"Information about iCloud Calendar" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Enhanciar is an AI company brain for every team. It reads your Slack, Gmail, Google Drive, Notion, Confluence, Jira, Linear, Zendesk, GitHub code and databases, writes a wiki from them, and answers questions from any MCP client with a link to the source. Tools: query (cited answers), search_wiki, get_page, list_pages, get_graph, get_process_map, impact (what a code change touches), list_repos, list_skills, get_skill, propose_action and list_proposed_actions (tickets, Slack messages, Gmail drafts, Notion pages and calendar holds that a person approves first). Hosted service, bring your own AI key. Plans: Solo $24 a month, Team $100 a month for up to 10 people. Create an API key in Settings at https://enhanciar.in.
Ask Nebula (Mumbai) about AI-first B2B digital marketing: services, sectors, GEO/AEO Answers, blogs.
Connect AI agents to Emitd email sending, message tracking, templates, and automations. Emitd hosts a Model Context Protocol server for integrating supported email operations into AI-agent workflows. Connect a compatible client to the hosted endpoint (https://mcp.emitd.com/mcp) and authenticate with an Emitd API key. Available tools depend on the key's permissions and enabled features. Emitd's capability areas include sending email, message activity, templates, contacts, audiences, segments, domains, analytics, inbound email, broadcasts, automations, webhooks, and suppressions. Use restricted keys, sending guardrails, and approval settings appropriate to each workflow. For more information check https://emitd.com
20 inbox, calendar, travel, meals and family-logistics skill products. 7 of 9 free.
Postemi is a social media scheduler for 37 platforms and apps. Your AI agent can list your channels, check the calendar, upload media, preview a post and schedule it to Instagram, TikTok, LinkedIn, X, YouTube, Threads, Bluesky, Pinterest and more. It always shows a preview first, and you confirm before anything is saved. Sign in with OAuth; every plan starts with a 7-day free trial.
Ask about your business's sales, Google rankings, AI visibility and email marketing, and have Kooga write, change and send for you, asking first before anything leaves Kooga.
Cloud-native, serverless Model Context Protocol (MCP) server using Streamable HTTP (https://brightcanoe.com/api/mcp) that enables AI agents like Claude and Cursor to check live calendar availability, create appointments, search Client 360 CRM records, and retrieve 24/7 AI voice receptionist call logs.
XMemo is a user-owned Memory OS for AI agents, providing a shared, persistent memory layer across AI assistants, IDEs, CLIs, tools, projects, and sessions. It enables ChatGPT, Claude, Codex, Cursor, Gemini, and other supported AI clients to access authorized long-term context without requiring users to repeatedly explain their preferences, project decisions, or previous work. Beyond basic memory storage and retrieval, XMemo supports semantic search, contextual recall, memory updates and corrections, source attribution, version history, project-scoped context, task tracking, and governed memory lifecycle management. Identity-aware access controls, scoped authorization, and memory isolation help users manage which agents and workflows can access their information. XMemo also provides advanced capabilities for structured knowledge, reusable procedures, and memory consolidation through its broader Memory OS platform. Connect through hosted MCP with OAuth or bearer-token authentication, or integrate directly through REST APIs and supported client tools. Memory remains available across authorized clients and sessions, with user-controlled access, export, and deletion. Website: https://xmemo.dev Documentation: https://xmemo.dev/docs
Server-side conversion tracking for Meta, TikTok, etc. Set up tracking and ask about events.
Mail, Calendar, Messages, Notes, Contacts, Slack on your Mac for AI. Remote needs Pro or free trial.
