How to Use the College Scorecard API MCP in Mastra AI

Build complex educational research workflows in Mastra AI using verified institutional data.

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Connect College Scorecard API MCP to Mastra AI

Create your Vinkius account to connect College Scorecard API 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 College Scorecard API with Mastra AI

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Automated Research in Mastra AI

Hook `search_colleges` into your agent workflow to automate data collection. If a search fails or returns an empty set, Mastra AI can trigger a retry or flag the agent for a different query. This setup allows you to chain tools. Your agent performs the search, then immediately pipes the ID into `get_college_details` to pull the full profile for your report.

State-Based Analysis for Mastra AI

Deploy `list_colleges_by_state` within your agent's logic to handle high-volume data tasks. The server handles the pagination, and your workflow processes the resulting list in batches. Each step in your Mastra AI pipeline remains traceable. You can see exactly which tool was called and what data returned, making debugging your research bot trivial.

Mastra AI Workflow Integration

Use `get_fields_of_study` to build conditional branches in your agent. If a school offers a specific program, the workflow continues; otherwise, the agent skips to the next university. This MCP Server provides the structured output your Mastra AI agents require to make decisions. You define the success criteria, and the server provides the raw facts to satisfy them.

Setup guide

Set up College Scorecard API 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 College Scorecard API 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: "college-scorecard-api-mcp-client",
  servers: {
    "college-scorecard-api-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

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

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Common questions about College Scorecard API MCP in Mastra AI

You add the server URL to your agent configuration. Mastra AI detects the available tools, allowing you to call them inside your workflow definitions.

Definitely. You can chain these tools together to build a research pipeline that starts with a broad search and ends with granular data extraction.

It integrates with the framework's native retry logic. If a network blip occurs, your agent can automatically re-attempt the call to get the school data.

You get access to official federal records including completion rates, average tuition costs, and specific academic program listings for thousands of institutions.

The server operates in a secure, isolated sandbox. It only touches non-sensitive, public-domain school statistics, ensuring your proprietary agent logic remains isolated from the data layer.

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