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Wikidata MCP Server for OpenAI Agents SDKGive OpenAI Agents SDK instant access to 8 tools to Create Statement, Execute Sparql, Get Item, and more

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The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Wikidata through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.

Ask AI about this MCP Server for OpenAI Agents SDK

The Wikidata MCP Server for OpenAI Agents SDK is a standout in the The Unthinkable category — giving your AI agent 8 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
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="Wikidata Assistant",
            instructions=(
                "You help users interact with Wikidata. "
                "You have access to 8 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from Wikidata"
        )
        print(result.final_output)

asyncio.run(main())
Wikidata
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 Wikidata MCP Server

Connect to Wikidata, the central storage for structured data of Wikimedia projects. This MCP server allows your AI agent to tap into millions of items, properties, and statements using both traditional SPARQL queries and modern vector-based semantic search.

The OpenAI Agents SDK auto-discovers all 8 tools from Wikidata through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Wikidata, another analyzes results, and a third generates reports, all orchestrated through Vinkius.

What you can do

  • Entity Retrieval — Fetch full data and statements for any Wikidata Item (e.g., Q42) using the get_item and get_item_statements tools.
  • Advanced Querying — Execute complex SPARQL queries against the Wikidata Query Service (WDQS) with execute_sparql to find relationships and patterns across the entire graph.
  • Semantic Search — Use search_items_vector and search_properties_vector to find entities and properties based on meaning rather than just exact keywords.
  • Data Contribution — Update the knowledge graph by creating statements or setting descriptions with create_statement and set_item_description (requires OAuth).
  • Similarity Analysis — Compare text strings against specific entities to get semantic similarity scores using get_similarity_score.

The Wikidata MCP Server exposes 8 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 8 Wikidata tools available for OpenAI Agents SDK

When OpenAI Agents SDK connects to Wikidata through Vinkius, your AI agent gets direct access to every tool listed below — spanning knowledge-graph, sparql, structured-data, 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 statement on Wikidata

Requires OAuth 2.0 Access Token. Create a new statement for an Item

execute

Execute sparql on Wikidata

Use hint:Query hint:optimizer "None" if queries timeout. Execute a SPARQL query

get

Get item on Wikidata

g., Q42) via the Wikibase REST API. Retrieve a specific Wikidata Item

get

Get item statements on Wikidata

Retrieve statements for a Wikidata Item

get

Get similarity score on Wikidata

Compute similarity between text and an entity

search

Search items vector on Wikidata

Hybrid vector/keyword search for Items

search

Search properties vector on Wikidata

Hybrid vector/keyword search for Properties

set

Set item description on Wikidata

Requires OAuth 2.0 Access Token. Set an Item description

Connect Wikidata to OpenAI Agents SDK via MCP

Follow these steps to wire Wikidata into OpenAI Agents SDK. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

01

Install the SDK

Run pip install openai-agents in your Python environment
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
03

Run the script

Save the code above and run it: python agent.py
04

Explore tools

The agent will automatically discover 8 tools from Wikidata

Why Use OpenAI Agents SDK with the Wikidata MCP Server

OpenAI Agents SDK provides unique advantages when paired with Wikidata through the Model Context Protocol.

01

Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety

02

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

03

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

04

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

Wikidata + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Wikidata MCP Server delivers measurable value.

01

Automated workflows: build agents that query Wikidata, process the data, and trigger follow-up actions autonomously

02

Multi-agent orchestration: create specialist agents. one queries Wikidata, another analyzes results, a third generates reports

03

Data enrichment pipelines: stream data through Wikidata tools and transform it with OpenAI models in a single async loop

04

Customer support bots: agents query Wikidata to resolve tickets, look up records, and update statuses without human intervention

Example Prompts for Wikidata in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Wikidata immediately.

01

"Search for Wikidata items related to 'artificial neural networks' using vector search."

02

"Run a SPARQL query to find the 5 most populated cities in Brazil."

03

"Get all statements for the Wikidata item Q42."

Troubleshooting Wikidata MCP Server with OpenAI Agents SDK

Common issues when connecting Wikidata to OpenAI Agents SDK through Vinkius, and how to resolve them.

01

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents
02

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

Wikidata + OpenAI Agents SDK FAQ

Common questions about integrating Wikidata MCP Server with OpenAI Agents SDK.

01

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.
02

Can I use multiple MCP servers in one agent?

Yes. Pass a list of MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.
03

Does the SDK support streaming responses?

Yes. The SDK supports SSE and Streamable HTTP transports, both of which work natively with Vinkius.

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