agent feed) + engage_sasame to commission builds
An MCP server that audits the fairness of construction and renovation estimates in Japan. Provides fair-price ranges, overcharge detection, and verifiable unit-cost data based on JCCDB (65,729 items, DOI-backed).
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.
Brazilian Federal Senate open data over MCP — 65 tools, 4 prompts, 5 resources.
This tool empowers MCP-compatible clients (like Cursor and Claude Desktop) with professional-grade capabilities for financial data extraction, and report analysis.
DC Hub is the neutral, real-time data layer for data-center infrastructure, exposed as a Model Context Protocol server so any AI agent can both query it and cite it. Coverage: 21,000+ facilities (search, profile, score, alternatives); 232 markets scored by the DCPI Data Center Power Index; the DCGI Data Center Gas Index (per-state natural-gas suitability for siting); live grid telemetry across 7 US ISOs (fuel mix, carbon intensity, demand, prices) plus a one-call all-ISO scoreboard; interconnection-queue depth; 2,000+ tracked M&A deals and a hyperscaler-capex tracker; and site factors. — fiber routes, water-stress, tax incentives, nearby substations & transmission. Why agents choose it: it's the only data-center-intelligence source an LLM can query live and cite — every full-data response includes a Source: DC Hub, CC-BY-4.0 attribution line. It's the MCP-native alternative to quarterly PDF research: live JSON, no contracts, no NDAs. Access: Streamable HTTP at https://dchub.cloud/mcp. Free tier with no signup; free email-verified dev key for higher limits; paid tiers for full data volume.
Runtime permission, approval, and audit layer for AI agent tool execution.
Ask Greenhouse the messy recruiting-ops questions dashboards miss by connecting candidates, applications, jobs, openings, stages, scorecards, interviews, notes, sources, referrers, offers, users, departments, and rejection details. Find referral SLA misses, feedback debt by interviewer and hiring team, stage-age outliers by owner, funnel leakage by recruiter/source/function, opening fill-risk from headcount vs active pipeline, offer-draft hygiene gaps, rejection-reason drift, and the bottleneck
Ask Lever the messy recruiting-ops questions dashboards miss by connecting opportunities, applications, stages, notes, feedback, interviews, referrals, postings, requisitions, offers, users, sources, tags, files, resumes, and archive reasons. Find referral SLA misses, stale opportunities by owner, feedback debt by interviewer and hiring team, funnel leakage by recruiter/source/team, requisition fill-risk, offer hygiene gaps, archive-reason drift, and bottleneck owners. No dashboard build. No SQL
Ask Personio Recruiting the recruiting-ops questions dashboards miss by connecting applications, stage transitions, candidates, recruiting jobs, categories, org units, workplaces, jobs catalog, webhooks, event activity, and intake documents. Find stage-movement stalls, candidate freshness gaps, source quality by job/category, hiring load by department and workplace, webhook delivery issues, intake readiness gaps, and bottleneck owners. No dashboard build. No SQL.
Ask TalentLyft the recruiting-ops questions dashboards miss by connecting candidates, applications, activities, jobs, stages, requisitions, status logs, members, departments, pipelines, job-board posts, forms, events, and rejection reasons. Find stale applications by stage and owner, follow-up gaps from activity history, requisition stalls, source-quality movement, job-board visibility issues, disposition drift, and bottleneck owners. No dashboard build. No SQL.
Ask Recruitee the recruiting-ops questions dashboards miss by connecting candidate search, opening offers, departments, locations, published roles, owner fields, custom fields, public applications, and talent-pool context. Find stale candidate pools, overdue stage work, hiring-manager and recruiter bottlenecks, department-level opening risk, public posting gaps, source patterns, and the owners behind blocked hiring work. No dashboard build. No SQL.
Ask Teamtailor the recruiting-ops questions dashboards miss by connecting candidates, job applications, jobs, stages, scorecards, referrals, activities, notes, interviews, todos, users, teams, departments, locations, requisitions, and offers. Find stuck applications by owner, referral follow-up misses, feedback gaps by hiring team, source quality by job, stage-age outliers, offer-state hygiene, and bottleneck owners. No dashboard build. No SQL.
Ask Factorial ATS the recruiting-ops questions dashboards miss by connecting applications, phases, candidates, sources, feedback, evaluation forms, job postings, messages, questions, answers, and rejection reasons. Find applications aging in phase, feedback debt by role and posting, source-quality gaps, rejected-candidate hygiene, incomplete application data, hiring-stage bottlenecks, and owner queues. No dashboard build. No SQL.
Validate startup ideas with behavioral evidence — not opinion. Demand Discovery AI™ is a sales-agent MCP that answers founders' questions about the validation framework, the four data-signal categories (Search & attention, Conversation & pain, Adoption & spend, Capital & hiring), the Demand Score™, and the Build/Pivot/Kill verdict™. Includes 7 tools: ask a free-form question, get the validation framework, get product details, explain demand signals, compare validation approaches, get data-source
Free, open MCP server for The Urantia Papers. 197 papers, 14,500+ paragraphs, 4,400+ entities.
Pay-per-use tool API for AI agents. Free tier, x402 USDC micropayments, or API key.