"React Query" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Read-only MCP server for short-term rental owners in Poland. Query reservations, availability, pricing, guest reviews, and monthly stats via 10 tools. OAuth 2.1 with PKCE or static Bearer token.
Connect AI agents to Prosyo to query pipeline metrics, search B2B prospects, and manage multichannel LinkedIn and cold email outreach.
React components and blocks with motion. Search docs, props and shadcn install commands.
# **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.
Marketgenius MCP Server offering our free investment tools as live, interactive React apps. Directly inside your AI client.
Analytics for MCP servers. Query your tool calls, first-call success, retries and schema cost.
Query and join across SaaS tools, SQL, and NoSQL databases through one unified SQL interface.
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
Your agent needs the Google results page as it actually renders — organic and paid, the AI overview, maps, images, news, jobs and the finance panel — not a scraped guess. **What you can ask for** • "What does the SERP for this keyword look like in Germany, on mobile?" • "Does this query trigger an AI overview, and what does it say?" • "Who is advertising against our brand name?" • "Find local results and the map pack for this phrase." • "Search Google by this image and tell me where else it appears." **How to use it** Point any MCP client at https://mcp.aisa.one/seo-serp/mcp and sign in with OAuth — there is no key to create or paste. 38 tools across Google's surfaces: organic, ads and advertisers, AI mode, autocomplete, images, news, maps and local, events, jobs, datasets, scholar, finance quotes and markets, plus Semrush's organic and paid result sets. **Why this rather than the source** Location and language are parameters, so you can read the page a customer in another country sees. **It is also a door to the rest** The same login reaches 26 sources and 580+ operations. Read the SERP here, then ask the same agent who links to the winner or how much traffic they get — without adding a second server. **What it costs** Finding and inspecting an operation is free. Running one is billed per call at API prices, with no seat and no monthly minimum, and every call takes max_price_usd so an agent cannot overspend by accident. **Where else it reaches** https://mcp.aisa.one/seo-serp-other-engines/mcp for Bing, Yahoo, Baidu, Naver, Seznam and YouTube. https://mcp.aisa.one/seo/mcp for all of it at once — rankings, keywords, backlinks, site health and AI-answer visibility across DataForSEO, Semrush and Ahrefs.
Beamline UI installs React UI code into your own repository: 200+ components and 50+ complete screens by Danylo Pravda. Editable source lands in src/ui/beamline; compiled archives live in your app's .beamline/packages/. Commit those files with your app. Nothing at runtime calls Beamline servers. The hosted MCP server is an optional discovery and installation tool for your coding agent; the shadcn CLI installs the same parts. Nine looks, dark and light. The Complete System is $49 launch price, plus VAT or sales tax where it applies: one payment for one person's Beamline account, MCP, library, installs and updates, with lifetime updates for as long as we publish the purchased system. Teammates, contractors and clients may use, edit, build and ship the installed code as part of that app. They need their own licence for Beamline access or to take its parts into other apps. The free sample remains MIT, including commercial use. https://beamline.io
Read-only marketing analytics for AI assistants. Query cross-platform ad performance (Google Ads, Meta, TikTok, LinkedIn), GA4 and Search Console data, KPI trends and top movers, offline media (TV, radio, outdoor) and marketing mix modeling results such as channel contribution, saturation and incremental lift from your Animo workspace. OAuth 2.1 sign-in with an Animo account.
Query UK Parliament, elections, crime stats, ONS census data, and national archives
Workplace analytics from Spaceti: query building occupancy, people counts, environmental readings (CO2, temperature, humidity, noise), booking statistics and records, insight events and raw sensor data for your organization's buildings. Read-only, tenant-scoped, OAuth 2.1 sign-in with your Spaceti account. Requires a Spaceti workspace with an Intelligence Pro license.
MEOK ABCI Bridge MCP — read-only Tendermint / Cosmos blockchain query for agents. Built-in registry
Our free Marketgenius investment tools as live, interactive React MCP Apps.
Query your databases and build charts, dashboards, filters and alerts in TractorScope.
n8n MCP — query your own n8n instance (BYO).
Real-time and historical market data for AI agents across stocks, forex, crypto, indices, ETFs, commodities, and bonds. Query live quotes, trades, OHLCV history, market status, sessions, holidays, and symbol metadata through 10 typed MCP tools and one normalized interface. Supports API key and OAuth authentication, with a free tier available.
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
[A4B](https://a4b.ai/) is a flat-rate CMMS (asset & maintenance management) that ships a native MCP server — an integration still uncommon in the CMMS category. AI assistants like Claude and ChatGPT can query asset inventory, create and update assets and maintenance tasks, search history, and generate reports. Secured with OAuth sign-in, audit logging, and per-organization isolation. Docs: https://docs.a4b.ai/mcp/
