How to Use the Zotero MCP in OpenAI Agents SDK
Automate your research flow with Zotero using the OpenAI Agents SDK.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Zotero MCP to OpenAI Agents SDK
Create your Vinkius account to connect Zotero to OpenAI Agents SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Manage references and collections
The `list_collections` tool shows you every collection in your library. You can also use `list_top_collections` to quickly see all top-level groups. This makes it easy for your agent to understand where specific research items are stored. Need details? Use `get_collection` by key to pull up a whole collection's contents, or check the entire library with `list_items`. It gives your agent full visibility into your Zotero data set.
Create and update item records
When you need a new citation in Zotero, call `create_items`. The tool first uses `get_new_item_template` to ensure the schema is correct. Your agent handles this validation, guaranteeing the data hits the library right. If an existing reference needs tweaking, use `update_item`. It supports partial updates, meaning you only send what's changed—no need to resend the whole record every time.
Organize and track metadata
You can check all available fields for any item type using `list_item_fields`. This helps your agent know exactly what data points are valid. Furthermore, it lets you list tags on a specific reference with `list_item_tags`. Want to see everything about the structure? The `list_item_types` tool shows every single item type Zotero supports. It’s great for building specialized agent workflows.
Set up Zotero MCP in OpenAI Agents SDK
Prerequisites
- Python 3.10+ installed
-
openai-agentspackage (pip install openai-agents) - Active Vinkius subscription with a valid endpoint token
- 1
Install the SDK
Run
pip install openai-agentsto install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed. - 2
Connect via SSE transport
Use
MCPServerSsewith your Vinkius endpoint URL. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. The SDK auto-discovers all Zotero tools at runtime. - 3
Create your Agent
Pass the MCP to
Agent(mcp_servers=[server]). The agent receives Zotero tools as native definitions — JSON schemas resolve automatically. - 4
Run the agent
Call
Runner.run(agent, prompt)to execute. The agent invokes the appropriate Zotero tools and returns structured results. Copy the full example on the right to get started.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse
async def main():
async with MCPServerSse(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as server:
agent = Agent(
name="Zotero Agent",
instructions="You have access to Zotero tools.",
mcp_servers=[server],
)
result = await Runner.run(agent, "List recent transactions")
print(result.final_output)
asyncio.run(main()) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Zotero. 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 Zotero MCP in OpenAI Agents SDK
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