How to integrate Kibana MCP with Mastra AI

This guide walks you through connecting Kibana to Mastra AI using the Composio tool router. By the end, you'll have a working Kibana agent that can visualize weekly sales data as a chart, list top error logs from last 24 hours, generate dashboard of user activity trends through natural language commands. This guide will help you understand how to give your Mastra AI agent real control over a Kibana account through Composio's Kibana MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Introduction

This guide will help you understand how to give your Mastra AI agent real control over a Kibana account through Composio's Kibana MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Kibana with

OpenAI Agents SDK Claude Agent SDK Claude Code Claude Cowork Codex OpenClaw Hermes CLI Google ADK LangChain Vercel AI SDK LlamaIndex CrewAI

TL;DR

Here's what you'll learn:

Set up your environment so Mastra, OpenAI, and Composio work together
Create a Tool Router session in Composio that exposes Kibana tools
Connect Mastra's MCP client to the Composio generated MCP URL
Fetch Kibana tool definitions and attach them as a toolset
Build a Mastra agent that can reason, call tools, and return structured results
Run an interactive CLI where you can chat with your Kibana agent

What is Mastra AI?

Mastra AI is a TypeScript framework for building AI agents with tool support. It provides a clean API for creating agents that can use external services through MCP.

Key features include:

MCP Client: Built-in support for Model Context Protocol servers
Toolsets: Organize tools into logical groups
Step Callbacks: Monitor and debug agent execution
OpenAI Integration: Works with OpenAI models via @ai-sdk/openai

What is the Kibana MCP server, and what's possible with it?

The Kibana MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Kibana account. It provides structured and secure access so your agent can perform Kibana operations on your behalf.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step09 STEPS

Prerequisites

Before starting, make sure you have:

Node.js 18 or higher
A Composio account with an active API key
An OpenAI API key
Basic familiarity with TypeScript

Getting API Keys for OpenAI and Composio

OpenAI API Key

Go to the OpenAI dashboard and create an API key.
You need credits or a connected billing setup to use the models.
Store the key somewhere safe.

Composio API Key

Log in to the Composio dashboard.
Go to Settings and copy your API key.
This key lets your Mastra agent talk to Composio and reach Kibana through MCP.

Install dependencies

bash

npm install @composio/core @mastra/core @mastra/mcp @ai-sdk/openai dotenv

Install the required packages.

What's happening:

@composio/core is the Composio SDK for creating MCP sessions
@mastra/core provides the Agent class
@mastra/mcp is Mastra's MCP client
@ai-sdk/openai is the model wrapper for OpenAI
dotenv loads environment variables from .env

Set up environment variables

bash

COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

COMPOSIO_API_KEY authenticates your requests to Composio
COMPOSIO_USER_ID tells Composio which user this session belongs to
OPENAI_API_KEY lets the Mastra agent call OpenAI models

Import libraries and validate environment

typescript

import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey as string,
});

What's happening:

dotenv/config auto loads your .env so process.env.* is available
openai gives you a Mastra compatible model wrapper
Agent is the Mastra agent that will call tools and produce answers
MCPClient connects Mastra to your Composio MCP server
Composio is used to create a Tool Router session

Create a Tool Router session for Kibana

typescript

async function main() {
  const session = await composio.create(
    composioUserID as string,
    {
      toolkits: ["kibana"],
    },
  );

  const composioMCPUrl = session.mcp.url;
  console.log("Kibana MCP URL:", composioMCPUrl);

What's happening:

create spins up a short-lived MCP HTTP endpoint for this user
The toolkits array contains "kibana" for Kibana access
session.mcp.url is the MCP URL that Mastra's MCPClient will connect to

Configure Mastra MCP client and fetch tools

typescript

const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      nasdaq: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

console.log("Fetching MCP tools from Composio...");
const composioTools = await mcpClient.getTools();
console.log("Number of tools:", Object.keys(composioTools).length);

What's happening:

MCPClient takes an id for this client and a list of MCP servers
The headers property includes the x-api-key for authentication
getTools fetches the tool definitions exposed by the Kibana toolkit

Create the Mastra agent

typescript

const agent = new Agent({
    name: "kibana-mastra-agent",
    instructions: "You are an AI agent with Kibana tools via Composio.",
    model: "openai/gpt-5",
  });

What's happening:

Agent is the core Mastra agent
name is just an identifier for logging and debugging
instructions guide the agent to use tools instead of only answering in natural language
model uses openai("gpt-5") to configure the underlying LLM

