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"Finding LinkedIn users by educational background" matching MCP connectors:

Matching Connector Tools:

  • Ask Lever the messy recruiting-ops questions dashboards miss by connecting opportunities, applications, stages, notes, feedback, interviews, referrals, postings, requisitions, offers, users, sources, tags, files, resumes, and archive reasons. Find referral SLA misses, stale opportunities by owner, feedback debt by interviewer and hiring team, funnel leakage by recruiter/source/team, requisition fill-risk, offer hygiene gaps, archive-reason drift, and bottleneck owners. No dashboard build. No SQL

  • Lists a company's filed documents at JUCESP by NIRE. Platform-hosted, no credentials, pay per query

  • Read-only MCP server for HolyDB: find Catholic parish Mass times by location and time.

  • Public-registry routing map by entity kind. Read-only reference data, not a determination.

  • MCP server exposing supplements database used by iNutriPlan.com

  • EU-native PaaS for AI agents — deploy web apps with one sentence, managed Postgres, GDPR by default.

  • Access comprehensive company data including financial records, ownership structures, and contact information. Search for businesses using domains, registration numbers, or LinkedIn profiles to streamline due diligence and lead generation. Retrieve historical financial performance and complex corporate group structures to support informed business analysis.

  • The HubSpot MCP Server acts as a bridge that enables AI assistants and Large Language Models to securely interact with HubSpot CRM data through natural conversation, without requiring users to understand complex API structures. It provides read-only access to standard CRM objects (contacts, companies, deals, tickets, products, invoices, and more) and their associations, secured via OAuth 2.0, allowing AI agents to perform tasks like summarizing deals, fetching company updates, and looking up record changes.

  • The Ramp MCP server enables users to securely connect Ramp with AI assistants like ChatGPT and Claude to query financial data and take actions using natural language. It transforms Ramp's developer API into a SQL interface that LLMs can query, allowing admins to analyze spend trends, identify cost savings, and run complex SQL analyses on comprehensive datasets (transactions, purchase orders, vendors, users), while all users can manage cards, view transactions, request reimbursements, and get expense policy answers.