"1&1" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Ask Claude, ChatGPT, Cursor or any AI tool how your site is doing — the answers come from your own Google Analytics 4 (GA4) property. Paste https://app.anacraft.dev/mcp, sign in with Google and pick your site; nothing to install. Twelve tools: headline metrics against the previous period, live visitors, top pages, events, referrers, traffic sources and countries, page and event search, and an audit that checks whether the GA4 property is measuring correctly before its numbers are quoted. One tool writes: it creates a GA4 property and web stream for a new domain and returns the tag to paste.
Cite42 gives AI agents AI visibility, citations, SEO keywords and trends, plus four weekly or monthly trackers: AI Visibility, AI Competitors, AI Citations and AI Sentiment. Use it over MCP from Claude, Codex or Cursor, or via the REST API. $1 free on signup, no subscription. Learn more at https://www.cite42.dev
图片去文字去水印、本地视频全屏去硬字幕及画面水印，支持抖音、快手、哔哩哔哩、微博等分享链接去平台水印。OAuth 授权；本地文件需宿主上传支持，否则到 qzm.550wai.cn 上传。
Yinli AI (引力AI, formerly FitMeet): an AI-native human connection and instant messaging network.
Translate a user's uploaded text-based PDFs into English or Chinese while keeping the layout, check job status, and fetch temporary links to translated or bilingual PDFs. OAuth 2.0 with PKCE; the user's iSomor account credits apply. Text-based PDFs only (no OCR).
Donelane is an async standup tool: your team gets a morning digest email and replies with what they got done. This MCP server puts your agents in that same loop. Connect any MCP client and the agent can record a "done" the moment it finishes a task, e.g. "Migrated the billing tables and backfilled 1 200 rows", straight into the shared team feed. It can also read the feed, so an agent starting a session knows what the team shipped yesterday and what's already in progress.
RedM (Red Dead Redemption 2 multiplayer) / RDR3 modding. Hosted HTTP endpo int: native lookups (hash ↔ name), semantic search over framework docs (VORP, RSGCore, oxmysql), and grep over `rdr3_discoveries` community data tables (peds, weapons, animations, AI flags, props). No install, no auth.
Onsite technical GEO visibility tests, score trends, sitemap discovery, and domain monitoring to ensure AI crawlers can access your site.
weclapp ERP in your AI assistant: reads instantly, writes only after a preview you approve.
Your agent needs X/Twitter data — who follows a competitor, what a community is posting, who quoted that tweet, what is trending in Japan. Normally that means applying for an X developer account, passing app review, and managing a quota per endpoint. **What you can ask for** • "Who follows @stripe, and which of them are verified?" • "Pull every reply and quote on this tweet and summarise what people object to." • "List this community's moderators and its posts this week." • "What is trending in Japan right now?" • "Give me the full thread context behind this link, including the long-form article." **How to use it** Point any MCP client at https://mcp.aisa.one/twitter-api/mcp and sign in with OAuth — there is no key to create or paste. 29 read tools: users (profile, about, batch lookup by id, search, followers, verified followers, followings, follow check), tweets (timeline, latest, mentions, advanced search, replies, quotes, retweeters, thread context, articles), communities, lists, Spaces and trends. **Why this rather than the source** No developer account to apply for, no app review, no per-endpoint quota to manage. **It is also a door to the rest** The same login reaches 26 sources and 580+ operations. Ask for a handle's followers here, then ask the same agent for that brand's search traffic, its backlinks, or the people to contact — 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/social/mcp for X plus Instagram, Reddit, Pinterest and YouTube; https://mcp.aisa.one/gtm/mcp for those plus Similarweb and Apollo.
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.
Rule engine with built-in simulation. 55 MCP tools for complete business rule lifecycle management.
Ask your AI assistant about your own website's SEO and get answers from your real data, not generic advice. One connector, all your channels: Google Search Console (rankings, clicks, indexing), Google Analytics (traffic and sources), Google Ads (campaigns and search terms), Google Business Profile (local visibility and reviews), Google Trends, keyword research, backlinks and link prospects, competitor rankings, site crawls, and AI visibility (does ChatGPT mention your site?). Ask things like: which keywords am I one push away from page 1 for? Why did traffic drop last month? Which competitor is outranking me, and where? Are my ads and SEO fighting over the same keywords? Then let it act. On a paid plan, your assistant can prepare SEO fixes, content campaigns, and article drafts. Nothing touches your site until you approve it in SEOmatic, and every change shows before-and-after results. Connect via OAuth: log in, pick your site, done. No API key needed.
Tender search + AI CPV finder. Register free: 1 daily email alert, up to 20 results/search.
Short links + QR tracking URLs for agents. Prefer punycode host. Account required to create links.
Read-only public X (Twitter) data: profiles, tweets, threads, followers, search. Pay per result.
RENT-ranked covered-call, CSP & wheel income ideas, your positions & Greeks. Never places orders.
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.
# **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.
128 REST operations. 120 MCP routes; 119 JSON/text ops. OAuth 2.1. Not affiliated with X Corp.
