"Using iCalendar on macOS" matching MCP servers:

Local MCP server for macOS Messages + Contacts: send messages, read chat history, wait for replies, and manage Contacts.app entries.

Enables AI agents to perform CRM operations like creating contacts, managing deals, and updating leads through natural language using the Model Context Protocol.

MCP server for the Mamba Labs People Finder & Email Verifier actor on Apify. Give it a company domain, name or LinkedIn URL and it returns the people at that company who match your role, seniority and department filters, each as a structured contact record with an optional verified business email.

Enables checking CRM contacts to learn their current employer, title, start month, role history, and whether they left, landed elsewhere, or were promoted, returning one flat row per person with match method, source, and source age. It accepts single contacts or bulk lists, works with your own search, enrichment, and email-verification keys, and runs on Apify.

Find prospects, verify their emails, spot buying signals, draft grounded outreach and stage campaigns, all from a conversation with your AI assistant, using your own API keys.

AI-powered lead qualification engine. Ingest leads from any source, auto-enrich with company data, score 0-100 using weighted AI rules, and export to HubSpot, Pipedrive, Google Sheets, CSV, or JSON. 8 MCP tools + 3 resources.

MCP server for B2B lead generation and company search using the Generect Live API. Provides tools to search leads, companies, generate emails, and get lead by URL.

Enables AI assistants to identify and quantify value leaks in organizations using Melt's methodology, providing structured estimates instead of generic vendor lists.

Enables research on prospects, pull call transcripts, and enrich leads using Gong, ZoomInfo, Clay, and LinkedIn Sales Navigator through natural language.

Enables an AI client to track a watch list of contacts and retrieve only what changed since the last run — departures, new employers, replacements, and new hires after a role closed — each row carrying match evidence, source dates, and ready-to-use outreach payloads. It runs the analysis on Apify using the caller's own provider keys, supports stored or caller-held state, and can push results to a signed webhook.

Scores companies against a configurable Ideal Customer Profile using firmographic and signal data. Returns a weighted fit score with per-criterion breakdowns.

Demo MCP server for booking confirmed sales appointments through Claude. Allows users to request appointments, check status, and get detailed BANT briefings using natural language, with realistic fake data for demonstration.

MCP server for Zammad that focuses on workflows the standard Zammad API tooling does not cover well — primarily shared drafts with strict reply-HTML validation, fresh signature rendering and German-localised quote blocks.

Enables AI assistants to query Bullhorn CRM data using natural language through direct REST API access with OAuth 2.0 authentication.

Create and manage quizzes, question banks, and translations; capture and manage leads, respondents, and bookings; and pull stats and funnel analytics on RooQuiz — a lightweight assessment platform for lead capture and viral sharing.

Enables managing Kaspi Marketplace orders through AI assistants, including listing, accepting, completing, and canceling orders, with real-time operations directly on production data (no sandbox).

Enables LLMs to search and retrieve Autotask tickets, companies, and contacts using advanced semantic search and AI-powered reranking.

Connects AI assistants to the Lanten property management API, allowing them to manage tenants, units, and work orders using natural language.

Resolves messy company, customer, and vendor names across CRM, ERP, and ITSM systems to canonical records using fuzzy matching, preventing AI agents from updating or creating wrong or duplicate records.

Manage Job using MCP: Manage Job, Candidates, Resumes, Salaries all within this one MCP tools It can solve problems like: You have 50 resumes to screen. Your AI assistant can reason about candidates, but it can't: Read PDFs/DOCX — The AI can't open binary files Extract structured data — Copy-pasting loses formatting, metrics, and context Compare at scale — No consistent scoring across candida