Climate and disaster risk for any place or property: flood risk, heat waves, storms and hurricanes, wildfires, earthquakes, sea level rise and 7-day weather risk. Is it safe to go there? Ask about any city, address or coordinates and get this week's weather risk (heat, cold, wind, heavy rain, snow), wildfires, earthquakes, floods and cyclones happening nearby right now, long-term exposure to 2050 and 2080 (flood depth, sea level rise, extreme heat, drought, water stress) and the country's disaster-risk profile and rank among 194 countries. Also compares and ranks countries by risk for ESG and insurance research, and in Claude and other MCP Apps hosts shows an interactive map of the place right in the chat. Every value cites its source: INFORM, ND-GAIN, World Bank, CMIP6, ERA5, IPCC AR6, WRI Aqueduct, GDACS, NASA FIRMS, OpenAQ, ECCC GDPS. Remote, free, no API key, read-only.
The judgment layer for email. Connect Gmail, Outlook, iCloud, Yahoo and IMAP to AI apps in one MCP connection. Nothing sends until you approve it.
Look up Swedish name days by date or name. Find out which names are celebrated today, discover the names associated with any calendar date, or find the name day for a specific name. The service provides Swedish name day information, including name meanings, cultural and historical background, alternative spellings, and name variants.
Daash connects Garmin Connect to ChatGPT and Claude. Your assistant reads your runs, splits, sleep, HRV, Body Battery and recovery, and writes structured workouts and whole training plans to your Garmin calendar, so they're on your watch at the next sync. Free, hosted, open source. Works on free Claude.
Mac & Windows: let ChatGPT, Claude & Cursor use your email, calendar, iMessage, Teams, files.
Ask Drex decision models typed questions about a state and get calibrated probabilities; free within per-network limits.
Gmail, Outlook, Hotmail, iCloud and Fastmail at once: search, read, draft, send and organise mail.
Ask questions about Claude Code, Cursor, Codex and MCP — get answers grounded in their official docs, with citations. A hybrid RAG service that AI agents call through two MCP tools (or over REST). It indexes ~600 pages of official documentation, refreshes itself daily, and every design choice is backed by an experiment.
Your mailboxes in ChatGPT and Claude: Gmail, iCloud, Fastmail, any IMAP. Passwords stay yours.
# **RChilli** RChilli MCP Hub is a production-grade Model Context Protocol (MCP) server that exposes RChilli’s HR data intelligence platform through AI-callable tools. Built on 15+ years of HR data intelligence, RChilli supports ATS vendors, HR technology platforms, staffing agencies, and enterprise recruiting teams worldwide. The tools return consistent, structured JSON responses for recruiting, talent intelligence, skills, matching, compliance, and HR workflow use cases. `userkey` and `subuserid` are injected automatically from the Bearer token and must not be passed manually. <br> --- <br> # **Available Tools** <br> > ### **`analyze_hr_call`** > > Transcribes and analyzes HR or recruiting call recordings to extract speaker turns, sentiment, candidate intent, action items, skill mentions, and structured follow-up data for recruiting operations. <br> > ### **`analyze_skill_adjacency`** > > Identifies related, adjacent, and transferable skills to support skill discovery, talent mobility, workforce planning, and candidate evaluation. <br> > ### **`analyze_skill_gap`** > > Compares candidate or employee skills against a target job and returns present skills, missing skills, readiness score, and development areas for hiring, internal mobility, and workforce planning. <br> > ### **`autocomplete_job_profile`** > > Accepts a partial job title and returns ranked autocomplete suggestions with canonical titles and job families. Ensures job titles map to standardized taxonomy profiles from the moment a recruiter starts typing. <br> > ### **`autocomplete_skill`** > > Accepts a partial skill string and returns ranked autocomplete suggestions with canonical skill names and categories. Helps prevent free-text entry errors and keeps skill data clean. <br> > ### **`classify_job_zone`** > > Reads the job profile from a resume or job description and returns its O*NET Job Zone, from Zone 1 through Zone 5, based on the education, experience, and training preparation required for the role. <br> > ### **`convert_document_format`** > > Accepts a document as base64 or URL and converts between PDF, DOCX, RTF, HTML, and plain text. Useful as a pre-processing step before extracting data from non-standard document formats. <br> > ### **`detect_bias`** > > Reviews job descriptions and hiring criteria for gendered