How to Use the CrossRef MCP in Google ADK

Q: Does Google ADK support filtering the CrossRef tools?

You can restrict tool access using the optional toolnames filter in the setup. This lets you expose only the author lookup or DOI resolver to specific agents in your workflow.

Connect Gemini agents to 140M+ academic papers using Google ADK and massive context windows.

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Connect CrossRef MCP to Google ADK

Create your Vinkius account to connect CrossRef to Google ADK 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 Google ADK

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Extract full metadata via the CrossRef MCP Server

The `get_crossref_doi` tool retrieves the exact title, authors, journal, year, and abstract for any registered digital object identifier. Your agent passes a DOI string and receives structured bibliographic data in return. Gemini models can process 1M+ tokens, which changes how you handle academic metadata. Your Google ADK agent can resolve hundreds of DOIs in a single pass and cross-reference them against internal datasets stored in BigQuery.

Query the global DOI registry from Google Cloud

Activating the `search_crossref` tool gives your agent direct access to 140M+ scholarly works. The response packs in citation counts, DOIs, and core publication details across every scientific discipline. Enterprise agents running on Google Cloud need factual grounding. By routing these search results through Vertex AI, your system builds literature reviews using verified academic data instead of relying on base model weights.

Track researcher output and citation counts

The `search_crossref_author` tool finds publications by specific researchers and sorts them by relevance. Your agent sees exactly how many times each paper has been cited. You configure this by passing the McpToolset to your LlmAgent setup. You can even use the tool_names filter to restrict your agent so it only performs author lookups, keeping its focus narrow and predictable.

Setup guide

Set up CrossRef MCP in Google ADK

Prerequisites

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

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with CrossRef tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="CrossRef_agent",
    model="gemini-2.0-flash",
    instruction="You have access to CrossRef tools via MCP.",
    tools=mcp_tools,
)

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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 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.

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Common questions about CrossRef MCP in Google ADK

Install the google-adk package. Set up an McpToolset using StreamableHttpServerParameters with your Vinkius URL, then pass it as tools=[mcp_toolset] when initializing your LlmAgent.

Yes. Because Gemini supports massive context windows, your agent can pull hundreds of abstracts via DOI lookups and analyze them simultaneously without dropping details.

You can restrict tool access using the optional tool_names filter in the setup. This lets you expose only the author lookup or DOI resolver to specific agents in your workflow.

The search results include the DOI, title, publication year, author list, and citation count. This provides enough context for your agent to decide if it needs to pull the full abstract.

No. The Vinkius platform handles your bibliographic searches and author lookups inside an isolated, stateless MCP Server environment. Your specific research queries are never persisted or used to train external models.

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