Kibana MCP

Name: Kibana MCP
Author: mshegolev

by mshegolevversion 0.1.1i★ –iRuns on your computer

Registry nameio.github.mshegolev/kibana-mcp

Install

Overview

Description from the maker (original English)

Kibana/Elasticsearch MCP — log search, aggregations, index discovery, dashboards.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiVery new↓ 145/wk · ★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Search & AI memory
You need to fill in: KIBANA_URL, KIBANA_API_KEY, KIBANA_PASSWORD

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: KIBANA_URL, ELASTICSEARCH_URL, KIBANA_API_KEY, KIBANA_USERNAME, KIBANA_PASSWORD, KIBANA_SSL_VERIFY

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "kibana": {
      "command": "uvx",
      "args": [
        "kibana-mcp"
      ],
      "env": {
        "KIBANA_URL": "your-value",
        "ELASTICSEARCH_URL": "your-value",
        "KIBANA_API_KEY": "your-value",
        "KIBANA_USERNAME": "your-value",
        "KIBANA_PASSWORD": "your-value",
        "KIBANA_SSL_VERIFY": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add kibana --env KIBANA_URL=your-value --env ELASTICSEARCH_URL=your-value --env KIBANA_API_KEY=your-value --env KIBANA_USERNAME=your-value --env KIBANA_PASSWORD=your-value --env KIBANA_SSL_VERIFY=your-value -- uvx kibana-mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "kibana": {
      "command": "uvx",
      "args": [
        "kibana-mcp"
      ],
      "env": {
        "KIBANA_URL": "your-value",
        "ELASTICSEARCH_URL": "your-value",
        "KIBANA_API_KEY": "your-value",
        "KIBANA_USERNAME": "your-value",
        "KIBANA_PASSWORD": "your-value",
        "KIBANA_SSL_VERIFY": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "kibana": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "kibana-mcp"
      ],
      "env": {
        "KIBANA_URL": "your-value",
        "ELASTICSEARCH_URL": "your-value",
        "KIBANA_API_KEY": "your-value",
        "KIBANA_USERNAME": "your-value",
        "KIBANA_PASSWORD": "your-value",
        "KIBANA_SSL_VERIFY": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

KIBANA_URL required env
Kibana base URL (e.g. https://kibana.example.com)
ELASTICSEARCH_URL env
Direct Elasticsearch URL. If unset, ES requests route through the Kibana Console proxy.
KIBANA_API_KEY secret env
Elasticsearch API key (ApiKey base64(id:api_key) format). Takes priority over Basic auth.
KIBANA_USERNAME env
HTTP Basic auth username. Used only when KIBANA_API_KEY is not set.
KIBANA_PASSWORD secret env
HTTP Basic auth password.
KIBANA_SSL_VERIFY env
Verify SSL certificates (true/false). Set to 'false' for self-signed certs.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account mshegolev, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

More stars than 0% of the other 5716 servers in this category
Published to the registry more recently than 10% of the other 5716 servers in this category
Basic checks equal to or better than 100% of the other 5716 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Kibana MCP safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: KIBANA_URL, KIBANA_API_KEY, KIBANA_PASSWORD

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.1) reached the registry 7 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

by upstashWidely used↓ 972.7K/wk★ 64.2KUpdated 2 days ago

Computer or cloud

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Codebase Memory

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Runs on your computer

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Exa

Connect AI agents to Exa for web search, content fetching, and multi-step research.

by exa-labsWidely used★ 5.2KUpdated 2 months ago

Runs in the cloud✓ exa.ai

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

kibana-mcp

MCP server for Kibana / Elasticsearch — log search, aggregations, index discovery, and dashboard browsing via Claude and any MCP-compatible agent.

Why another Kibana MCP?

