How to Use the CrossRef MCP in AutoGen

Q: How do I register CrossRef tools with my AutoGen agents?

Install autogen-extmcp via pip. Use mcpservertools with your Vinkius endpoint to fetch the tools, then pass that list directly to your AssistantAgent constructor.

Deploy AutoGen agents that debate source credibility and verify DOIs using live data from the world's largest registry.

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Connect CrossRef MCP to AutoGen

Create your Vinkius account to connect CrossRef 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 CrossRef with AutoGen

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Verify paper credentials using DOIs in AutoGen

The `get_crossref_doi` tool retrieves verified metadata for any digital object identifier. It delivers titles, authors, and citation counts directly to your agent conversation. This structured data helps your debating agents verify claims. If one agent cites a paper, another agent can run the DOI through this tool to confirm the publication year and citation weight before accepting the argument.

Let AutoGen agents search 140M scholarly works

The `search_crossref` tool queries the massive CrossRef registry to find relevant scholarly papers. It returns DOIs and full bibliographic records to help your agents build consensus on academic topics. Your research agent can query the database, while a critic agent reviews the citation counts. This multi-agent debate ensures your system only relies on highly-cited, peer-reviewed literature.

Map academic profiles using this MCP Server

The `search_crossref_author` tool finds publications associated with a specific researcher. It returns their full bibliography sorted by relevance alongside citation counts to help you profile academic output. AutoGen agents can split this work. One agent retrieves the author's papers, while another analyzes the publication trends and citation counts to draft a detailed academic profile.

Setup guide

Set up CrossRef 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 CrossRef 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="CrossRef_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

Get your connection token →

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="CrossRef_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent CrossRef 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 CrossRef. 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.

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Live

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

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Common questions about CrossRef MCP in AutoGen

Install autogen-ext[mcp] via pip. Use mcp_server_tools with your Vinkius endpoint to fetch the tools, then pass that list directly to your AssistantAgent constructor.

Yes, they can. Since the MCP server is hosted on Vinkius, multiple agents in your conversation framework can call the tools concurrently to fetch metadata or search authors.

The MCP Tool Adapter handles schema conversion automatically. It maps the server's tool definitions directly into the format that your agents expect.

No. Vinkius manages the connection and handles the backend API limits, so your agents can focus on running searches and retrieving DOIs.

Vinkius executes all tool calls in an ephemeral V8 sandbox. Your DOIs and author search terms are processed in memory and immediately destroyed once the tool execution completes.

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