How to Use the Elastic Enterprise Search MCP in AutoGen

Q: Can AutoGen agents coordinate a search using Elastic Enterprise Search?

Yes, AutoGen agents can share the search tool. They discuss the query parameters and verify the results before delivering an answer.

Q: How do AutoGen agents index documents in Elastic Enterprise Search?

They use the indexdocuments tool as part of their workflow. You can set up one agent to format the JSON and another to execute the write.

Q: Can I use Elastic Enterprise Search analytics to trigger agent actions in AutoGen?

You can. An agent can call analytics to check search health and then trigger a re-indexing task if the data looks stale.

Coordinate multi-agent teams in AutoGen to manage and query Elastic Enterprise Search.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Elastic Enterprise Search MCP to AutoGen

Create your Vinkius account to connect Elastic Enterprise Search to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Elastic Enterprise Search with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Consensus-based document indexing

Multiple AutoGen agents can debate the validity of data before calling `index_documents`. This ensures only clean, verified information hits your engine. You reduce noise in your search results by having a validation agent sign off on the data first. It’s a programmatic gate for your search index.

Collaborative search operations

One agent handles the `search` query while another parses the output. They negotiate the best interpretation of the results to answer the user. This prevents single-agent hallucinations. By comparing search results against internal logic, your agents arrive at a more accurate conclusion.

Administrative oversight via agents

Assign an agent to monitor the `analytics` tool. It can identify patterns in search queries and propose adjustments to your engine configuration. You gain an automated admin team that watches your search health. If queries fail, the agent knows and can report the issue immediately.

Setup guide

Set up Elastic Enterprise Search MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Elastic Enterprise Search tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Elastic Enterprise Search_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Elastic Enterprise Search data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Elastic Enterprise Search_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Elastic Enterprise Search data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Elastic Enterprise Search. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Elastic Enterprise Search now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Elastic Enterprise Search MCP in AutoGen

Yes, AutoGen agents can share the `search` tool. They discuss the query parameters and verify the results before delivering an answer.

They use the `index_documents` tool as part of their workflow. You can set up one agent to format the JSON and another to execute the write.

You can. An agent can call `analytics` to check search health and then trigger a re-indexing task if the data looks stale.

We enforce strict isolation between agent sessions. Your data is processed in an ephemeral environment that vanishes immediately after the tool execution.

No. The key is held by the MCP server and never exposed to the agents themselves. They only see the results of the operations you allow.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python