Elasticsearch Semantic Search MCP Server
The MCP server provides semantic search functionality through Elasticsearch, enabling users to search through Search Labs blog posts that have been indexed using Elastic Open Crawler.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Elasticsearch Semantic Search MCP Serverfind blog posts about semantic search implementation"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP Server: Elasticsearch semantic search tool
Demo repo for: https://j.blaszyk.me/tech-blog/mcp-server-elasticsearch-semantic-search/
Table of Contents
Related MCP server: ElasticMind-MCP
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 devOnce running, access the MCP Inspector at: http://localhost:5173
Integrating with Claude Desktop
To add the MCP server to Claude Desktop:
make install-claude-configThis 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 "$(pwd)/crawler-config:/app/config" \
--network host \
docker.elastic.co/integrations/crawler:latest \
-c "bin/crawler crawl config/test-crawler.yml"This should print crawled content from a single page.
2. Configure Elasticsearch
Set up Elasticsearch URL and API Key.
Generate an API key with minimum crawler permissions:
POST /_security/api_key
{
"name": "crawler-search-labs",
"role_descriptors": {
"crawler-search-labs-role": {
"cluster": ["monitor"],
"indices": [
{
"names": ["search-labs-posts"],
"privileges": ["all"]
}
]
}
},
"metadata": {
"application": "crawler"
}
}Copy the encoded value from the response and set it as API_KEY.
3. Update Index Mapping for Semantic Search
Ensure the search-labs-posts index exists. If not, create it:
PUT search-labs-postsUpdate the mapping to enable semantic search:
PUT search-labs-posts/_mappings
{
"properties": {
"body": {
"type": "text",
"copy_to": "semantic_body"
},
"semantic_body": {
"type": "semantic_text",
"inference_id": ".elser-2-elasticsearch"
}
}
}The body field is indexed as semantic text using Elasticsearch’s ELSER model.
4. Start Crawling
Run the crawler to populate the index:
docker run --rm \
--entrypoint /bin/bash \
-v "$(pwd)/crawler-config:/app/config" \
--network host \
docker.elastic.co/integrations/crawler:latest \
-c "bin/crawler crawl config/elastic-search-labs-crawler.yml"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/_countThis 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
This server cannot be deployed
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