"Information on using a web browser" matching MCP servers:

Enables AI-powered web searches using DuckDuckGo with automatic summarization via Google's Gemini AI. Supports both summary and detailed analysis modes for search results.

An MCP server that enables web searching, URL content extraction, and summarization without requiring API keys. It also provides advanced mathematical evaluation and multi-language Wikipedia summary retrieval tools.

MCP server that provides web content fetching, summarization, comparison, and extraction capabilities, handling up to 20 URLs per request.

Allows you to search the web using DuckDuckGo and optionally fetch and summarize content from search results.

Enables intelligent web searching using SearXNG with content crawling via Creeper, then summarizes webpage content using LLM to avoid token limit issues. Supports smart filtering with domain blacklist/whitelist and optional LLM-based relevance filtering.

This server provides a note storage system with a custom URI scheme, allowing users to add and summarize notes, with adjustable summary detail levels.

Provides web search, URL fetching, summarization, math evaluation, and Wikipedia tools for LM Studio without needing an API key.

A TypeScript-based MCP server that implements a simple notes system, allowing users to create, access, and generate summaries of text notes through Claude Desktop.

MCP server that searches the web, reads pages, and returns concise summaries with cited sources via the research_web and read_url tools.

A Python MCP server for web research that enables fetching web pages, searching, batch-fetching, extracting links, and summarizing content via client-side sampling, with optional local file access.

A simple note storage system that lets users create and summarize notes with varying detail levels using Claude.

Enables LLM clients to search a firm's precedent vault and draft grounded contract clauses, legal memos, and document summaries.

An HTTP MCP server that indexes large documents into exact-line-numbered sections, enabling AI models to locate, read, summarize, and edit parts of a document without ingesting the whole file.

Enables natural language management of Gmail through MCP tools for searching, analyzing, summarizing, drafting, and sending emails, with AI reasoning and user confirmation for actions.

Fetches category data from a Q&A service API and returns a markdown summary grouped by category.

Enables interactive AI chat through the Anthropic API, with document retrieval, slash commands, and extensible MCP tool integrations.

A Node.js MCP server providing browser search and web page access capabilities, including Google search, intelligent web analysis, and LLM-powered summarization.

Provides clean, bounded web content to AI by filtering HTML noise and optionally summarizing, preventing context window overflow.

MCP server for evidence-based bullet point summarization guidance. Validates and improves bullet lists using scientifically-validated principles from cognitive psychology and UX research.

tooltrim reduces the tokens agents spend re-reading bloated tool results. Run it as an MCP server exposing compress and expand_tool_output, or as a gateway in front of any upstream MCP server: it re-exposes the upstream tools unchanged and shrinks each result (HTML/JSON/logs/tables) before it reaches the model, keeping the relevant content only.