How to Use the College Scorecard API MCP in CrewAI

Deploy specialized agents in CrewAI to audit university data and tuition costs automatically.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect College Scorecard API MCP to CrewAI

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

GDPR Free for Subscribers

Setup College Scorecard API with CrewAI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

CrewAI Agents and College Scorecard API

Assign a researcher agent the `search_colleges` and `list_colleges_by_zip` tools. While the researcher agent finds the candidates, your analysis agent waits to process the results. This MCP Server fits right into your crew. You define the agent's role, grant it access to the tools, and let the agents collaborate to find the best school matches based on your criteria.

Granular Data Access for CrewAI

Use `get_college_details` to give your agents deep context on specific schools. Your agents don't guess; they look up the exact cost and performance metrics before writing their summaries. This works perfectly for hierarchical teams. A lead agent identifies the target school, then delegates the detail-gathering task to a specialized agent using the server tools.

Program Audits with CrewAI

Leverage `get_fields_of_study` to let your agents audit program offerings across the country. Your CrewAI agents can compare degree requirements and availability without human oversight. Everything is handled through secure transport. Each tool call is logged by the framework, providing a clear trail of how your agents arrived at their conclusions.

Setup guide

Set up College Scorecard API MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke College Scorecard API tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="College Scorecard API Analyst",
    goal="Access and analyze College Scorecard API data via MCP.",
    backstory="Expert analyst with direct College Scorecard API access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent College Scorecard API transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="College Scorecard API Analyst",
        goal="Access and analyze College Scorecard API data via MCP.",
        backstory="Expert analyst with direct College Scorecard API access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent College Scorecard API transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by College Scorecard. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect College Scorecard API now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about College Scorecard API MCP in CrewAI

You pass the server URL directly into the agent definition. Once connected, your CrewAI agents can trigger any of the six tools as part of their assigned tasks.

They can. Because of the framework's shared memory, once an agent fetches data about a university, the other agents in the crew can reference that information.

It does. You can set up your agents to search, filter, and report on school data on a schedule, with the server providing the necessary inputs for every step.

The server provides access to federal data points such as institutional ID, city, state, zip code, available fields of study, and school performance indicators.

Yes. The server is ephemeral and runs in an isolated sandbox. It only handles public university datasets, keeping your internal agent infrastructure completely separate from external systems.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript