"JSON Web Tokens" matching MCP servers:

Real-time web search with answer-ready results for Claude, Cursor and any MCP client. A Tavily alternative: same speed, 20.2% fewer tokens, higher answer quality (60.7% of decided duels won) on a public benchmark. Hosted on mcp.serpdive.com or npx serpdive-mcp.

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.

Structured web extraction for AI agents. Pass any URL and a prompt, get clean JSON data back. Native MCP server with 100 free requests/month.

Web scraping, crawling, and structured data extraction for AI agents. 5 tools: scrape (clean markdown from any URL), crawl (entire sites), map (discover URLs), extract (structured JSON), and search. 833ms avg latency, single binary, self-hostable.

An enterprise-grade Model Context Protocol server for high-performance web analysis that discovers subpages, provides AI-based page summaries, and extracts structured content for RAG using FastMCP and FastAPI.

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

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.

Shared research cache for AI agents. Caches web research across sessions and users - hit means instant answer from verified sources, miss means your research saves the next dev's tokens. Semantic search with freshness tracking, gap detection, and real-time token measurement via JSONL. Free, open source.

Provides web search capabilities to Claude AI using the Anthropic API, allowing LLMs to access up-to-date information from the web with customizable domain filtering.

Provides free web search and URL summarization using Kagi session tokens, compatible with any MCP client.

Give AI agents eyes on any web page: pixel-perfect screenshots, print-ready PDFs, branded OG images, code images, and structured page extraction (JSON or Markdown).

A metasearch backend MCP server that aggregates results from multiple search engines and knowledge sources into structured JSON for AI agents. It provides unified search capabilities across web, academic, developer, and knowledge providers through MCP tools.

A powerful MCP server for fetching and transforming web content into various formats (HTML, JSON, Markdown, Plain Text) with ease.

Enables retrieval and cleaning of official documentation content for popular AI/Python libraries (uv, langchain, openai, llama-index) through web scraping and LLM-powered content extraction. Uses Serper API for search and Groq API to clean HTML into readable text with source attribution.

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.

Web scraping for AI agents: scrape, map, crawl and batch public pages into Markdown, tables and JSON, with an Evidence Record on every page. Blocked, empty and wrong pages come back as such, with the reason.

Enables LLMs and AI agents to access real-time web data, search websites, and navigate the web without getting blocked. Includes 5,000 free monthly requests and supports web scraping, browser automation, and bypassing geo-restrictions.

Minimizes LLM token consumption via YAML serialization, HTML-to-Markdown distillation, and pre-flight token counting, with tools for web content extraction and metrics database querying.

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.