"Equipment or items used in windsurfing" matching MCP servers:

Single-binary local RAG MCP server in Rust — MiniLM compiled in, hybrid BM25+dense, zero runtime downloads

Provides AI agents with persistent, searchable memory using semantic search, auto-linking, and categorization, with zero-config local setup or production-ready external providers.

An MCP server that retrieves resume/experience evidence relevant to a job description via vector RAG, and tracks fit-analysis results in a configurable tracking store (Notion or SQLite), with tools like match_job, push_to_tracker, and list_applications.

An MCP server for semantic search and retrieval of indexed Slack messages stored in Qdrant using Cohere reranking via AWS Bedrock. It enables users to search through Slack history, retrieve full message threads, and access channel or user statistics through natural language.

MCP server for semantic search in an Obsidian Second Brain vault using self-hosted Qdrant and Google Gemini embeddings.

Turns a tools.yaml contract into typed, tenant-guarded vector database tools that agents can use via Python imports or MCP.

A server that enables vector and keyword search capabilities in Typesense databases through the Model Context Protocol, providing tools for collection management, document operations, and search functionality.

Enables AI agents to manage and search data in Redis using natural language. Supports hashes, lists, sets, sorted sets, streams, JSON, and vector search.

Enables Claude to store and query personal finance transactions using semantic search. Transactions are persisted in ChromaDB and JSON, allowing natural language questions about spending trends and portfolio allocations.

A memory server for Claude that stores and retrieves knowledge graph data in DuckDB, enhancing performance and query capabilities for conversations with persistent user information.

A flexible memory system for AI applications that supports multiple LLM providers and can be used either as an MCP server or as a direct library integration, enabling autonomous memory management without explicit commands.

Mem0-compatible persistent memory for AI agents - write facts once, recall them semantically in any session. Self-hostable open-source server, or managed cloud with a remote MCP endpoint at https://deepmem.dev/mcp.

An offline-first, governed memory and knowledge server for AI agents that provides Remember, Search, Update, and Forget operations with hybrid retrieval, semantic embeddings, and NID-based authentication. It can be used as an MCP server via stdio or Streamable HTTP, enabling agents to persist and query memories and wiki knowledge.

A high-performance MCP server for semantic search and codebase indexing using the Qdrant vector database. It features optimized embedding pipelines, AST-aware chunking, and git metadata enrichment for fast, privacy-focused local or remote search.

Helps developers tackle legacy codebases by giving AI coding assistants context through Qdrant vector store and Agentic RAG with Ollama or DeepSeek.

Enables storing, semantically searching, listing, and deleting text records in any Qdrant collection using plain vectors compatible with default LangChain and n8n setups.

Enables semantic search over a Qdrant knowledge base through MCP, with optional domain filtering and stdio or Streamable HTTP transport.

A focused local-paper RAG MCP server that imports PDFs, indexes them into SQLite and ChromaDB, and retrieves section-aware paper chunks for use with Claude Code, Codex, or any MCP client.

Exposes LangChain and Anthropic Claude capabilities as tools for generating production-ready RAG systems, Supabase vector stores, and document ingestion pipelines. It enables users to instantly scaffold AI infrastructure and document processing code through natural language prompts in MCP-compatible clients.

Enables AI development tools to perform semantic search and document relationship analysis on vectorized content stored in Qdrant databases.