Elasticsearch MCP & Search Integrations
Connect Elasticsearch MCP, Algolia MCP, and Meilisearch MCP to Claude. Full-text search, vector search, and web search integrations for knowledge retrieval.
Popular Search MCP Servers
Official and community integrations for search engines
Elasticsearch MCP Server
Full-text search, analytics, and vector search with Elasticsearch
Algolia MCP Server
Lightning-fast search with typo tolerance and AI-powered relevance
Tavily Search MCP
AI-optimized web search designed for LLMs and RAG applications
Exa MCP Server
Neural search engine for finding similar content and semantic queries
Full-text Search Engines
Search documents, products, and content with keyword matching
Elasticsearch MCP
Algolia MCP
Meilisearch MCP
Typesense MCP
OpenSearch MCP
Solr MCP Server
Web Search & Discovery
Search the web with AI-optimized search engines
Tavily Search MCP
Exa MCP Server
Brave Search MCP
SerpAPI MCP
Perplexity MCP
Jina Reader MCP
Vector & Semantic Search
Find similar content using AI embeddings for RAG applications
Pinecone MCP
Weaviate MCP
Qdrant MCP
ChromaDB MCP
Milvus MCP
Vespa MCP Server
What Can Search MCP Servers Do?
Search Documents
Find information in your documents, wikis, and knowledge bases.
Web Discovery
Search the web for current information and research topics.
Semantic Search
Find similar content using AI embeddings and meaning.
RAG Retrieval
Retrieve context for AI to answer questions accurately.
Compare Search MCP Servers
Choose the right search integration for your workflow
| Feature | Elasticsearch | Algolia | Pinecone | Tavily |
|---|---|---|---|---|
| Full-text Search | ✓ | ✓ | — | — |
| Vector Search | ✓ v8+ | Coming | ✓ | — |
| Web Search | — | — | — | ✓ |
| Self-hosted | ✓ | Cloud | Cloud | Cloud |
| AI Optimized | Partial | Partial | ✓ | ✓ |
| Free Tier | ✓ | ✓ | ✓ | ✓ |
Frequently Asked Questions
What is a search MCP server?
A search MCP server connects search engines like Elasticsearch, Algolia, or vector databases to AI assistants through the Model Context Protocol. It enables AI to search documents, find similar content, and query knowledge bases using natural language.
What's the difference between full-text and vector search?
Full-text search (Elasticsearch, Algolia) matches keywords and phrases in documents. Vector search (Pinecone, Weaviate) uses AI embeddings to find semantically similar content. Many modern systems combine both for hybrid search.
Which search MCP server is best for AI/RAG?
For RAG applications, vector databases like Pinecone, Weaviate, or Qdrant are ideal. For web research, Tavily and Exa are specifically optimized for LLMs. Elasticsearch 8+ also supports vector search alongside full-text.
How do I add web search to Claude?
Install a web search MCP server like Tavily, Exa, or Brave Search. Configure your API key and add it to Claude Desktop. You can then ask Claude to search the web and it will use the MCP server to fetch results.
Can I search my own documents with MCP?
Yes! Index your documents in Elasticsearch, Meilisearch, or a vector database. Then use the corresponding MCP server to let AI search your content. This is the foundation of RAG (Retrieval Augmented Generation) systems.
What's the best search for e-commerce?
Algolia and Typesense excel at e-commerce with features like faceted filtering, typo tolerance, and merchandising. Elasticsearch is also popular for large catalogs. All have MCP server options.
How does semantic search work with MCP?
Semantic search MCP servers convert your query into a vector embedding, then find documents with similar embeddings. This understands meaning, not just keywords — 'laptop' finds 'notebook computer' and 'MacBook'.
Can I combine multiple search sources?
Yes! Configure multiple search MCP servers and AI can choose the right one for each query. Use Elasticsearch for your docs, Tavily for web, and Pinecone for semantic similarity — all in one conversation.
Build a Custom Search MCP Server
Create custom search integrations. Build an MCP server, publish to the marketplace, and earn 83% of every sale.