"Creating a Web API, VSIX Extension, and WPF Application" matching MCP servers:

A focused MCP server that provides a single web_search tool for web searches, integrating Tavily and Brave with automatic fallback and key rotation.

Enables document Q&A with grounded citations using the official Gemini File Search API. Upload documents, create stores, and ask questions that return exact passage citations.

A self-hosted MCP server that crawls, indexes, and searches documentation from any website locally, including private sites requiring authentication. It provides hybrid search capabilities and local embedding generation to maintain privacy while keeping AI assistant knowledge up to date.

Enables extracting clean, structured markdown from any URL—stripping nav, ads, and scripts—for RAG pipelines and AI research agents, with pay-per-call micropayments via x402.

An MCP server that extends AI agents' context window by providing tools to store, retrieve, and search memories, allowing agents to maintain history and context across long interactions.

MCP server for semantic search over PDF documents using RAG, pgvector, and OpenAI embeddings. Includes a web app for document upload and management.

Provides free web search, content fetching, image search, and deep research via SearXNG, no API keys required.

MCP server for searching web documentation via sitemap.xml, enabling semantic search across multiple documentation sites using Ollama embeddings.

Provides standard MCP tools for web search, page fetching with content extraction, and a combined research workflow that returns sources with excerpts, plus a session resource and fact-check prompt template.

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.

A simple application demonstrating Model Context Protocol (MCP) integration with FastAPI and Streamlit, allowing users to interact with LLMs through a clean interface.

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.

Provides a Google search tool via the Serper API, returning structured results and a summary answer for LLMs like Claude.

MCP server that provides web search via LLM API gateways with server-side search, returning cited answers and multi-provider fallback.

A fast, dependency-light MCP server that converts web pages into clean Markdown, structured metadata, and classified links for language models.

An MCP server that runs Apify scraping actors with quality-gated validation, scoring, and retries, returning embedding-ready chunks for AI agents.

MCP server that fetches web pages and uses local Qwen models to answer questions about their content, with site-scoped search and map-reduce chunking for long pages.

A Model Context Protocol server that gives AI assistants access to 7 search providers with intelligent auto-routing. Analyzes query intent and picks the best provider automatically — no manual switching needed. Install, configure your keys, and go.

An MCP server that enables AI models to perform Google Web searches using the Gemini API, complete with citations and grounding metadata for accurate information retrieval. It is compatible with Claude Desktop and other MCP clients for real-time web access.

Monitor and manage Apache Airflow clusters through natural language queries via MCP tools: DAG inspection, task monitoring, health checks, and cluster analytics without API complexity. * Guide: https://call518.medium.com/mcp-airflow-api-a-model-context-protocol-mcp-server-for-apache-airflow-5dfdfb2