"How to browse the internet" matching MCP servers:

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Model-agnostic, agent-ready Obsidian MCP server with RBAC, SLSA provenance, and native search. 163 tools across 31 domains, multi-vault, pluggable embeddings.

Local-first MCP server providing semantic search over library docs, fully offline. Single Go binary speaks MCP over stdio against a vector index pinned to the binary version. Like Context7 with the internet turned off. Apache 2.0. Linux + macOS, also available as a container image.

Enables MCP hosts to discover, browse, and load Agent Skills from one or many SKILL.md libraries over the Model Context Protocol, with namespaced libraries, search/list/get tools, progressive disclosure, and a digest-verified pull client for syncing skills to disk.

A basic MCP server setup guide demonstrating how to configure and run Python-based MCP servers with integration examples for Bright Data web scraping and Apify Actors for product data collection.

Enables AI assistants to search, browse, and save to a semantic knowledge graph with vector search and hierarchical organization.

Hybrid retrieval MCP server for searching team markdown journals using BM25 and local vector embeddings, with tools for search, browse, and regex lookup.

Enables MCP clients to search, browse, read, and manage IMA knowledge base content, including notes, web imports, and file uploads, using the official IMA OpenAPI.

Enables MCP-capable clients to search team knowledge, browse an integration catalog, and get sourced product answers through deterministic, offline tools.

Enables AI agents to fetch one or many web pages concurrently and receive clean, LLM-ready Markdown with navigation, ads and boilerplate stripped away, plus extracted metadata such as title, description, author, Open Graph tags and canonical URL. It runs locally over stdio with no API key or account, requiring only a single command.

Enables AI and LLM systems to interact with the Buttondown newsletter service, supporting email drafting, scheduling, analytics retrieval, and list management through a Model Context Protocol interface.

A Model Context Protocol server that enables AI models to perform real-time internet and knowledge searches through Higress, enhancing model responses with up-to-date information from Google, Bing, Arxiv, and internal knowledge bases.

Provides OpenCode with adaptive long-term memory by storing preferences, lessons, and usage history locally in SQLite, enabling AI to remember and adapt to users through context-based learning.

Enables AI agents to autonomously browse inventory, negotiate terms, manage carts, and execute secure payments on Shopify stores using standardized protocols. It provides a bridge for LLMs to handle the entire commerce lifecycle from discovery to order tracking through a verifiable mandate chain.

Provides tools to fetch and search news from The Verge's RSS feed, allowing users to get today's news, retrieve random articles from the past week, and search for specific keywords in recent Verge content.

Enables searching and retrieving documentation from crawled documentation sites as an MCP server, allowing coding agents to query real docs instead of relying on training data.

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

A Model Context Protocol server that enables AI assistants to perform real-time web searches, retrieving up-to-date information from the internet via a Crawler API.

Provides AI assistants with access to Civitai's collection of AI models, enabling users to browse, search, and discover AI models through MCP-compatible AI assistants.

Enables an agent to run ten ready-made research and monitoring workflows — competitor digests, cited reports, paper alerts, market maps, regulatory and due-diligence watches — pulling from Firecrawl, Tavily, GitHub and landing results in Notion, Slack, Google Docs, Sheets and Linear. Fields are filed with the user's own keys held in the operating system keychain, and every action that creates, sends or changes anything is shown and approved first.