How to Use the Elastic Enterprise Search MCP in CrewAI

Q: How do I give my CrewAI agents access to Elastic Enterprise Search?

Add the server URL to the mcps array in your agent definition. The agent will automatically discover the search and indexing tools.

Q: Can I restrict which CrewAI agents use Elastic Enterprise Search tools?

Yes. Use the MCPServerHTTP class with a toolfilter. You can give your analyst agent the analytics tool while restricting indexdocuments to a background worker.

Q: How do multiple CrewAI agents share Elastic Enterprise Search data?

Agents share memory natively. A researcher agent can run search, find the relevant documents, and pass the exact JSON payload to the next agent in the sequence.

Give your CrewAI agents direct access to Elastic Enterprise Search. Build autonomous teams that index, search, and monitor data.

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Connect Elastic Enterprise Search MCP to CrewAI

Create your Vinkius account to connect Elastic Enterprise Search to CrewAI 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 CrewAI

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Deploy an Elastic Enterprise Search MCP Server

The `search` tool gives your researcher agent direct read access to your corporate data. Instead of guessing at facts, the agent queries the index, retrieves the exact JSON documents, and passes the context to a writer agent. You assign specific tools to specific roles. A data entry agent gets `index_documents` to push new records, while the analyst agent only gets read access to prevent accidental overwrites.

Autonomous search monitoring

The `analytics` tool feeds live search metrics to a monitor agent. This agent watches for trends, like a sudden drop in click-through rates on top queries. If the monitor spots an issue, it hands off to a moderator agent. The moderator runs `list_engines` and `get_engine` to audit the cluster configuration and pinpoint the failure.

Verify indexing tasks automatically

The `list_documents` tool acts as a verification step for your CrewAI pipelines. After an agent ingests a batch of records, a QA agent checks the engine to ensure the document count matches the source. This creates a self-healing loop. If documents are missing, the QA agent instructs the data agent to re-run the ingestion process.

Setup guide

Set up Elastic Enterprise Search MCP in CrewAI

Prerequisites

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

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Elastic Enterprise Search tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Elastic Enterprise Search Analyst",
    goal="Access and analyze Elastic Enterprise Search data via MCP.",
    backstory="Expert analyst with direct Elastic Enterprise Search access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Elastic Enterprise Search transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

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

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Elastic Enterprise Search Analyst",
        goal="Access and analyze Elastic Enterprise Search data via MCP.",
        backstory="Expert analyst with direct Elastic Enterprise Search access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Elastic Enterprise Search transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

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.

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Common questions about Elastic Enterprise Search MCP in CrewAI

Add the server URL to the `mcps` array in your agent definition. The agent will automatically discover the search and indexing tools.

Yes. Use the `MCPServerHTTP` class with a `tool_filter`. You can give your analyst agent the `analytics` tool while restricting `index_documents` to a background worker.

Agents share memory natively. A researcher agent can run `search`, find the relevant documents, and pass the exact JSON payload to the next agent in the sequence.

CrewAI supports stdio, SSE, and Streamable HTTP. Just pass the endpoint, and the framework negotiates the connection to the MCP server.

Yes. The V8 Isolate sandbox runs the MCP connection ephemerally. When your CrewAI agents pull JSON documents via `search` or push them via `index_documents`, the data never rests on our infrastructure.

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