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# **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 β no raw exceptions, no inconsistent formats. <br> --- <br> # **Tools β 17 Total** userkey and subuserid are injected automatically from your Bearer token β you never need to pass them manually. <br> --- <br> # **π Resume & Job Description Parsing β 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 β 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 β 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> # **π§ Skills & Job Taxonomy β 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> # **π‘οΈ Redaction, Documents & Utilities β 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 (TM001βTM006) to produce a consistently formatted output document in PDF, DOCX, RTF, or HTML β 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 β 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>` β 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 β 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) β 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> # **π― Search & Matching β 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.
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. β 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 β 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.
Connect your AI assistant to Signed and ask about your angel investing in plain English: how the portfolio is doing, what distributions came in this year, whatβs sitting in the pitch queue. It's a view into the startups that you've invested in (or are thinking of investing in!)
Read-only cloud cost and infrastructure governance across AWS, Azure and GCP. 85 tools covering cost overview and trends, cost by provider/resource/tag/team, budgets, resources, schedules, recommendations, tagging policies, audit logs, anomalies, Kubernetes resources and pod logs. Hosted remote server, nothing to install. Docs: https://zop.dev/learn/mcp-server?utm_source=glama&utm_medium=listing&utm_campaign=mcp-directory Claude setup: https://zop.dev/learn/how-to/set-up-zopnight-mcp-for-claude
1Create and drive plori cloud agents and workflows over MCP; each agent has its own cloud computer.
Hosted GEO/AEO analysis for public webpages. Compares a target page with up to six competitors, identifies citation gaps and information-gain opportunities, prioritises improvements, and generates shareable reports.
FinOps for Google Cloud: size 1- and 3-year CUD commitments to known demand. Also solves LP/MIP.
A wiki about your life that writes itself. Save from any AI chat, recall it in the next.
Adszy is an AI Google Ads agent β it finds wasted spend, drafts the fixes, and applies the changes you approve. The Adszy MCP server brings your Google Ads answers into Claude and Codex: ask about your account in plain English and get live data from your linked account (tools like get_search_terms and get_negative_keyword_candidates). Read-only until you approve. More at https://adszy.ai/mcp
Build financial models as code. Cloud execution, GSheets MCP, version control, collaboration.
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.
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
Join.cloud is Slack for AI agents. Create rooms, invite agents, and let them collaborate in real-time. Agents communicate via broadcast messages or DMs, and each room is a standard git repository for code collaboration (clone/push/pull).
A managed AI marketing agent that plugs into all your AI tools. Ask about your marketing in plain English β Agentcy analyzes data across GA4, Google Ads, Search Console, WooCommerce, and more, then delivers synthesized insights and recommendations. Not a data dump. Not a dashboard. An agent that thinks. Sign up at goagentcy.com to configure your domains and data sources. Free plan includes 50 requests/month β paid plans start at $29/mo.
Access CQC care ratings, NHS health services, and food hygiene data across the UK
Connect AI agents to BoomTax for IRS information return filing. Query filings (1099, W-2, 1095, etc.), check e-file status and errors, look up payers, and get filing summaries across tax years. **Tools:** - Search and filter filings by tax year, form type, and status - Get filing details with payer info and e-file status - View e-file errors with IRS error codes and messages - Look up payers/issuers with filing counts - List all supported filing types and e-file availability
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 β all from your AI coding assistant. Learn more about the [MCP integration](https://openclaw.com/openclaw-mcp-integration).
Automate cloud Chromeβnavigate, click, type, screenshot, run code, record screen video
x402 data & AI gateway: 194 services + AI Gateway free data (save 50-90% tokens).
Hosted remote MCP server for AI-driven stealth browser automation. Connect any MCP client (Cursor/Cline natively, Claude Desktop via mcp-remote) β no install, no Docker, no Playwright. Drives a real Chromium with residential proxies, automatic CAPTCHA solving, persistent profiles, and a live viewer URL for human-in-the-loop. Three tools: humanbrowser_run, humanbrowser_stream, humanbrowser_viewer_url. Same hb_live_* Bearer token works for both MCP and the A2A 1.0 endpoint.