kibana-connectors

elastic/agent-skills · updated Apr 8, 2026

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$npx skills add https://github.com/elastic/agent-skills --skill kibana-connectors
0 commentsdiscussion
summary

Connectors store connection information for Elastic services and third-party systems. Alerting rules use connectors to

  • route actions (notifications) when rule conditions are met. Connectors are managed per Kibana Space and can be
  • shared across all rules within that space.
skill.md

Kibana Connectors

Core Concepts

Connectors store connection information for Elastic services and third-party systems. Alerting rules use connectors to route actions (notifications) when rule conditions are met. Connectors are managed per Kibana Space and can be shared across all rules within that space.

Connector Categories

Category Connector Types
LLM Providers OpenAI, Google Gemini, Amazon Bedrock, Elastic Managed LLMs, AI Connector, MCP (Preview, 9.3+)
Incident Management PagerDuty, Opsgenie, ServiceNow (ITSM, SecOps, ITOM), Jira, Jira Service Management (9.2+), IBM Resilient, Swimlane, Torq, Tines, D3 Security, XSOAR (9.1+), TheHive
Endpoint Security CrowdStrike, SentinelOne, Microsoft Defender for Endpoint
Messaging Slack (API / Webhook), Microsoft Teams, Email
Logging & Observability Server log, Index, Observability AI Assistant
Webhook Webhook, Webhook - Case Management, xMatters
Elastic Cases

Authentication

All connector API calls require API key auth or Basic auth. Every mutating request must include the kbn-xsrf header.

kbn-xsrf: true

Required Privileges

Access to connectors is granted based on your privileges to alerting-enabled features. You need all privileges for Actions and Connectors in Stack Management.

API Reference

Base path: <kibana_url>/api/actions (or /s/<space_id>/api/actions for non-default spaces).

Operation Method Endpoint
Create connector POST /api/actions/connector/{id}
Update connector PUT /api/actions/connector/{id}
Get connector GET /api/actions/connector/{id}
Delete connector DELETE /api/actions/connector/{id}
Get all connectors GET /api/actions/connectors
Get connector types GET /api/actions/connector_types
Run connector POST /api/actions/connector/{id}/_execute

Creating a Connector

Required Fields

Field Type Description
name string Display name for the connector
connector_type_id string The connector type (e.g., .slack, .email, .webhook, .pagerduty, .jira)
config object Type-specific configuration (non-secret settings)
secrets object Type-specific secrets (API keys, passwords, tokens)

Example: Create a Slack Connector (Webhook)

curl -X POST "https://my-kibana:5601/api/actions/connector/my-slack-connector" \
  -H "kbn-xsrf: true" \
  -H "Content-Type: application/json" \
  -H "Authorization: ApiKey <your-api-key>" \
  -d '{
    "name": "Production Slack Alerts",
    "connector_type_id": ".slack",
    "config": {},
    "secrets": {
      "webhookUrl": "https://hooks.slack.com/services/T00/B00/XXXX"
    }
  }'

All connector types share the same request structure — only connector_type_id, config, and secrets differ. See the Common Connector Type IDs table for available types and their required fields.

Example: Create a PagerDuty Connector

curl -X POST "https://my-kibana:5601/api/actions/connector/my-pagerduty" \
  -H "kbn-xsrf: true" \
  -H "Content-Type: application/json" \
  -H "Authorization: ApiKey <your-api-key>" \
  -d '{
    "name": "PagerDuty Incidents",
    "connector_type_id": ".pagerduty",
    "config": {
      "apiUrl": "https://events.pagerduty.com/v2/enqueue"
    },
    "secrets": {
      "routingKey": "your-pagerduty-integration-key"
    }
  }'

Updating a Connector

PUT /api/actions/connector/{id} replaces the full configuration. connector_type_id is immutable — delete and recreate to change it.

Listing and Discovering Connectors

# Get all connectors in the current space
curl -X GET "https://my-kibana:5601/api/actions/connectors" \
  -H "Authorization: ApiKey <your-api-key>"

# Get available connector types
curl -X GET "https://my-kibana:5601/api/actions/connector_types" \
  -H "Authorization: ApiKey <your-api-key>"

# Filter connector types by feature (e.g., only those supporting alerting)
curl -X GET "https://my-kibana:5601/api/actions/connector_types?feature_id=alerting" \
  -H "Authorization: ApiKey <your-api-key>"

The GET /api/actions/connectors response includes referenced_by_count showing how many rules use each connector. Always check this before deleting.

Running a Connector (Test)

Execute a connector action directly, useful for testing connectivity.

curl -X POST "https://my-kibana:5601/api/actions/connector/my-slack-connector/_execute" \
  -H "kbn-xsrf: true" \
  -H "Content-Type: application/json" \
  -H "Authorization: ApiKey <your-api-key>" \
  -d '{
    "params": {
      "message": "Test alert from API"
    }
  }'

Deleting a Connector

curl -X DELETE "https://my-kibana:5601/api/actions/connector/my-slack-connector" \
  -H "kbn-xsrf: true" \
  -H "Authorization: ApiKey <your-api-key>"

Warning: Deleting a connector that is referenced by rules will cause those rule actions to fail silently. Check referenced_by_count first.

