jedrazb
MCP Serverjedrazbpublic

elastic semantic search mcp server

MCP server to search up-to-date elasticsearch docs

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Python
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About This Server

MCP server to search up-to-date elasticsearch docs

Model Context Protocol (MCP) - This server can be integrated with AI applications to provide additional context and capabilities, enabling enhanced AI interactions and functionality.

Documentation

MCP Server: Elasticsearch semantic search tool

Demo repo for: https://j.blaszyk.me/tech-blog/mcp-server-elasticsearch-semantic-search/

Table of Contents

  • Overview
  • Running the MCP Server
  • Integrating with Claude Desktop
  • Crawling Search Labs Blog Posts
      1. Verify Crawler Setup
      1. Configure Elasticsearch
      1. Update Index Mapping for Semantic Search
      1. Start Crawling
      1. Verify Indexed Documents

Overview

This repository provides a Python implementation of an MCP server for semantic search through Search Labs blog posts indexed in Elasticsearch.

It assumes you've crawled the blog posts and stored them in the search-labs-posts index using Elastic Open Crawler.


Running the MCP Server

Add ES_URL and ES_AP_KEY into .env file, (take a look here for generating api key with minimum permissions)

Start the server in MCP Inspector:

make dev

Once running, access the MCP Inspector at: http://localhost:5173


Integrating with Claude Desktop

To add the MCP server to Claude Desktop:

make install-claude-config

This updates claude_desktop_config.json in your home directory. On the next restart, the Claude app will detect the server and load the declared tool.


Crawling Search Labs Blog Posts

1. Verify Crawler Setup

To check if the Elastic Open Crawler works, run:

docker run --rm \
  --entrypoint /bin/bash \
  -v "$(pwd)/crawler-config:/app/config" \
  --network host \
  docker.elastic.co/integrations/crawler:latest \
  -c "bin/crawler crawl config/test-crawler.yml"

This should print crawled content from a single page.


2. Configure Elasticsearch

Set up Elasticsearch URL and API Key.

Generate an API key with minimum crawler permissions:

POST /_security/api_key
{
  "name": "crawler-search-labs",
  "role_descriptors": {
    "crawler-search-labs-role": {
      "cluster": ["monitor"],
      "indices": [
        {
          "names": ["search-labs-posts"],
          "privileges": ["all"]
        }
      ]
    }
  },
  "metadata": {
    "application": "crawler"
  }
}

Copy the encoded value from the response and set it as API_KEY.


Ensure the search-labs-posts index exists. If not, create it:

PUT search-labs-posts

Update the mapping to enable semantic search:

PUT search-labs-posts/_mappings
{
  "properties": {
    "body": {
      "type": "text",
      "copy_to": "semantic_body"
    },
    "semantic_body": {
      "type": "semantic_text",
      "inference_id": ".elser-2-elasticsearch"
    }
  }
}

The body field is indexed as semantic text using Elasticsearch’s ELSER model.


4. Start Crawling

Run the crawler to populate the index:

docker run --rm \
  --entrypoint /bin/bash \
  -v "$(pwd)/crawler-config:/app/config" \
  --network host \
  docker.elastic.co/integrations/crawler:latest \
  -c "bin/crawler crawl config/elastic-search-labs-crawler.yml"

TIP

If using a fresh Elasticsearch cluster, wait for the ELSER model to start before indexing.


5. Verify Indexed Documents

Check if the documents were indexed:

GET search-labs-posts/_count

This will return the total document count in the index. You can also verify in Kibana.


Done! You can now perform semantic searches on Search Labs blog posts

Quick Start

1

Clone the repository

git clone https://github.com/jedrazb/elastic-semantic-search-mcp-server
2

Install dependencies

cd elastic-semantic-search-mcp-server
npm install
3

Follow the documentation

Check the repository's README.md file for specific installation and usage instructions.

Repository Details

Ownerjedrazb
Repoelastic-semantic-search-mcp-server
LanguagePython
License-
Last fetched8/10/2025

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