How to Use the College Scorecard API MCP in AutoGen

Let AutoGen agents debate and converge on facts using the College Scorecard API.

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Connect College Scorecard API MCP to AutoGen

Create your Vinkius account to connect College Scorecard API to AutoGen 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 AutoGen

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Multi-agent debate on College Scorecard API data

Assign one agent to `search_colleges` and another to verify costs. They debate the findings until they reach a consensus on the best school choice. This prevents single-point errors. The agents challenge each other's interpretation of the API results before giving you an answer.

Negotiate school metrics with AutoGen

Use `get_college_details` to feed your agents specific performance data. A security agent can flag high-cost schools while a performance agent argues for value. They negotiate based on the actual tool output. You get a decision that accounts for multiple perspectives on school quality.

Coordinate school searches in AutoGen

The agents use `list_colleges_by_city` to narrow down the options. They work together to filter the list based on your specific criteria. This MCP server acts as the source of truth for the entire conversation. The agents call these tools as needed to resolve conflicts in their reasoning.

Setup guide

Set up College Scorecard API MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes College Scorecard API tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

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

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="College Scorecard API_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent College Scorecard API data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

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

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="College Scorecard API_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent College Scorecard API data")
    print(result.messages[-1].content)

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.

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Common questions about College Scorecard API MCP in AutoGen

The MCP adapter converts the API schema into tools your agents can call. They discuss the tool results during their turn-based conversation.

They absolutely can. That is the point of the framework, as agents debate the data to ensure the final conclusion is solid.

The server uses a zero-trust sandbox. We only expose the specific school datasets required for your agents to perform their assigned tasks.

You pass the tool list directly into the agent constructor. You can restrict specific agents to specific tools to maintain system boundaries.

It supports both stdio and Streamable HTTP transports. You choose the connection type that fits your agent architecture best.

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