How to Use the Mattermark MCP in Mastra AI

Q: How do I register Mattermark tools within a Mastra AI MCP setup?

Instantiate the MCP client with the server URL, then call mcpClient.listTools() to retrieve the available endpoints. Spread those tools directly into your Mastra agent configuration to give it instant access to startup data.

Q: Can Mastra AI handle complex branching logic using Mattermark data?

Yes, you can build workflows that check getcompanyemployees and branch conditionally based on headcount. For example, if employee growth exceeds twenty percent, your agent can automatically trigger a news search with getcompanynews.

Q: Does this setup support human-in-the-loop for deal sourcing?

Yes, you can use the requireToolApproval option in Mastra. This forces the agent to pause and ask for confirmation before executing tools like searching for sensitive funding rounds.

Run automated VC workflows and check startup signals using Mastra AI agents equipped with live company data.

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Connect Mattermark MCP to Mastra AI

Create your Vinkius account to connect Mattermark to Mastra AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Mattermark with Mastra AI

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Automated Target Sourcing

`search_companies` scans the market for startups matching your specific growth criteria. Your Mastra workflow then takes those results and triggers `get_company_details` to filter out companies that don't fit your investment thesis. Because Mastra handles conditional branching, you can set rules like stopping the workflow if a company has too few employees. This lets your agent build clean prospect lists without manual supervision.

Deals Sourcing with Mastra AI and MCP

`search_funding_rounds` identifies recent investment events based on target round sizes. The Mastra agent automatically branches based on round type, calling `get_funding_round_details` for Series A or skipping to seed rounds depending on your criteria. If a check fails, Mastra's built-in retry logic kicks in with exponential backoff. Your data collection keeps running even if the target API experiences temporary downtime.

Deep Investor Profiling via MCP Server

`list_investors` pulls active venture funds while `get_investor_details` extracts their historical portfolio focus and co-investors. Your agent uses this data to map out competitive syndicates and find the right lead partners for a deal. You can configure the workflow to require human approval before sending a compiled investor profile to your team. Mastra's human-in-the-loop feature pauses the agent until you review the output.

Setup guide

Set up Mattermark MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All Mattermark tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "mattermark-mcp-client",
  servers: {
    "mattermark-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "Mattermark Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to Mattermark tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent Mattermark transactions"
);
console.log(result.text);

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Mattermark. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Mattermark MCP in Mastra AI

Instantiate the MCP client with the server URL, then call `mcpClient.listTools()` to retrieve the available endpoints. Spread those tools directly into your Mastra agent configuration to give it instant access to startup data.

Yes, you can build workflows that check `get_company_employees` and branch conditionally based on headcount. For example, if employee growth exceeds twenty percent, your agent can automatically trigger a news search with `get_company_news`.

Mastra has built-in exponential backoff and retry mechanisms. If `get_investor_details` hits a rate limit or a network hiccup, the framework pauses and retries the call automatically before failing the workflow.

Yes, you can use the `requireToolApproval` option in Mastra. This forces the agent to pause and ask for confirmation before executing tools like searching for sensitive funding rounds.

Absolutely. All search queries and VC data requests are routed through zero-trust MCP sandboxes that do not persist your search queries or target lists.

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