Elasticsearch

Data & Analytics

Neotask on OpenClaw makes Elasticsearch's search and analytics capabilities conversational — exploring indices, running queries, and executing ES|QL to surface insights from your data without leaving your workflow.

• Log and event data becomes instantly queryable — your agent executes Elasticsearch queries on demand so your team gets answers from operational data in seconds, not hours
• Index management happens through conversation — your agent explores mappings, checks shard health, and audits your Elasticsearch infrastructure without command-line access
• Advanced analytics run autonomously — your agent uses ES|QL to run complex analytical queries across your Elasticsearch data and deliver formatted results to any downstream system

What You Can Do

The Elasticsearch integration gives Neotask 5 search and analytics actions.

`list_indices` — enumerate all indices in your Elasticsearch cluster with document counts and health status

`get_mappings` — retrieve the field mappings and data types for a specific index

`search` — execute a full Elasticsearch query against any index with filtering, aggregation, and sorting

`esql` — run ES|QL queries for advanced analytical operations with tabular results

`get_shards` — check shard allocation and health across your cluster

Every action runs autonomously or requires your approval — you decide.

Try Asking

"List all indices in our Elasticsearch cluster — how many documents are in each?"

"Search the application logs index for error events from the last hour grouped by service"

"What are the field mappings for our customer_events index?"

"Run an ES|QL query to find the top 10 slowest API endpoints by average response time this week"

"Check shard health across our cluster — are there any unassigned shards?"

Pro Tips

Schedule operational health checks: your agent queries cluster status, flags index issues, and delivers a daily infrastructure report

Use `esql` for business reporting queries — its tabular output format integrates cleanly with your reporting and notification tools

Pair Elasticsearch with your alerting integration so anomaly queries run continuously and trigger notifications when thresholds are crossed

Use `get_mappings` before writing complex queries — your agent maps the field structure to avoid type mismatches and query failures