"All About Docker" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
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.
AXL MCP lets AI assistants create and manage landing pages, courses, email campaigns, CRM records, and marketing workflows inside AXL. Built for growing expert businesses, it turns chat requests into real work across sales, marketing, and course delivery. An AXL account is required. Sign in securely with OAuth 2.1. Website: https://axl.tech/developers/mcp . Setup guide: https://docs.axl.tech/mcp . Watch AXL in 77 seconds: pages, courses, CRM, and automation. Product overview: https://www.youtube.com/watch?v=jlhR9CafIww
# **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.
Check shipping costs for all logistics services in Indonesia.
Connect any AI agent to the NachoNacho marketplace with the Model Context Protocol MCP Let your AI search thousands of B2B SaaS AI products, compare deals, and sign up — all from chat
Real-time US business entity search across all 53 US jurisdictions - all 50 states, DC, Puerto Rico, and US Virgin Islands. Search, verify, and check the status of any LLC, corporation, or registered entity. Ideal for KYB, due diligence, and vendor verification.
Plan your hike. Get your developer token at https://Infoseek.ai/mcp
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, what’s sitting in the pitch queue. It's a view into the startups that you've invested in (or are thinking of investing in!)
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 — all from your AI coding assistant. Learn more about the [MCP integration](https://openclaw.com/openclaw-mcp-integration).
Oviond brings data from 100+ marketing platforms into one reporting platform. Through the Oviond MCP server, AI assistants can securely access and work with Oviond clients, projects, reports, dashboards, widgets, and marketing data. Ask questions about your reporting data, analyze marketing performance, and manage reporting workflows directly through your AI assistant.
Analytics for MCP servers. Find out which of your tools agents get wrong. MCPulse shows you which tools AI agents retry, which come back empty, and which they never call at all. Two lines inside your own server. It never sees your arguments or your results. getmcpulse.com
Ask about your trusts, entities, policies and documents. Every answer cites a page or declines.
Connect Karma.Domains to ChatGPT, Claude, Cursor, VS Code, or another MCP client — and find a domain in plain language. The same auctions, expired, backorder, and buy-now data you use in the app, plus saved filters, notes and tags, guest share links, and SEO enrich — all from chat.
- BrowserlessOAuth via extensionio.browserless.mcp
Browserless MCP - Cloud browser automation for AI agents with bot-detection bypass. Scrape and crawl sites, take screenshots, generate PDFs, run headless Chrome functions or an autonomous browsing agent, all through MCP.
- KamaiOAuthio.kamai.mcp
Kamai is an AI-powered construction blueprint intelligence platform that automatically extracts quantities, measurements, objects, rooms, walls, and other structured data from construction drawings. Through MCP, you can connect Kamai directly to AI assistants and ask questions about your plans in natural language, generate takeoffs and tables, analyze relationships between building elements, and use blueprint data inside broader estimating, procurement, and construction workflows. Kamai turns
- AdszyOAuthai.adszy.mcp
Adszy is an AI Google Ads agent — 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
- DoverOAuthcom.dover.app
Dover's MCP server connects your AI assistant directly to your Dover ATS. Find candidates, review applications, move candidates through your hiring pipeline, add notes, and get interview prep- all without leaving your AI conversation. Built for founders and hiring teams who want to manage recruiting faster and more efficiently.
- reapOAuthvideo.reap.mcp
The Reap MCP server connects your AI agent directly to your Reap workspace. Once connected, your agent can run the full pipeline for you — upload a video, generate clips, add captions, reframe, dub, transcribe, and publish to social platforms — all from inside your chat. Works with Cursor, Claude Code, VS Code, GitHub Copilot, Codex, Gemini CLI, and any other MCP-compatible agent.
Connect your Rock workspace to any MCP client. Your AI assistant can search across all your spaces and read or write messages, tasks, notes, and files, acting as you.
