"sage active" matching MCP servers:

Enables personal trainers to query and summarize client management data—active clients, workouts, physical assessments, retention, check-ins, feedback, and finances—through MCP-compatible AI clients in read-only mode.

Transforms job postings into qualified sales leads by searching for active jobs, enriching company data, and identifying decision-maker contact information.

Finds active podcasts covering a given topic for guest booking or sponsorship, returning each show's published contact route, evidence episodes, and your prior outreach history so you don't pitch the same show twice.

Enables AI assistants to interact with HubSpot CRM data, including creating contacts and companies, retrieving active records and recent conversations, and performing semantic search over previously retrieved HubSpot data through built-in vector storage and caching.

Enables AI assistants to interact with HubSpot CRM data for creating contacts and companies, retrieving company activity, active contacts and companies, recent conversations, and performing semantic search across previously retrieved data with built-in vector storage and caching.

Enables AI assistants to interact with HubSpot CRM data, creating contacts and companies with duplicate prevention, retrieving company activity, active contacts and companies, and recent conversation threads. Built-in FAISS vector storage, thread-level indexing, and embedding caching provide semantic search over previously retrieved data to overcome HubSpot API limits and improve response times.

Enables AI assistants to read and write HubSpot CRM data, including creating contacts and companies with duplicate prevention, retrieving active records, company activity, and recent conversations. Built-in vector storage and caching add semantic search across previously retrieved data while working around HubSpot API limitations.

Enables AI assistants to interact directly with HubSpot CRM data, creating contacts and companies, retrieving company activity, active contacts/companies, and recent conversation threads, and running semantic searches over previously retrieved data. Built-in vector storage and caching overcome HubSpot API limitations while improving response times.