"A product search on eBay for a specific item" matching MCP servers:

Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

Production-ready MCP server providing RAG, hierarchical memory, and 8+ tools for AI agents via the Model Context Protocol.

A Python-based MCP server that enables document-based question answering by processing PDF, TXT, and Markdown files through OpenAI's API. It provides hallucination-free responses based strictly on document content using semantic search and includes a web interface for management.

Enables document-based question answering using OpenAI's GPT-4 with semantic search and embeddings. Upload PDF, TXT, or Markdown files and get answers strictly based on document content with source attribution and confidence scores.

A full-feature MCP server that serves as a product-development copilot, providing RAG search, SQL queries, and inline chart visualizations from seeded product data, with per-user identity and its own OAuth login.

Exposes product catalog and semantic search as tools for an LLM agent, enabling natural language product recommendations based on intent rather than keyword matching.

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for eBay Analytics (beta): https://www.cdata.com/download/download.aspx?sku=JJZK-V&type=beta

Enables AI-powered Amazon product searches and recommendations by integrating the Amazon API with Hugging Face models. It allows users to filter products by price and specific features to receive tailored shopping suggestions.

A comprehensive Model Context Protocol (MCP) server implementing the latest MCP specification with tools, resources, prompts, and enhanced sampling capabilities that features HackerNews and GitHub API integrations for AI-powered analysis.

Universal search engine for AI agents. Discover products, services, and businesses across every category. 10 MCP tools, zero LLM calls, millisecond responses.

Federated, local-first search for AI agents: one query fans across transcripts, files, a knowledge graph, a vector store, the live web, and YouTube, fused by trust-weighted RRF into one ranked answer. Five modes (grep/lexical/semantic/hybrid/rerank), runs entirely on your machine over MCP.

CLI-first web and code search for agents, with MCP support for integration with IDEs like Cursor, VS Code, and Claude Code.

A semantic search system for Claude Code transcript history, exposed as an MCP server so Claude Code can query its own past sessions.

Enables AI agents to search local Markdown documents using natural language, with automatic indexing and section-level retrieval.

MCP search and evidence tool for AI agents. Rewrites queries, zooms into source domains, and returns sourced answers with metrics.

Enables AI agents to maintain persistent, searchable two-layer memory with 37 tools, hybrid search, knowledge graphs, and enterprise features like authentication and backups.

MCP server for hybrid documentation search (keyword + vector) and RAG chat, enabling natural language queries with cited answers from indexed repositories.

MCP server that provides secure access to a serverless Markdown wiki on AWS, enabling AI assistants to read, search, and edit pages with space-level permission checks and Bedrock-powered semantic search.

Enables fully local semantic search over a Roam Research graph via MCP, providing tools for hybrid retrieval, index refresh, and stats while keeping all content on-machine.