How to Use the OverDrive Library API MCP in Google ADK

Q: How do I restrict which OverDrive Library API tools my Google ADK agent can access?

Use the toolnames filter when instantiating your McpToolset. For example, you can limit the agent to only getlibraryproductdetails if you want to prevent catalog-wide searches.

Q: How do I initialize the OverDrive Library API MCP Server in Google ADK?

Pass the server's HTTP endpoint to StreamableHttpServerParameters and wrap it in an McpToolset. Then, add that toolset to your LlmAgent constructor.

Connect Gemini to the OverDrive Library API to search catalogs and audit book metadata within your Google ADK pipelines.

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Connect OverDrive Library API MCP to Google ADK

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Setup OverDrive Library API with Google ADK

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Analyze Huge Catalogs with Google ADK

The `list_library_collections` tool pulls every digital media collection linked to your account. In a Google ADK pipeline, you can feed these collection IDs into Gemini's massive context window to map out inventory trends across hundreds of branches using this MCP Server. This setup lets you run deep catalog analysis without pagination limits. Your agent can cross-reference the output with your existing BigQuery data to find gaps in your digital library.

Run High-Volume Searches via Google ADK

The `search_library_collection` tool queries the public catalog for specific titles, formats, and authors. Your Google ADK agent can execute these searches across multiple parameters and compile the results directly into Vertex AI datasets. Because the Google ADK framework handles complex reasoning, your agent can translate vague user requests into precise OverDrive search queries. It then uses the tool to pull matching books instantly.

Audit Book Availability and Metadata

The `get_library_product_details` tool gets complete metadata and live availability for specific library items. This allows your Google ADK agent to check if a book is available for immediate checkout or if there is a waitlist. You can restrict your Google ADK agent's access to only this tool using the `tool_names` filter in your MCP toolset configuration. This keeps your enterprise agent focused on inventory auditing without exposing unnecessary search endpoints.

Setup guide

Set up OverDrive Library API 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 OverDrive Library API 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="OverDrive Library API_agent",
    model="gemini-2.0-flash",
    instruction="You have access to OverDrive Library API tools via MCP.",
    tools=mcp_tools,
)

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Common questions about OverDrive Library API MCP in Google ADK

Use the `tool_names` filter when instantiating your `McpToolset`. For example, you can limit the agent to only `get_library_product_details` if you want to prevent catalog-wide searches.

Yes. You can configure your Google ADK agent to search the catalog using `search_library_collection` and write the returned book metadata directly into a BigQuery table.

Pass the server's HTTP endpoint to `StreamableHttpServerParameters` and wrap it in an `McpToolset`. Then, add that toolset to your `LlmAgent` constructor.

Gemini's long-context window easily processes the detailed JSON metadata returned by `get_library_product_details`. The agent can analyze thousands of lines of book details without losing track of the original prompt.

Yes. The integration runs inside isolated V8 sandboxes that do not persist your library catalog IDs, digital book metadata, or search parameters. Your enterprise data stays within your Google Cloud perimeter, and Vinkius only acts as a secure, stateless gateway to fetch the requested library information.

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