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Elastic Semantic Search

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MCP server to search up-to-date elasticsearch docs

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About

MCP server to search up-to-date elasticsearch docs

README

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

Table of Contents


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.


3. Update Index Mapping for Semantic Search

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

from github.com/jedrazb/elastic-semantic-search-mcp-server

Installing Elastic Semantic Search

This server has no published package — it is built from source. Open the repository and follow its README.

▸ github.com/jedrazb/elastic-semantic-search-mcp-server

FAQ

Is Elastic Semantic Search MCP free?

Yes, Elastic Semantic Search MCP is free — one-click install via Unyly at no cost.

Does Elastic Semantic Search need an API key?

No, Elastic Semantic Search runs without API keys or environment variables.

Is Elastic Semantic Search hosted or self-hosted?

Self-hosted: the server runs locally on your machine via the install command above.

How do I install Elastic Semantic Search in Claude Desktop, Claude Code or Cursor?

Open Elastic Semantic Search on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

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