MCP Server: Elasticsearch semantic search tool
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README
MCP Server: Elasticsearch semantic search tool
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
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