Set up interactive chat interface

typescript

let messages: AiMessageType[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end.\n");

const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: "> ",
});

rl.prompt();

rl.on("line", async (userInput: string) => {
  const trimmedInput = userInput.trim();

  if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) {
    console.log("\nGoodbye!");
    rl.close();
    process.exit(0);
  }

  if (!trimmedInput) {
    rl.prompt();
    return;
  }

  messages.push({
    id: crypto.randomUUID(),
    role: "user",
    content: trimmedInput,
  });

  console.log("\nAgent is thinking...\n");

  try {
    const response = await agent.generate(messages, {
      toolsets: {
        kibana: composioTools,
      },
      maxSteps: 8,
    });

    const { text } = response;

    if (text && text.trim().length > 0) {
      console.log(`Agent: ${text}\n`);
        messages.push({
          id: crypto.randomUUID(),
          role: "assistant",
          content: text,
        });
      }
    } catch (error) {
      console.error("\nError:", error);
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    console.log("\nSession ended.");
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});

What's happening:

messages keeps the full conversation history in Mastra's expected format
agent.generate runs the agent with conversation history and Kibana toolsets
maxSteps limits how many tool calls the agent can take in a single run
onStepFinish is a hook that prints intermediate steps for debugging

Complete Code

Here's the complete code to get you started with Kibana and Mastra AI:

typescript

import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({ apiKey: composioAPIKey as string });

async function main() {
  const session = await composio.create(composioUserID as string, {
    toolkits: ["kibana"],
  });

  const composioMCPUrl = session.mcp.url;

  const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      kibana: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "kibana-mastra-agent",
    instructions: "You are an AI agent with Kibana tools via Composio.",
    model: "openai/gpt-5",
  });

  let messages: AiMessageType[] = [];

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: "> ",
  });

  rl.prompt();

  rl.on("line", async (input: string) => {
    const trimmed = input.trim();
    if (["exit", "quit"].includes(trimmed.toLowerCase())) {
      rl.close();
      return;
    }

    messages.push({ id: crypto.randomUUID(), role: "user", content: trimmed });

    const { text } = await agent.generate(messages, {
      toolsets: { kibana: composioTools },
      maxSteps: 8,
    });

    if (text) {
      console.log(`Agent: ${text}\n`);
      messages.push({ id: crypto.randomUUID(), role: "assistant", content: text });
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main();

Conclusion

You've built a Mastra AI agent that can interact with Kibana through Composio's Tool Router. You can extend this further by:

Adding other toolkits like Gmail, Slack, or GitHub
Building a web-based chat interface around this agent
Using multiple MCP endpoints to enable cross-app workflows

TOOLS

Supported Tools

Every Kibana action and event your agent gets out of the box.

Delete Alerting Rule

Tool to delete an alerting rule in Kibana.

Delete Connector

Tool to delete a connector in Kibana.

Delete Fleet Output

Tool to delete a specific output configuration in Kibana Fleet.

Delete Fleet Proxy

Deletes a Fleet proxy configuration by its unique identifier.

Delete List

Deletes a list.

Delete Osquery Saved Query

Delete a saved Osquery query by its saved object ID.

Delete Saved Object

Tool to delete a saved object in Kibana.

Find Kibana Alerts

Tool to find and/or aggregate detection alerts in Kibana.

Get Action Types

Retrieves all available connector types (actions) in Kibana.

Get Alerting Rules

Tool to retrieve a list of alerting rules in Kibana.

Get Rule Types

Retrieves available rule types (alert types) in Kibana.

Get Cases

Tool to retrieve a list of cases in Kibana.

Get All Connectors

Tool to retrieve a list of all connectors in Kibana.

Get Data Views

Retrieves all data views (formerly known as index patterns) available in Kibana.

Find Detection Engine Rules

Retrieves a paginated list of Kibana detection engine rules with flexible filtering and sorting options.

Get Endpoint List Items

Retrieves Elastic Endpoint exception list items with filtering, pagination, and sorting capabilities.

Get Entity Store Engines

Retrieves all entity store engines configured in Kibana.

List Entity Store Entities

Tool to list entity records in the entity store with support for paging, sorting, and filtering.

Get Entity Store Status

Retrieves the current status of the Kibana Entity Store and its configured engines.

Get Fleet Agent Policies

Retrieves a paginated list of Fleet agent policies with filtering, sorting, and optional detailed information.

Get Fleet Agents Available Versions

Tool to retrieve the available versions for Fleet agents.

Get Fleet Agents Setup Status

Check Fleet setup readiness and identify missing requirements.

Check Fleet Permissions

Tool to check the permissions for the Fleet API.

Get Fleet Enrollment API Key

Tool to retrieve details of a specific enrollment API key by its ID.

Get Fleet Enrollment API Keys

Tool to fetch a list of enrollment API keys.

Get Fleet EPM Categories

Get all available package categories in the Elastic Package Manager (EPM) with package counts.

Get Fleet EPM Data Streams

Tool to retrieve the list of data streams in the Elastic Package Manager.

Get Fleet EPM Package Details

Retrieves comprehensive details for a specific Fleet integration package version from the Elastic Package Manager (EPM).

Get Fleet EPM Package File

Retrieves a specific file from an Elastic Package Manager (EPM) package.

Get Fleet EPM Packages

Tool to fetch the list of available packages in the Elastic Package Manager.

Get Installed EPM Packages

Tool to retrieve the list of installed packages in the Elastic Package Manager.

