"All About Docker" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Production-grade MCP server for discovering AI agent frameworks, vector databases, LLM gateways, and generating certified Docker Compose deployment stacks
Zero-Ops deploy of a private AI coding workspace onto your own VPS — straight from your AI chat. Provide only your Ubuntu server credentials and Fractera automatically configures everything (Nginx, HTTPS, auth, database, services) in about 10 minutes: 5 AI coding engines, an autonomous Hermes orchestrator, and private graph memory (LightRAG). No terminal, no DevOps. IP-first and free; a custom domain with HTTPS is an optional later step.
Nephia is a brand monitoring service, and this is its remote MCP server. Claude, Cursor, ChatGPT or any MCP client can read the mentions your brand gets on 14 sources: X, Reddit (posts and comments), YouTube, TikTok, Bluesky, Hacker News, Mastodon, Lemmy, GitHub, Product Hunt, Stack Overflow, any RSS feed, Vinted, and AI answers from ChatGPT, Gemini and Perplexity. Every mention arrives already read, with its sentiment and intent, so an agent can answer plain questions: which complaints came in since Friday, what Reddit said about us this week. The source is an argument, not a tool, so one call reads every source you watch. Sign-in is OAuth in the browser: no API key to copy. The consent screen has three permissions: read your mentions and Queries, change what is running (pause, resume, retire), and spend credits (semantic search and AI passes), which arrives unticked. Every tool description states its cost, so a model can budget before it spends. The server is on every plan, Free included, and reading your own mentions through it costs nothing.
Formify turns document paperwork into something you can just ask for. Describe the agreement you need and it is built as a real, fillable PDF — text fields, checkboxes, dropdowns and signature space placed where a signing client actually expects them. Send it for electronic signature to one person or several, in a set order or all at once, by email or SMS, and preview exactly where every field landed before anyone is contacted. Prove who signed. Swedish BankID, an ID document scan, a live face check, or a company registration lookup for KYC and AML — including the option to capture an ID document's data without storing the image at all. Attach an AI assistant to the document itself. The recipient can ask it what a clause means and it highlights the passage it is answering about, reads it aloud if they prefer, and answers in English, Swedish or Spanish. They never have to paste your contract into another chatbot to understand it. Then track it. See who signed, who only opened it, and who never looked. Remind only the people who have not signed. Fix a mistyped email, hand someone a link in person, revoke a send, or download the completed document. Built for small businesses — agencies, property managers, trades, clinics and tour operators — where the person winning the client is also the person chasing the signature.
Real-time options analytics MCP server. Access gamma exposure (GEX), delta exposure (DEX), vanna exposure (VEX), dealer positioning, volatility surfaces, Black-Scholes greeks, implied volatility solver, and key options levels for any US equity — all through natural language. 14 read-only tools covering exposure metrics, volatility analysis, pricing, and market data.
Find the stories worth writing about: discover emerging stories, rank the angle, draft from sources.
ClaimHit runs 9 frontier AI models simultaneously to find products and technical standards that potentially infringe your patent in about 60 seconds. Results are scored by multi-model consensus across four factors: how many models agreed, which claim elements are covered, how strong the evidence is, and whether the product is functionally equivalent to your invention.
The HUB of ai skills Publish, discover, and use AI agent skills across all platforms. Connect the MCP server once and every skill on the registry becomes instantly available — no local installation needed.
Multicalci exposes 9 process engineering calculation engines as MCP tools, so AI assistants call real standards-referenced code instead of estimating the arithmetic. All results are computed with iterative numerical methods (Newton-Raphson, quadrature) rather than approximations. Tools include: pipe pressure drop (Darcy-Weisbach/Colebrook-White), control valve sizing for liquid and gas (IEC 60534-2-1), orifice flow (ISO 5167-2, Reader-Harris/Gallagher), gas Z-factor (Peng-Robinson), NPSH availa
54+ pay-per-use AI & data tools for agents, payable in USDC via x402 on Solana — no API keys, no subscriptions. AI image, video, music and voice generation (cheaper than official APIs), web search, cited research reports, Claude Opus Q&A, crypto prices, page scraping, domain info and more. Pay only for what you call, straight from the agent wallet. Free directory tool lists all live endpoints.
APICK Korean data, OCR, search, conversion, image and video generation, and asynchronous TTS
22 AI microservices with x402 micropayments: summarize, translate, code-review. USDC on Base.
Measure what ChatGPT, Claude, Gemini and 4 more AI engines say about any business. No auth.
Agent-only BBS: live channels, persistent threads, artifact drops, signed history, ROOT takeovers.
Alternatives to well-known AI tools, with revenue verified through Stripe, never invented.
# **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.
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
- 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
- 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.
