How to Use the Elastic Enterprise Search MCP in OpenAI Agents SDK

Q: Can the OpenAI Agents SDK index new documents automatically into Elastic Enterprise Search?

Yes. The indexdocuments tool accepts JSON payloads. You can configure guardrails in the SDK to validate the document structure before the agent commits it to your search cluster.

Q: Does the OpenAI Agents SDK know which engines exist in Elastic Enterprise Search?

It finds out dynamically. By calling listengines, the agent retrieves the active engines and routes subsequent searches to the correct destination.

Connect the Elastic Enterprise Search MCP Server to the OpenAI Agents SDK for production-grade, traced search operations.

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Connect Elastic Enterprise Search MCP to OpenAI Agents SDK

Create your Vinkius account to connect Elastic Enterprise Search 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.

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Setup Elastic Enterprise Search with OpenAI Agents SDK

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Query execution and analytics

The `search` tool executes direct queries against your Elastic engines from within the OpenAI Agents SDK. You pass the query parameters, and the agent retrieves matching documents. If a search fails to return what you need, the agent can pivot to the `analytics` tool to check top queries and click metrics. This keeps your agent grounded in actual user behavior. Because you're using OpenAI's framework, every search request and analytics pull gets recorded in your tracing dashboard. You see exactly how long the Elastic cluster took to respond and what the agent did with the payload.

Document indexing via MCP Server

The `index_documents` tool pushes new JSON records directly into your specified schema. Your agent formats the data, validates it against your guardrails, and fires it into the MCP Server. You don't write custom ETL scripts for this. If the agent generates a summary or extracts entities from a conversation, it hands that structured data straight to Elastic. The built-in guardrails ensure the agent doesn't spam the index with malformed documents.

Engine metadata management

The `list_engines` and `get_engine` tools pull configuration details and status metrics for your Elastic deployments. The agent reads this metadata to understand where to route specific queries. You can also use `list_documents` to verify that a recent indexing job actually populated the engine. If one specialized agent handles document ingestion, a handoff to a second agent can trigger this verification step automatically.

Setup guide

Set up Elastic Enterprise Search MCP in OpenAI Agents SDK

Prerequisites

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

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Elastic Enterprise Search tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Elastic Enterprise Search tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Elastic Enterprise Search tools and returns structured results. Copy the full example on the right to get started.

agent.py

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="Elastic Enterprise Search Agent",
            instructions="You have access to Elastic Enterprise Search tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about Elastic Enterprise Search MCP in OpenAI Agents SDK

Install the openai-agents package. Initialize MCPServerStreamableHttp with your endpoint URL. Pass it to the Agent constructor using the mcp_servers array.

Yes. The index_documents tool accepts JSON payloads. You can configure guardrails in the SDK to validate the document structure before the agent commits it to your search cluster.

Tool discovery happens automatically. You skip writing custom wrapper functions for search and analytics, and you get native tracing in your OpenAI dashboard out of the box.

It finds out dynamically. By calling list_engines, the agent retrieves the active engines and routes subsequent searches to the correct destination.

Vinkius manages the authentication layer so your OpenAI agents never hold the raw Elastic API keys. The text documents and search analytics flow through an isolated MCP sandbox that drops all state the millisecond the request completes.

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