Get Fleet EPM Packages (Limited)

Retrieves a limited list of package names from the Elastic Package Manager (EPM) registry.

Get EPM Package Statistics

Retrieves usage statistics for a specific Fleet package in Kibana, including the number of package policies and agent policies using the package.

Get Fleet Package Policies

Retrieves a list of Fleet package policies (integration policies) in Kibana.

Get Fleet Server Host

Tool to fetch details of a specific Fleet server host by its item ID.

Get Fleet Server Hosts

Tool to retrieve the list of Fleet Server hosts.

Get Index Management Indices

Tool to fetch information about indices managed by Kibana's Index Management feature.

Get Node Metrics

Tool to retrieve statistics for nodes in an Elasticsearch cluster, often visualized in Kibana.

Get Reporting Jobs

Tool to retrieve a list of reporting jobs in Kibana.

Get Saved Objects

Tool to retrieve a list of saved objects in Kibana based on specified criteria.

Get Kibana Status

Tool to get the current status of Kibana.

Create Alerting Rule

Tool to create a new alerting rule in Kibana.

Create Case

Tool to create a new case in Kibana.

Create Kibana Connector

Tool to create a new connector in Kibana.

Create Dashboard

Tool to create a new dashboard in Kibana.

Create Data View

Tool to create a new data view (index pattern) in Kibana.

Create or Update Saved Object

Tool to create or update a saved object in Kibana.

FRAMEWORKS

How to build Kibana MCP Agent with another framework

OpenAI Agents SDK

Use Kibana MCP with OpenAI Agents SDK

Claude Agent SDK

Use Kibana MCP with Claude Agent SDK

Claude Code

Use Kibana MCP with Claude Code

Claude Cowork

Use Kibana MCP with Claude Cowork

Codex

Use Kibana MCP with Codex

OpenClaw

Use Kibana MCP with OpenClaw

Hermes

Use Kibana MCP with Hermes

CLI

Use Kibana MCP with CLI

Google ADK

Use Kibana MCP with Google ADK

LangChain

Use Kibana MCP with LangChain

Vercel AI SDK

Use Kibana MCP with Vercel AI SDK

LlamaIndex

Use Kibana MCP with LlamaIndex

CrewAI

Use Kibana MCP with CrewAI

MORE TOOLKITS

Explore Other Toolkits

Toolkit marketplace

Firecrawl

Api Key

Firecrawl automates large-scale web crawling and data extraction. It helps organizations efficiently gather, index, and analyze content from online sources.

Tavily

Api Key

Tavily offers powerful search and data retrieval from documents, databases, and the web. It helps teams locate and filter information instantly, saving hours on research.

Exa

Api Key

Exa is a data extraction and search platform for gathering and analyzing information from websites, APIs, or databases. It helps teams quickly surface insights and automate data-driven workflows.

Serpapi

Api Key

SerpApi is a real-time API for structured search engine results. It lets you automate SERP data collection, parsing, and analysis for SEO and research.

FAQ

Frequently asked questions

With a standalone Kibana MCP server, the agents and LLMs can only access a fixed set of Kibana tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Kibana and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. Mastra AI fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Kibana tools.

Yes, absolutely. You can configure which Kibana scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Kibana data and credentials are handled as safely as possible.

Start with Kibana.It takes 30 seconds.

Managed auth, hosted MCP servers, and every Kibana tool your agent needs.Free to start.

Start building

Customer stories

Teams ship real agents on Composio

GET STARTED FOR FREE BOOK A DEMO

Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati

Co-founder, Slashy

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

Abhi Arya

Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

Nirman Dave

CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

Ryan Yu

Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

Tomisin Jenrola

Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Jerome Leclanche

Co-Founder, Ingram Technologies

How to integrate Kibana MCP with Mastra AI

Connect Kibana without auth hassles

Introduction

Also integrate Kibana with

TL;DR

What is Mastra AI?

What is the Kibana MCP server, and what's possible with it?

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

How the Composio SDK works

Step-by-step Guide

Prerequisites

Getting API Keys for OpenAI and Composio

Install dependencies

Set up environment variables

Import libraries and validate environment

Create a Tool Router session for Kibana

Configure Mastra MCP client and fetch tools

Create the Mastra agent

Set up interactive chat interface

Complete Code

Conclusion

Supported Tools

How to build Kibana MCP Agent with another framework

OpenAI Agents SDK

Claude Agent SDK

Claude Code

Claude Cowork

Codex

OpenClaw

Hermes

CLI

Google ADK

LangChain

Vercel AI SDK

LlamaIndex

CrewAI

Explore Other Toolkits

Firecrawl

Tavily

Exa

Serpapi

Frequently asked questions

What are the differences in Tool Router MCP and Kibana MCP?+

Can I use Tool Router MCP with Mastra AI?+

Can I manage the permissions and scopes for Kibana while using Tool Router?+

How safe is my data with Composio Tool Router?+

Start with Kibana.It takes 30 seconds.

Teams ship real agents on Composio