Elasticsearch: Lightning-Fast Search & Scalable Analytics

Elasticsearch mirrors your data in real time, empowering lightning-fast searches and scalable analytics to drive critical decisions with confidence.

Visit Repository

✨ Developer Tools

4.2(16 reviews)

24 saves

11 comments

63% of users reported increased productivity after just one week

About Elasticsearch

What is Elasticsearch: Lightning-Fast Search & Scalable Analytics?

Elasticsearch is a distributed search and analytics engine designed to handle massive datasets with real-time performance. It allows Large Language Models (LLMs) to automate index management and execute complex queries at scale. The protocol server acts as a bridge, enabling seamless interaction between applications and Elasticsearch clusters for tasks like document indexing, search optimization, and schema management.

Key Features of Elasticsearch: Lightning-Fast Search & Scalable Analytics?

Instant Search Execution: Perform precise searches using Elasticsearch Query DSL with guaranteed low-latency responses.
Automated Schema Discovery: Dynamically retrieve index mappings (field definitions, data types) via URLs like elasticsearch://<host>/<index>/schema.
Full Index Lifecycle Management: Create, list, and manage indices programmatically with optional configuration parameters for mappings and settings.
Document-Level Operations: Directly index documents with optional ID assignment for precise data insertion.

Elasticsearch Features

How to use Elasticsearch: Lightning-Fast Search & Scalable Analytics?

Integrate Elasticsearch into your workflow in two steps:

Configure the Protocol Server: Add the server configuration to claude_desktop_config.json:

{
  "mcpServers": {
    "elasticsearch": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-elasticsearch", "http://localhost:9200"]
    }
  }
}

Deploy Elasticsearch: Use this Docker command to start a single-node instance:
docker run -d --name elasticsearch -p 9200:9300 -e "discovery.type=single-node" docker.elastic.co/elasticsearch/elasticsearch:8.11.3

Use Cases of Elasticsearch: Lightning-Fast Search & Scalable Analytics?

Real-Time Log Analysis: Process and search terabytes of log data instantly
E-commerce Search: Power product discovery with faceted search and autocomplete
IoT Data Streaming: Analyze sensor data streams in near real-time
Content Recommendation: Build search-based recommendation engines

Elasticsearch FAQ

FAQ from Elasticsearch: Lightning-Fast Search & Scalable Analytics?

How do I start with Elasticsearch?: Begin by deploying the official Docker image and configuring the protocol server as shown in the usage section.
Can I customize index mappings?: Yes, provide explicit mappings and settings parameters when creating indices for full control over data structures.
What makes Elasticsearch fast?: Its inverted index architecture and distributed nature allow parallel query processing across nodes, even at petabyte scale.
Is this free to use?: Yes, the protocol server is MIT-licensed. Commercial Elasticsearch deployments require proper licensing from Elastic.

Content

Elasticsearch

A Model Context Protocol server for Elasticsearch clusters. Enables LLMs to manage indices and execute queries.

IMPORTANT NOTE : this was built mainly by feeding examples to claude from the postgres mcp server.

Components

Tools

search
- Execute search queries against indices
- Input:
  - index (string): Target index name
  - query (object): Elasticsearch query DSL
- Returns search hits
create_index
- Create new Elasticsearch indices
- Input:
  - index (string): Index name
  - mappings (object, optional): Index mappings configuration
  - settings (object, optional): Index settings configuration
list_indices
- List all available indices
- No input required
- Returns array of index information
index_document
- Index a document
- Input:
  - index (string): Target index name
  - id (string, optional): Document ID
  - document (object): Document content
- Returns indexing operation result

Resources

The server provides mapping information for each index:

Index Mappings (elasticsearch://<host>/<index>/schema)
- JSON mapping information
- Field names, types and configurations
- Automatically discovered from metadata

Usage with Claude Desktop

Add to the "mcpServers" section of your claude_desktop_config.json:

{
  "mcpServers": {
    "elasticsearch": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-elasticsearch",
        "http://localhost:9200"
      ]
    }
  }
}

Docker one liner to run container :

docker run -d --name elasticsearch -p 9200:9200 -p 9300:9300 -e "discovery.type=single-node" -e "xpack.security.enabled=false" docker.elastic.co/elasticsearch/elasticsearch:8.11.3

Replace the URL with your Elasticsearch endpoint.

License

Licensed under MIT License. Free to use, modify, and distribute. See LICENSE file for details.