How to Use the Kibana MCP in Google ADK

Q: How do I configure the Kibana MCP integration in Google ADK?

Install google-adk and initialize a McpToolset using your Vinkius HTTP endpoint URL. Pass this toolset directly into the LlmAgent constructor.

Q: Can Google ADK filter the exposed Kibana tools?

Yes. You pass a toolnames list to the toolset configuration. This restricts the agent to specific read-only operations like findsavedobjects and hides destructive tools like deletespace.

Give your Gemini agent native access to Kibana dashboards and policies using the Google ADK and this MCP Server.

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Connect Kibana MCP to Google ADK

Create your Vinkius account to connect Kibana to Google ADK 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 Kibana with Google ADK

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Perplexity

Long-context Kibana MCP Server analysis

Gemini models hold over a million tokens in context. That changes how you interact with observability data. Your agent pulls hundreds of configurations using `bulk_get_saved_objects` and analyzes your entire dashboard architecture in a single pass. You aren't limited to simple queries. The agent cross-references Kibana data views grabbed via `list_data_views` against your existing BigQuery schemas. It identifies missing mappings and creates them instantly using `create_runtime_field`.

Manage Elastic Agents at scale

Fleet management gets complicated when you have thousands of endpoints. This integration allows your Google ADK agent to audit your deployment programmatically. It runs `list_agents` to check status and pulls specific policy details with `list_agent_policies`. Security events require immediate isolation. If your enterprise agent detects a compromised host, it executes `unenroll_agent` to cut off access. You build autonomous security workflows that react faster than a human operator ever could.

Cross-space object synchronization

Keeping multiple Kibana spaces aligned is a massive headache for enterprise teams. Your agent automates this entirely. It uses `list_spaces` to map the environment and executes `copy_saved_objects` to push baseline dashboards to newly created tenant spaces. Access control happens in the same motion. After spinning up a new space with `create_space`, the agent assigns proper permissions via `create_or_update_role`. Every new team gets a fully configured, secure environment within seconds.

Setup guide

Set up Kibana MCP in Google ADK

Prerequisites

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

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Kibana tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Kibana_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Kibana tools via MCP.",
    tools=mcp_tools,
)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Kibana. 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 Kibana MCP in Google ADK

Install `google-adk` and initialize a `McpToolset` using your Vinkius HTTP endpoint URL. Pass this toolset directly into the `LlmAgent` constructor.

Yes. You pass a `tool_names` list to the toolset configuration. This restricts the agent to specific read-only operations like `find_saved_objects` and hides destructive tools like `delete_space`.

The agent bridges the two systems natively. It reads your Kibana configurations using `get_data_view` and writes custom Vertex AI reasoning scripts to analyze how that data aligns with your BigQuery tables.

The connection defaults to Streamable HTTP. Your agent sends requests to the Vinkius endpoint, which securely forwards them to your cluster.

The server processes raw Elastic Agent policies and enrollment keys. Vinkius operates on a strict zero-trust model where every request is authenticated via a single endpoint token. We never store your infrastructure definitions.

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