Category: Agentic AI

Articles tagged Agentic AI

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Creating an Elasticsearch MCP server with TypeScript

Learn how to create an Elasticsearch MCP server with TypeScript and Claude Desktop.

Jeffrey Rengifo

The shell tool is not a silver bullet for context engineering

Learn what context-retrieval tools exist for context engineering, how they work, and their trade-offs.

Leonie Monigatti

Using Elasticsearch Inference API along with Hugging Face models

Learn how to connect Elasticsearch to Hugging Face models using inference endpoints, and build a multilingual blog recommendation system with semantic search and chat completions.

Jeffrey Rengifo

AI agent memory: Creating smart agents with Elasticsearch managed memory

Learn how to create smarter and more efficient AI agents by managing memory using Elasticsearch.

Gustavo Llermaly

The Gemini CLI extension for Elasticsearch with tools and skills

Introducing Elastic’s extension for Google's Gemini CLI to search, retrieve, and analyze Elasticsearch data in developer and agentic workflows.

Walter Rafelsberger

Agent Skills for Elastic: Turn your AI agent into an Elastic expert

Give your AI coding agent the knowledge to query, visualize, secure, and automate with Elastic Agent Skills.

Graham Hudgins

SearchClaw: Bring Elasticsearch to OpenClaw with composable skills

Give your local AI agent access to Elasticsearch data using OpenClaw, composable skills, and agents, no custom code required.

Alex Salgado

Building effective database retrieval tools for context engineering

Best practices for writing database retrieval tools for context engineering. Learn how to design and evaluate agent tools for interacting with Elasticsearch data.

Leonie Monigatti

Build task-aware agents with an expanded model catalog on Elastic Inference Service (EIS)

Elastic Inference Service (EIS) expands its managed model catalog, enabling teams to build production-ready agents with flexible model choice across retrieval, generation, and reasoning, without managing GPUs or infrastructure.

Sean Handley

Does MCP make search obsolete? Not even close

Explore why search engines and indexed search remain the foundation for scalable, accurate, enterprise-grade AI, even in the age of MCP, federated search, and large context windows.

Dayananda Srinivas

Using subagents and Elastic Agent Builder to bring business context into code planning

Learn about subagents, how to ensure they have the right information, and how to create a specialized subagent that connects Claude Code to your Elasticsearch data.

Gustavo Llermaly

Common Expression Language (CEL): How the CEL input improves data collection in Elastic Agent integrations

Learn how the Common Expression Language differs from other programming languages, how we’ve extended it for Filebeat’s CEL input, and the flexibility it gives you to express data collection logic in Elastic Agent integrations.

Chris Berkhout

Ready to build state of the art search experiences?

Sufficiently advanced search isn’t achieved with the efforts of one. Elasticsearch is powered by data scientists, ML ops, engineers, and many more who are just as passionate about search as you are. Let’s connect and work together to build the magical search experience that will get you the results you want.

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