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Use Elasticsearch for smarter e-commerce search with planning, expansion, and filtering.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Search MCP" yet — see the docs or source repo.
Based on the user query "lightweight waterproof jacket for running," generate a query plan for an e-commerce catalog, expand synonyms and related attributes, and add filters for price range, brand, and stock availability.
A structured search plan including intent, expanded terms, Elasticsearch query suggestions, and filters.
For the query "eye-care desk lamp for students," design a search strategy to improve recall, add common aliases, functional features, and usage scenarios, and explain how to intelligently filter irrelevant products.
A search design with query expansion logic, candidate keywords, filtering rules, and ranking optimization suggestions.
Analyze why results for the keyword "portable coffee maker" are imprecise, and propose improvements through query rewriting, attribute expansion, and intelligent filtering for Elasticsearch-based e-commerce search.
A diagnostic report and optimization recommendations to improve search accuracy and relevance.
Use natural language to search, analyze, and manage Elasticsearch data.
Search external information through an MCP server for LLM-powered agents.
Search across platforms and analyze websites with browser automation.
Perform real-time Google searches via MCP to gather and verify web information.
Lets AI agents run unified web, GitHub, and GitLab searches efficiently.
Enable AI agents to search the web and retrieve structured results.