Elastic-Python-MCP-Server
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Elasticsearch MCP Server is a Python-based server for searching and analyzing property data using Elasticsearch.
The Elasticsearch MCP Server is a Python-based Model Control Protocol server designed to facilitate the search and analysis of property data through Elasticsearch. Originally developed as a Jupyter notebook, it has been converted into a standalone Python script. The server integrates with Elasticsearch Serverless and utilizes the Elastic Learned Sparse Encoder (ELSER) for semantic search capabilities. It also incorporates geocoding functionality via the Google Maps API, allowing users to search for properties based on various criteria such as location, price range, number of bedrooms/bathrooms, square footage, and more. The server is structured to support data ingestion, environment configuration, and API key management, ensuring a comprehensive setup for property data analysis.
Features
- Property Search: Search for properties using criteria like location, price range, number of bedrooms/bathrooms, square footage, and more.
- Geocoding Integration: Uses Google Maps API to convert location strings into geographic coordinates.
- Elasticsearch Integration: Connects to Elasticsearch Serverless and uses ELSER for semantic search with support for custom search templates.
Tools
get_properties_template_params
Returns the required parameters for the properties search template.
geocode_location
Converts a location string into geographic coordinates.
search_template
Performs property searches using the configured search template.