Terraform Provider

Use the elasticstack provider resource elasticstack_kibana_action_connector.

terraform {
  required_providers {
    elasticstack = {
      source  = "elastic/elasticstack"
    }
  }
}

provider "elasticstack" {
  kibana {
    endpoints = ["https://my-kibana:5601"]
    api_key   = var.kibana_api_key
  }
}

resource "elasticstack_kibana_action_connector" "slack" {
  name              = "Production Slack Alerts"
  connector_type_id = ".slack"

  config = jsonencode({})

  secrets = jsonencode({
    webhookUrl = "https://hooks.slack.com/services/T00/B00/XXXX"
  })
}

resource "elasticstack_kibana_action_connector" "index" {
  name              = "Alert Index Writer"
  connector_type_id = ".index"

  config = jsonencode({
    index              = "alert-history"
    executionTimeField = "@timestamp"
  })

  secrets = jsonencode({})
}

Key Terraform notes:

  • config and secrets must be JSON-encoded strings via jsonencode()
  • Secrets are stored in Terraform state; use a remote backend with encryption and restrict state file access
  • Import existing connectors: terraform import elasticstack_kibana_action_connector.my_connector <space_id>/<connector_id> (use default for the default space)
  • After import, secrets are not populated in state; you must supply them in config

Preconfigured Connectors (On-Prem)

For self-managed Kibana, connectors can be preconfigured in kibana.yml so they are available at startup without manual creation:

xpack.actions.preconfigured:
  my-slack-connector:
    name: "Production Slack"
    actionTypeId: .slack
    secrets:
      webhookUrl: "https://hooks.slack.com/services/T00/B00/XXXX"
  my-webhook:
    name: "Custom Webhook"
    actionTypeId: .webhook
    config:
      url: "https://api.example.com/alerts"
      method: post
      hasAuth: true
    secrets:
      user: "alert-user"
      password: "secret-password"

Preconfigured connectors cannot be edited or deleted via the API or UI. They show is_preconfigured: true and omit config and is_missing_secrets from API responses.

Networking Configuration

Customize connector networking (proxies, TLS, certificates) via kibana.yml:

# Global proxy for all connectors
xpack.actions.proxyUrl: "https://proxy.example.com:8443"

# Per-host TLS settings
xpack.actions.customHostSettings:
  - url: "https://api.example.com"
    ssl:
      verificationMode: full
      certificateAuthoritiesFiles: ["/path/to/ca.pem"]

Connectors in Kibana Workflows

Connectors serve as the integration layer across multiple Kibana workflows, not just alerting notifications:

Workflow Connector Types Key Pattern
ITSM ticketing ServiceNow, Jira, IBM Resilient Create ticket on active, close on Recovered
On-call escalation PagerDuty, Opsgenie trigger on active, resolve on Recovered; always set a deduplication key
Case management Cases (system action) UI-only; groups alerts into investigation Cases; can auto-push to ITSM
Messaging / awareness Slack, Teams, Email onActionGroupChange for incident channels; summaries for monitoring channels
Audit logging Index onActiveAlert to write full alert time-series to Elasticsearch
AI workflows OpenAI, Bedrock, Gemini, AI Connector Powers Elastic AI Assistant and Attack Discovery; system-managed
Custom integrations Webhook Generic HTTP outbound with Mustache-templated JSON body

For detailed patterns, examples, and decision guidance for each workflow, see workflows.md.

Best Practices

  1. Use preconfigured connectors for production on-prem. They eliminate secret sprawl, survive Saved Object import

how to use kibana-connectors

How to use kibana-connectors on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add kibana-connectors
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/elastic/agent-skills --skill kibana-connectors

The skills CLI fetches kibana-connectors from GitHub repository elastic/agent-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/kibana-connectors

Reload or restart Cursor to activate kibana-connectors. Access the skill through slash commands (e.g., /kibana-connectors) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.534 reviews
  • Soo Ndlovu· Dec 24, 2024

    kibana-connectors is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Kofi Sharma· Dec 24, 2024

    Solid pick for teams standardizing on skills: kibana-connectors is focused, and the summary matches what you get after install.

  • Dhruvi Jain· Dec 4, 2024

    Keeps context tight: kibana-connectors is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Oshnikdeep· Nov 23, 2024

    Registry listing for kibana-connectors matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Isabella Menon· Nov 15, 2024

    kibana-connectors reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Henry Bansal· Nov 15, 2024

    We added kibana-connectors from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Ganesh Mohane· Oct 14, 2024

    kibana-connectors reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Anaya Robinson· Oct 6, 2024

    Registry listing for kibana-connectors matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Mia Abebe· Oct 6, 2024

    kibana-connectors fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Nia White· Sep 25, 2024

    Useful defaults in kibana-connectors — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

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