Zotero MCP Server for Google ADKGive Google ADK instant access to 23 tools to Create Items, Delete Item, Delete Items, and more

Name: Zotero
Price: 29 USD
Availability: InStock
Rating: 4.9 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Zotero as an MCP tool provider through Vinkius and your ADK agents can call every tool with full schema introspection.

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The Zotero MCP Server for Google ADK is a standout in the Productivity category — giving your AI agent 23 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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python

from google.adk.agents import Agent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import (
    StreamableHTTPConnectionParams,
)

# Your Vinkius token. get it at cloud.vinkius.com
mcp_tools = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    )
)

agent = Agent(
    model="gemini-2.5-pro",
    name="zotero_agent",
    instruction=(
        "You help users interact with Zotero "
        "using 23 available tools."
    ),
    tools=[mcp_tools],
)

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Zotero MCP Server

Connect your Zotero library to any AI agent and take full control of your research workflow through natural conversation.

Google ADK natively supports Zotero as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 23 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.

What you can do

Collections & Organization — List top-level collections, subcollections, and specific collection details to navigate your library structure.
Item Management — Query all items, including notes and attachments, with support for advanced filtering by type, tag, or keyword.
Metadata Inspection — Fetch complete bibliographic data, creator information, and publication details for any specific item.
Tags & Publications — Access your personal publications and manage tags to categorize your research effectively.
Group Libraries — Seamlessly switch between your personal library and shared group libraries using specific IDs.

The Zotero MCP Server exposes 23 tools through the Vinkius. Connect it to Google ADK in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 23 Zotero tools available for Google ADK

When Google ADK connects to Zotero through Vinkius, your AI agent gets direct access to every tool listed below — spanning reference-management, citation-tools, academic-research, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

create

Create items on Zotero

Use get_new_item_template first to get the correct schema. Create new items in the Zotero library

delete

Delete item on Zotero

Delete a single item

delete

Delete items on Zotero

Delete multiple items (up to 50)

get

Get collection on Zotero

Get a specific collection by key

get

Get deleted on Zotero

Get deleted objects since a specific library version

get

Get item on Zotero

Get a specific item by key

get

Get item type fields on Zotero

List valid fields for a specific item type

get

Get new item template on Zotero

Get a JSON template for creating a new item of a specific type

get

Get tag on Zotero

Get tags matching a specific name

list

List collection items on Zotero

List items in a specific collection

list

List collections on Zotero

List all collections in the Zotero library

list

List item children on Zotero

List child items (notes, attachments) for a specific item

list

List item fields on Zotero

List all available Zotero item fields

list

List item tags on Zotero

List tags for a specific item

list

List item types on Zotero

List all available Zotero item types

list

List items on Zotero

List items in the Zotero library

list

List publications on Zotero

List items in My Publications

list

List subcollections on Zotero

List subcollections of a specific collection

list

List tags on Zotero

List all tags in the library

list

List top collections on Zotero

List top-level collections in the Zotero library

list

List top items on Zotero

List top-level items in the Zotero library

list

List trash items on Zotero

List items in the trash

update

Update item on Zotero

Update an existing item (Partial Update / PATCH)

Connect Zotero to Google ADK via MCP

Follow these steps to wire Zotero into Google ADK. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install Google ADK

Run pip install google-adk

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Create the agent

Save the code above and integrate into your ADK workflow

Explore tools

The agent will discover 23 tools from Zotero via MCP

Why Use Google ADK with the Zotero MCP Server

Google ADK provides unique advantages when paired with Zotero through the Model Context Protocol.

Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution

Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with Zotero

Production-ready features like session management, evaluation, and deployment come built-in. not bolted on

Seamless integration with Google Cloud services means you can combine Zotero tools with BigQuery, Vertex AI, and Cloud Functions

Zotero + Google ADK Use Cases

Practical scenarios where Google ADK combined with the Zotero MCP Server delivers measurable value.

Enterprise data agents: ADK agents query Zotero and cross-reference results with internal databases for comprehensive analysis

Multi-modal workflows: combine Zotero tool responses with Gemini's vision and language capabilities in a single agent

Automated compliance checks: schedule ADK agents to query Zotero regularly and flag policy violations or configuration drift

Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including Zotero

Example Prompts for Zotero in Google ADK

Ready-to-use prompts you can give your Google ADK agent to start working with Zotero immediately.

"List all my top-level collections in Zotero."

"Search for items in my library with the tag 'artificial-intelligence'."

"Get the complete bibliographic details for item key ABCD1234."

Troubleshooting Zotero MCP Server with Google ADK

Common issues when connecting Zotero to Google ADK through Vinkius, and how to resolve them.

McpToolset not found

Update: pip install --upgrade google-adk

Zotero + Google ADK FAQ

Common questions about integrating Zotero MCP Server with Google ADK.

How does Google ADK connect to MCP servers?

Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.

Can ADK agents use multiple MCP servers?

Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.

Which Gemini models work best with MCP tools?

Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.

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