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Match Startup Founders to Mentors Using MCP.

Mentor expertise mapped, startup needs matched, introductions sent , connect each cohort company with the right advisor in minutes, not weeks

Explore All MCP Servers

Works with every AI agent you already use

…and any MCP-compatible client

Match Startup Founders to Mentors Using MCP MCP on Cursor AI Code Editor MCP Client Match Startup Founders to Mentors Using MCP MCP on Claude Desktop App MCP Integration Match Startup Founders to Mentors Using MCP MCP on OpenAI Agents SDK MCP Compatible Match Startup Founders to Mentors Using MCP MCP on Visual Studio Code MCP Extension Client Match Startup Founders to Mentors Using MCP MCP on GitHub Copilot AI Agent MCP Integration Match Startup Founders to Mentors Using MCP MCP on Google Gemini AI MCP Integration Match Startup Founders to Mentors Using MCP MCP on Lovable AI Development MCP Client Match Startup Founders to Mentors Using MCP MCP on Mistral AI Agents MCP Compatible Match Startup Founders to Mentors Using MCP MCP on Amazon AWS Bedrock MCP Support
Watch how your AI agent handles real conversations using this recipe.

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AI Agent
Claude Claude
ChatGPT ChatGPT
Cursor Cursor
Gemini Gemini
Windsurf Windsurf
VS Code VS Code
JetBrains JetBrains
Vercel Vercel

How It Works

Your batch starts next week. 30 startups, each with different needs. Startup A (fintech) needs help with bank partnerships and compliance.

Startup B (healthtech) needs help with FDA pre-submission and clinical trial design. Startup C (SaaS) needs help with enterprise sales and pricing strategy.

Your AI agent enriches your 200-mentor database through Apollo: who works where, what industry, what function, what seniority. It categorizes each mentor: Finance/Compliance (28 mentors).

Healthcare/Biotech (22 mentors). Enterprise Sales (35 mentors). Product/Engineering (40 mentors). Marketing/Growth (32 mentors). Legal/IP (18 mentors). Operations/Fundraising (25 mentors). Then it matches: Startup A (fintech, needs compliance) matched to 3 mentors: a former Chief Compliance Officer at a mid-tier bank, a fintech regulatory consultant, and a payments attorney.

Startup B (healthtech, needs FDA guidance) matched to 3 mentors: a former FDA reviewer, a clinical trial manager, and a digital health founder who navigated 510(k) approval.

The agent creates the matching records in Airtable: 30 startups 3 mentors each = 90 mentor-startup pairs. Each pair includes: why this match was made, suggested meeting topics, and recommended session format (30-minute video call, office hours, or workshop).

Then Brevo sends the introductions: 'Hi Dr. Sarah , Meet CompanyB, a healthtech startup in our current batch building remote patient monitoring.

They are preparing for FDA pre-submission and would benefit from your experience at MedDevice Corp. Would you be available for a 30-minute call next week? Here is the founder's LinkedIn: [link].' The mentor gets a relevant, respectful introduction.

The founder gets an expert. The program director did not write 90 emails.

MCP Server Orchestration: 3 MCP Servers, one intelligent agent

Connect Apollo, Airtable and Brevo MCP servers so your AI agent maps your mentor network's expertise through Apollo (industry experience, functional skills, current company, seniority), organizes mentors and startups in an Airtable matching database, and sends personalized match introduction emails through Brevo. You have 200 mentors in your network. You have 30 startups in the current batch. Each startup needs 2-3 mentors matched to their sector, stage, and specific challenge , a fintech startup struggling with compliance needs a mentor who has been a compliance officer at a bank, not a growth marketer. Doing this manually takes your program director 2-3 weeks of emails, spreadsheets, and phone calls. The agent matches expertise to needs in minutes and sends the introductions automatically.

Run This Automation Today

Connect Claude, ChatGPT, Cursor, or any AI agent to the Vinkius catalog and run this automation in minutes.