language, age-coded terms, unnecessary credential inflation, cultural exclusion signals, and related compliance risks. Suggests neutral replacements. <br> > ### **`detect_resume_suspicion`** > > Reviews candidate profile data for possible inconsistencies, unusual claims, timeline conflicts, missing context, and other signals that require recruiter review. <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. <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. <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. Supports multilingual extraction, batch processing, resume auto-fill, and reprocessing of historical resumes. <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 Resume Data Extraction. Ideal for resumes stored in cloud storage, S3, email attachments, or other URL-accessible sources. <br> > ### **`find_matches_in_index`** > > Accepts a resume or job description as input and returns the top matching documents from the indexed corpus, ranked by semantic similarity. <br> > ### **`generate_interview_questions`** > > Creates technical, behavioral, situational, and competency-based interview questions tailored to a role and candidate profile, including question type, competency, and expected answer signals. <br> > ### **`generate_jd`** > > Generates structured job descriptions with title, responsibilities, required skills, preferred skills, qualifications, tone alignment, language support, and inclusivity scoring from role inputs. <br> > ### **`geolocate`** > > Converts partial or informal location text into structured city, state, country, ISO codes, latitude, and longitude. Supports radius-based candidate search and workforce planning. <br> > ### **`index_document`** > > Indexes a resume or job description in RChilli Search & Match so it can be searched, matched, updated, and reused across candidate matching, job matching, and similarity-search workflows. <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> > ### **`lookup_skill`** > > Returns authoritative detail for a known skill including description, aliases, related skills, proficiency levels, and O*NET or ESCO mappings. <br> > ### **`map_job_to_skills`** > > Converts job descriptions into granular skill maps with required and preferred skill clusters, proficiency signals, taxonomy tags, and downstream matching attributes. <br> > ### **`match_end_to_end`** > > Orchestrates data extraction, indexing, taxonomy normalization, and matching to return ranked candidates or jobs with scores, explainable results, and an audit trail from a single call. <br> > ### **`normalize_candidate_data`** > > Cleans and normalizes candidate records from multiple ATS or HR systems, resolves field conflicts, deduplicates records, and produces standardized candidate data with a field-level change log. <br> > ### **`normalize_hr_data_with_lov`** > > Maps raw and inconsistent HR data values, including degrees, universities, certifications, job profiles, skills, and locations, to the closest configured List of Values entry with a standardized value and confidence score. <br> > ### **`recommend_learning_path`** > > Builds structured learning paths with prerequisites, skill sequence, certifications, proficiency targets, and LMS alignment based on a person’s profile and target role. <br> > ### **`redact_resume`** > > Redacts configured personally identifiable information from candidate profiles to support anonymized review, bias-aware screening, compliance workflows, and audit logs. <br> > ### **`reformat_resume_with_template`** > > Applies one of the RChilli resume templates, TM001 through TM006, to a structured candidate profile and produces a consistently formatted PDF, DOCX, RTF, or HTML document. <br> > ### **`score_resume_against_jd`** > > Accepts one resume and one job description and returns an overall match score, dimension scores, matched skills, skill gaps, and a natural-language explanation. No index is required. <br> > ### **`screen_application_batch`** > > Evaluates a batch of candidates against job requirements and custom criteria, returning scores, insights, skill gaps, and recommended next actions for each candidate. <br> > ### **`search_indexed_documents`** > > Accepts a query string and returns ranked document references from the tenant’s indexed corpus. Supports Boolean and semantic search modes. <br> > ### **`skill_mapping`** > > Maps raw skill text to standardized RChilli taxonomy skills, aliases, classifications, and related skill information. <br> > ### **`tag_entities`** > > Annotates extracted HR text by wrapping recognized entities in structured XML-style labels. Supported entities include job titles, skills, names, degrees, organizations, locations, countries, dates, and years.
