How to Build an MCP Server for Investors: A Step-by-Step Guide (w or w/o Coding ;))

Connecting the Dots: Why an MCP Server Might Be the Most Valuable Tech Investment You Make This Year

👋 Hi, I’m Andre and welcome to my newsletter Data-Driven VC which is all about becoming a better investor with Data & AI. Join 33,930 thought leaders from VCs like a16z, Accel, Index, Sequoia, and more to understand how startup investing becomes more data-driven, why it matters, and what it means for you.

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Why Investors Need Their Own MCP Server

In today’s data-rich but insight-poor venture landscape, investors are drowning in information—pitch decks, startup news, founder tweets, CRM entries, and more. Yet despite this data overload, most investors still rely on intuition and gossip over hard evidence. Why? Because data is meaningless unless it's captured, organized, and intelligently queried.

Enter the MCP Server—short for Memory, Context, and Persona server. Inspired by how ChatGPT and other LLMs organize their internal workflows, an MCP server acts as a centralized brain for VCs: a persistent memory layer storing everything that matters, a contextual engine for understanding relationships, and a persona hub that tailors insights to your own investment thesis and decision-making style. Think of MCP like a USB-C port for AI applications.

Just as CRMs became essential for sales teams and ERPs revolutionized manufacturing, I believe MCP servers will soon become indispensable for modern investors.

Let me show you why—and exactly how to build your own, with or without coding skills ;)

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💡What Is an MCP Server?

An MCP Server is a modular software backend that integrates:

1. Memory — Persistent structured and unstructured data on startups, people, theses, markets, etc.

2. Context — Dynamic linking of entities (e.g., who introduced this founder, when you met them, how they compare to others).

3. Persona — A tailored overlay that understands your investment lens, sector preferences, writing style, and workflows.

Put simply, the MCP server allows you to feed in noisy real-world data (emails, PDFs, scraped bios, decks, call notes etc.), and ask high-quality, highly personalized questions like:

• “Remind me who introduced me to the founder of Company X and when we last spoke?”

• “Which companies in our CRM are similar to this one?”

• “Summarize our investment thesis in bio-based carbon capture in less than 200 words.”

It acts like an always-on chief-of-staff, analyst, and memory extension—available 24/7, and only getting smarter over time. Tell me you don’t want this too? ;)

📈Use Cases for VC Investors

Here are some exemplary VC workflows where an MCP Server shines:

1. Sourcing and Scouting

• Parse all inbound emails and automatically extract startup names, sectors, stage, traction, and team.

• Cross-reference with your CRM or Notion stack to flag if you've seen this before.

• Auto-tag warm vs cold intros and route to appropriate internal investors.

2. Due Diligence and Benchmarking

• Compare a startup’s metrics to internal portfolio data or market benchmarks.

• Ask your MCP server, “How does this company’s growth compare to others at similar stage in AI Infrastructure?”

• Generate custom DD checklists based on sector, stage, and geography.

3. Founder Interactions

• Summarize past interactions with a founder before a call.

• Maintain founder-specific preferences: preferred communication style, fundraising pace, key motivators.

• Recommend next steps or intros based on context.

4. Internal Investment Committees

• Pull up relevant IC memos, thesis notes, or past deals in a similar category.

• Automate early-stage memo drafts that incorporate internal language and structure.

5. Content and Thought Leadership

• Turn internal notes or interviews into high-quality blog posts or social content.

• Maintain consistency of tone and style that aligns with your personal or firm-level brand.

In short, an MCP Server becomes the connective tissue of your VC operation—across sourcing, diligence, communication, and content.

🛠️How to Build Your Own MCP Server: Step-by-Step

Today, I’d like to share two paths. One more complex yet more flexible and powerful, and one off-the-shelf.

Path #1: Complex & Powerful

Step 1: Define Your MVP Scope

Before building, align on what you actually want your MCP Server to do in v1. Choose a few core workflows. A good starter list:

• Parse and remember all interactions with founders

• Answer context-rich queries about startups or sectors

• Generate IC memo drafts based on structured + unstructured data

Start with useful over complete. You’re not replacing your CRM or knowledge base—yet.

Step 2: Set Up Your Memory Layer (Vector DB)

You'll need a vector database to store embeddings of your documents and data. Good open-source or commercial options include:

• Pinecone

• Weaviate

• Qdrant

• Chroma (lightweight, Python-native)

This memory layer is where all documents—decks, PDFs, call notes, CRM entries—are chunked, embedded via a model like OpenAI or Cohere, and stored for retrieval.

Structure it with metadata like: founder_name, company, doc_type, date, source

This enables filtering later on ("Only show me DD notes from 2024 for European companies").

Step 3: Add Contextual Reasoning

Now plug in a retrieval-augmented generation (RAG) pipeline:

1. Input query from the user.

2. Convert to embedding.

3. Search the vector DB for semantically similar docs.

4. Inject top results as context into the prompt for your LLM.

Use LangChain, LlamaIndex, or Haystack to orchestrate this RAG pipeline. Optionally enrich with knowledge graphs to enhance relationships (e.g., linking companies to founders to past investment themes).

This is where the magic happens: your MCP server can now answer queries not from static rules, but from your actual data.

Step 4: Personalize with a VC “Persona”

Use custom prompt templates that reflect:

• Your preferred tone (casual vs formal)

• Your investment thesis (e.g., “Pre-seed European B2B SaaS”)

• Your workflow structure (e.g., how you write memos, evaluate TAM, etc.)

Step 5: Add Interfaces

Make it usable. Some options:

• Chat interface: Use Streamlit or a custom React front-end

• Slack bot: Ask questions like “/mcp latest update from Company X?”

• Gmail plugin: Parse inbound and auto-summarize

• Notion/CRM sync: Pipe data in or out of existing tools

The goal is to meet the user where they already work—so they don’t need to switch context to use the MCP server.

Step 6: Automate Ingestion

You want your MCP to stay updated automatically:

• Connect Zapier or n8n to auto-fetch new emails, Google Docs, CRM entries.

• Use scraping bots or APIs to pull public data (e.g., LinkedIn, Crunchbase).

• Set up cron jobs or webhooks to regularly ingest, chunk, and embed new info.

This ensures your MCP server doesn’t become yet another stale knowledge base.

Step 7: Layer in Memory Management

Over time, your MCP server can learn:

• What information you tend to ask for

• How you phrase certain questions

• Which documents you often reference together

With a bit of fine-tuning and prompt engineering, your system can preemptively surface helpful info—before you even ask.

Path #2: Easy & Off-the-Shelf

Now that you’ve understood the required steps above, I’m happy to share a simple yet powerful off-the-shelf solution: Claude MCP Server meets Zapier. Here’s a step-by-step guide that you can easily adapt to your investment workflows, as described above. Please note that Google Workspace integrations require the Pro plan and any other integrations require the Max plan.

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🚀 The Future of MCPs in VC

I hope that this post serves as inspiration for you to get your hands dirty and quickly recognize how powerful MCPs servers are.

Today, they are experimental side projects for the data-forward few. But tomorrow, they will be standard infrastructure. I’m convinced that we’ll look back at VCs flipping between Notion, Google Docs, and email threads the same way we now view salespeople working from spreadsheets before Salesforce.

In the end, the best VCs of the future won’t just have better networks or instincts—they’ll have better memory, better context, and better systems. MCP Servers offer all three and now you can build your own. Enjoy!

Stay driven,
Andre

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