Build Your Own MCP

Turn any internal API into an MCP server. Import a spec, define Agent Skills, or deploy with MCPFusion.

  • Import from OpenAPI, Swagger, or YAML specs
  • Create Agent Skills with progressive disclosure
  • Deploy to edge with MCPFusion framework
  • Built in DLP, auth, and compliance on every call
  • Real time usage dashboard and cost metering
  • Publish to catalog or keep private
Start building

Connect & Automate

The 3 servers this recipe uses are ready in the catalog. Connect them once, paste a prompt, and your AI runs the full workflow.

  • Apolloio, Airtable & Brevo ready in the catalog right now
  • Add more from 4,700+ servers whenever you need
  • Every connection is secured and compliant automatically
  • Track usage and costs across all your servers
  • Works with Claude, ChatGPT, Cursor, and more
  • New servers and recipes added every week

Superpowers you didn't know your AI had

The Vinkius catalog gives your agent access to 4,700+ MCP servers and the intelligence to combine them. Imagine never logging into another dashboard. Your AI handles the work across every tool, in one conversation. That's what this infrastructure was built for.

Superpower 01

Cross-Platform Intelligence

Your agent doesn't just connect to tools. It understands the relationships between them. Data flows where it needs to go, automatically, with full context preserved across every platform.

Superpower 02

Contextual Reasoning

Every decision your agent makes considers the full picture. It reads CRM data, checks calendars, reviews conversation history, and acts on everything at once. Not step by step. All at once.

Superpower 03

Productivity at Scale

What used to take 45 minutes across five different dashboards now takes one sentence. Your agent runs the entire workflow end to end while you focus on decisions that actually matter.

Superpower 04

Zero-Config Reliability

No API keys to paste. No webhooks to configure. No YAML to debug. Connect your MCP servers once, and your agent handles the rest. Every time, without intervention.

Made for exactly this

Your AI agent taps into the entire Vinkius MCP catalog to handle these for you. You describe what you need. It does the rest.

Accelerator program managers onboarding a new cohort who need to match 30 startups with 200+ mentors by sector, function and specific challenge within the first week

Accelerator operations teams managing mentor relationships who need to track engagement, availability and effectiveness across multiple batches

Corporate accelerators with internal subject-matter experts who need to match startup needs with employee expertise for structured mentoring sessions

University incubators with faculty and alumni mentors who need an organized system to deploy academic expertise to student-founded startups

Frequently Asked Questions About This MCP Server Orchestration

Which MCP servers do I need for this workflow?

Three: Apollo, Airtable and Brevo. Connect all three to your AI client before running any prompt from this page.

Does this work with Claude Desktop, Cursor or Windsurf?

Yes. Any AI client that supports the Model Context Protocol works , Claude Desktop, Cursor, Windsurf, Cline and others. Connect the MCP servers and paste a prompt.

Can mentors decline a match?

Yes. The introduction email is an invitation, not a commitment. Mentors can decline or suggest a different time. The Airtable record tracks acceptances and declines to improve future matching.

How does the matching logic work?

The agent matches by sector first (fintech mentor to fintech startup), then by function (compliance expert to compliance challenge), then by seniority (senior operators to complex problems, junior experts to tactical questions). You can customize the matching criteria in your prompt.

Can I reuse this across batches?

Yes. The mentor database in Airtable persists. Each new batch adds new startup records and new matches. Over time, you see which mentors are most engaged and which matching patterns produce the best sessions.

Is mentor contact data private?

Apollo provides professional business data. Your mentors are existing network contacts who have opted into your program. The Brevo emails come from your accelerator's domain. Vinkius does not store mentor contact lists.

MCP servers used in this workflow

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Claude Claude
ChatGPT ChatGPT
Cursor Cursor
Gemini Gemini
Windsurf Windsurf
VS Code VS Code
JetBrains JetBrains
Vercel Vercel
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