Existing integrations require a running Kibana instance with browser-level credentials and often wrap the Kibana UI rather than the stable REST APIs. This server:

Hits Elasticsearch REST API directly for log queries (faster, stable across Kibana UI changes)
Falls back to the Kibana Console proxy when no direct ES URL is configured (zero extra firewall rules)
Supports ApiKey auth (best for agents) as well as Basic auth and anonymous access
Returns both structured JSON (outputSchema) and markdown text so it works with any MCP client
Is read-only — all tools carry readOnlyHint: true, no data is modified

Tools

Tool	API	Description
`kibana_list_indices`	`GET ES/_cat/indices`	Discover available indices with health, docs, size
`kibana_search_logs`	`POST ES/{index}/_search`	Full-text log search with time range, sort, size
`kibana_aggregate_logs`	`POST ES/{index}/_search`	Terms grouping with count/avg/sum/min/max metric
`kibana_list_dashboards`	`GET Kibana/api/saved_objects/_find`	List saved dashboards with search + pagination
`kibana_get_dashboard`	`GET Kibana/api/saved_objects/dashboard/{id}`	Fetch one dashboard with panel breakdown

Installation

pip install kibana-mcp

Or run directly with uvx:

uvx kibana-mcp

Configuration

Environment Variables

Variable	Required	Description
`KIBANA_URL`	Yes	Kibana base URL (e.g. `https://kibana.example.com`)
`ELASTICSEARCH_URL`	No	Direct ES endpoint. If unset, ES requests go through Kibana Console proxy
`KIBANA_API_KEY`	No	ES API key (`ApiKey base64(id:api_key)` format). Recommended for agents
`KIBANA_USERNAME`	No	HTTP Basic auth username (used if API key not set)
`KIBANA_PASSWORD`	No	HTTP Basic auth password
`KIBANA_SSL_VERIFY`	No	`true` (default) or `false` for self-signed certificates

Auth priority: ApiKey > Basic > anonymous.

Copy .env.example to .env and fill in your values.

MCP Client Configuration (Claude Desktop / claude.app)

"mcpServers": { "kibana": { "command": "uvx", "args": ["kibana-mcp"], "env": { "KIBANA_URL": "https://kibana.example.com", "KIBANA_API_KEY": "your-api-key-here" } } } }

Or with direct ES access for better performance:

"mcpServers": { "kibana": { "command": "uvx", "args": ["kibana-mcp"], "env": { "KIBANA_URL": "https://kibana.example.com", "ELASTICSEARCH_URL": "https://es.example.com:9200", "KIBANA_API_KEY": "your-api-key-here" } } } }

Docker

docker run --rm -i \

-e KIBANA_URL=https://kibana.example.com \ -e KIBANA_API_KEY=your-key \ ghcr.io/mshegolev/kibana-mcp

Usage Examples

Log Search

Find the last 50 ERROR logs from the API service in the last hour

→ kibana_search_logs(index="logs-*", query="level:ERROR AND service:api", size=50, time_from="2026-04-18T09:00:00Z")

Show 500 HTTP errors sorted oldest first for incident replay

→ kibana_search_logs(index="nginx-*", query="status:500", sort_order="asc", size=100)

Aggregations

How many logs per log level in the last hour?

→ kibana_aggregate_logs(index="logs-*", group_by="level", time_from="2026-04-18T09:00:00Z")

What is the average response time per service?

→ kibana_aggregate_logs(index="logs-*", group_by="service.keyword", metric="avg", metric_field="response_time_ms")

Index Discovery

What log indices are available?

→ kibana_list_indices()

Show me all filebeat indices

→ kibana_list_indices(pattern="filebeat-*")

Dashboards

Find the infrastructure dashboard

→ kibana_list_dashboards(search="infrastructure")

What panels does dashboard X have?

→ kibana_get_dashboard(dashboard_id=" ")

Performance Characteristics

Log search (kibana_search_logs): typically 50-500ms with direct ES URL; add 100-200ms when routing through Kibana Console proxy
Aggregations (kibana_aggregate_logs): size:0 queries — no hits transferred, usually 10-100ms
Index listing: single _cat/indices call, O(index_count) response, typically <100ms
Dashboard APIs: Kibana Saved Objects API, typically 50-200ms; latency is Kibana-side, not network
Set ELASTICSEARCH_URL directly if your agent does frequent log searches — eliminates the proxy overhead

Development

git clone https://github.com/mshegolev/kibana-mcp

cd kibana-mcp pip install -e '.[dev]' pytest tests/ -v ruff check src tests ruff format src tests

License

MIT — see LICENSE.

Kibana MCP

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

kibana-mcp

Why another Kibana MCP?

Tools

Installation

Configuration

Environment Variables

MCP Client Configuration (Claude Desktop / claude.app)

Docker

Usage Examples

Log Search

Aggregations

Index Discovery

Dashboards

Performance Characteristics

Development

License