couchbase-mcp

3.2

databases ai_chatbot

If you are the rightful owner of couchbase-mcp and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to henry@mcphub.com.

This project demonstrates the implementation of a Model Context Protocol (MCP) server that provides semantic search capabilities for Star Wars planets using Couchbase's vector search functionality.

The Model Context Protocol (MCP) is a standardized way for AI models to interact with external tools and data sources. This implementation creates an MCP server that allows AI models to fetch detailed information about Star Wars planets and find similar planets based on vector embeddings. The server uses Couchbase's vector search capabilities to efficiently find similar planets by comparing vector embeddings stored in the database. The implementation includes features such as efficient vector search, timeout protection, connection management, error handling, and type safety through a full TypeScript implementation.

Features

Efficient Vector Search: Utilizes Couchbase's vector search index for fast similarity lookups.
Timeout Protection: Implements timeouts for both search and document fetching operations.
Connection Management: Properly manages Couchbase connections with cleanup.
Error Handling: Comprehensive error handling and debugging support.
Type Safety: Full TypeScript implementation with proper type definitions.

Tools

fetch_planet_name
Fetch a Star Wars planet by name.
find_planets_which_are_similar
Find similar planets by name to the given name.

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